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Knowledge management
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Table of contents :
Cover
Half Title
About the Author
Title
Copyright
Dedication
Preface
Organisation of the Book
Contents
1. Introduction to Knowledge Economy
Context and Relevance of Knowledge Economy
The Changing Landscape of the Business
Role of Knowledge in Business Management
Paradigm Shift in the Way Business is Done
Knowledge Economy and Moore’s, Gilder’s, Metcalfe’s Laws
Distinctive Character of Knowledge Economy
Knowledge Economy Demands New Strategic Approach to Business
Knowledge Driven Network Organisation
Findings of the Association of Knowledge Work
India and the Knowledge Economy: Leveraging on Strengths and Opportunities (An Extract from the World Bank Report)
End Notes
Questions
2. What is Knowledge?
Data–Information–Knowledge–Business Intelligence
Attributes of Knowledge
Expression of Knowledge
Human Thinking and Learning
Tacit and Explicit Knowledge
Knowledge: A Driver for Creativity and Innovation
Knowledge: A Strategic Resource
Business Benefits of Knowledge
Tools for Knowledge Management
End Notes
Questions
3. Knowledge Management
Knowledge Management
Why Knowledge Management Now?
Knowledge Initiative
Knowledge Management Process
Knowledge Management Processes
Knowledge Development and Management Cycle
Knowledge Networking
Principles Behind KM Success
Thematic Analysis of Knowledge Management
SECI Model: Knowledge Transformation and its Dynamics
End Notes
Questions
4. Knowledge Management System
Generic Model of Knowledge Management System
Knowledge Management System: Development Cycle
Knowledge Management System: Application Cycle
Challenges in Developing KMS
KMS Lifecycle
KM System Architecture
Knowledge Construction Architecture
Implementation of KMS
The Learning Concept and Knowledge Management System
End Notes
Questions
5. Knowledge Management: Development
Introduction to KM
Establish a Knowledge Strategy Framework
Validation of Knowledge
Validation of Knowledge Through Knowledge Models
Knowledge Creation
Acquisition of Knowledge
Knowledge Acquisition Techniques (KAT)
End Notes
Questions
6. Knowledge Management: Application Phase
Knowledge Transfer
Knowledge Sharing: A Process
Knowledge Transferring Sharing and Tools
Codification of Knowledge
Build Knowledge Maps
Designing Knowledge Transfer and Sharing Strategy
Network Structures for Knowledge Transfer
Knowledge Asset, Intellectual Capital and Property
Skandia Model for Measuring Intellectual Capital
Successful Implementation of KM Initiative
End Notes
Questions
7. Organisation Learning and Learning Organisation
Building a Learning Organisation
Five Core Disciplines of a Learning Organisation
The Concept of Learning Organisation
Organisation Learning
Organisation Knowledge
Human Resource Management for KM
Paradigm Shift in HRM Functions
End Notes
Questions
8. Knowledge Management: Tools and Technology
Information and Communication Technology (ICT)
Unified Communications Technology (UCT)
WiMAX Technology
Data Warehouse and Data Mining, Business Intelligence
OLAP
Search Engines
Intelligent Agents
Knowledge Portal, Knowledge Products
Groupware Technology for Knowledge Transfer
End Notes
Questions
9. Case Illustrations of Knowledge Management
Data Warehousing and Data Mining
Knowledge Portal
Knowledge Products
Intelligent Agents
Unified Communications Technology Solutions
Business Case for Knowledge Management
KMS Applications
End Notes
Questions
Knowledge Management Vocabulary
References
Index

Citation preview

Knowledge Management

About the Author Waman S Jawadekar is a management consultant in IS and IT advising corporates on IT strategy for impacting business performance. He is an MA in Statistics with Operations Research from Bombay University and MBA (Systems and Marketing) from Stanford University, USA. His focus is on application of technology to management process. During a career of thirty years in the industry, the author has worked with different business organisations in various capacities in higher management: as manager, systems and technology, Sandvik Asia Ltd, general manager, computer and systems division, Kirloskar Oil Engines Ltd, general manager, IS and IT Thyssen Krupp Industries Ltd, consultant (project management) Mastek Ltd, and lead consultant in Systime Computer Systems (India) Ltd, a CMS group company for J.D. Edward ERP package. The author has rich experience in designing information driven manufacturing and management systems for exploiting the technology advantage, especially for product manufacturing and project executing companies. His role in consulting is that of the adviser/change agent/implementer on IT strategy, ERP, product development, software project management and learning management systems to a number of companies. His clients include Garware Wall Ropes Ltd, DSK Developers Ltd, Soft Ideas Pvt Ltd, Prateek Apparels Ltd, Thyssen Kruup Industries Ltd, Weiler International Electronics Ltd, PROEX Pvt Ltd, DSK InfoTech Ltd, National Defense Academy, Relationware CRM Pvt Ltd, ENTHEOS Management Services Pvt Ltd, Werhardt Infosys, Kirloskar Copeland Ltd, Genesis Management & Market Research (P) Ltd. SUVI Aviation Ltd and Cubix Micro Systems (I) Pvt Ltd. A life member of Computer Society of India, he shares his experiences through workshops and seminars for students and professionals. He is the chairperson of the academic council of Pune Institute of Computer Technology (PICT), School of Technology & Management, Pune. He is a recognised resource person for strategic design of MIS, for performance management and knowledge management, for creating a learning organisation, requirement engineering and analysis, for developing RDD and SRS, software quality assurance, for customer satisfaction, software project management, data warehousing and mining, for knowledge generation, software risk analysis and management, for mitigating the risk impact, BPR achieving process excellence, transforming an enterprise to a digital firm and for creativity and innovation for business transformation. The publications to his credit are: • Management Information Systems [now in its fourth edition] (Tata McGraw-Hill Education) • Software Engineering (Tata McGraw-Hill Education) • Software Engineering, Primer (Tata McGraw-Hill Education) • Reengineering Business Organization (Jaico, New Delhi) He can be contacted at [email protected]

Knowledge Management

Waman S Jawadekar Management and IT Consultant Pune

Tata McGraw Hill Education Private Limited NEW DELHI McGraw-Hill Offices New Delhi New York St Louis San Francisco Auckland Bogotá Caracas Kuala Lumpur Lisbon London Madrid Mexico City Milan Montreal San Juan Santiago Singapore Sydney Tokyo Toronto

Tata McGraw-Hill Published by the Tata McGraw Hill Education Private Limited, 7 West Patel Nagar, New Delhi 110 008. Knowledge Management Copyright © 2011, by Tata McGraw Hill Education Private Limited. No part of this publication may be reproduced or distributed in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise or stored in a database or retrieval system without the prior written permission of the publishers. The program listings (if any) may be entered, stored and executed in a computer system, but they may not be reproduced for publication. This edition can be exported from India only by the publishers, Tata McGraw Hill Education Private Limited. ISBN (13): 978-0-07-070086-4 ISBN (10): 0-07-070086-9 Vice President and Managing Director—McGraw-Hill Education: Asia-Pacific Region: Ajay Shukla Head—Higher Education Publishing and Marketing: Vibha Mahajan Publishing Manager—B&E/HSSL: Tapas K Maji Associate Sponsoring Editor: Piyali Ganguly Assistant Manager (Editorial Services): Anubha Srivastava Senior Production Manager: Manohar Lal Production Executive: Atul Gupta Deputy Marketing Manager: Vijay S Jagannathan Senior Product Specialist: Daisy Sachdeva General Manager—Production: Rajender P Ghansela Assistant General Manager—Production: B L Dogra Information contained in this work has been obtained by Tata McGraw-Hill, from sources believed to be reliable. However, neither Tata McGraw-Hill nor its authors guarantee the accuracy or completeness of any information published herein, and neither Tata McGraw-Hill nor its authors shall be responsible for any errors, omissions, or damages arising out of use of this information. This work is published with the understanding that Tata McGraw-Hill and its authors are supplying information but are not attempting to render engineering or other professional services. If such services are required, the assistance of an appropriate professional should be sought. Typeset at Bharati Composers, D-6/159, Sector-VI, Rohini, Delhi 110 085, and printed at Adarsh Printers, C-50-51, Mohan Park, Naveen Shahdara, Delhi 110 032 Cover Design: Aishwarya Padhye Cover Printer: SDR Printers RCXCRRBZRYLLA The McGraw-Hill Companies

To My wife Sudha Mother of Kalyani & Sachin Mother-in-law of Shwetal & Pradnesh Sudha Aaji of Siya, Sanket, Siddhant & teacher & mentor of many

Preface Business today is under pressure due to the far-reaching impact of globalisation, cut-throat competition from unheard of quarters, demanding customers, compelling business partners and stakeholders and government interventions to bring in inclusive growth. These challenges are known to business leaders. The real challenge is: how do we respond to them quickly and successfully to forge ahead towards excellence? Failing to respond quickly is suicidal. Conventional strategic thinking based on SWOT analysis and adopting strategies like TQM, organisation and business restructuring, BPR, focusing on business performance and strengthening core competencies have all lost the sharpness of the cutting edge. A totally new approach to business strategy design is necessary to keep existing competitive necessities effective, and to create new competitive advantages to maintain unchallenged business leadership. The mother of these challenges is continuously changing Information and Communication Technology (ICT). The changes brought about by ICT are dramatic and radical to the extent that ICT has changed business models and created new business opportunities affecting the culture and behaviour of an individual as well as that of a business organiation. Today, the size and scale of business is not its strength. Real strength lies in how smart the organisation is in responding to these challenges. Knowledge and BI are the key drivers of the business of the day. ICT has made organisations virtual, work culture collaborative and hierarchy a network structure. It has blurred organisation boundaries and made it an enterprise of business partners and stake holders. The pyramids have collapsed and become lean and flat, taking a shape of diamonds. Organisations are networked by meshes of computer networks, communication networks, people networks, and knowledge networks. Fixed assets net worth has taken a lower rank making way for knowledge. Human capital and intellectual capital of the organisation is valued high in market valuation of the business. There is a paradigm shift in economy from agro-industrial-service to knowledge economy. Organisations have no choice but to become knowledge-driven, learning organisations. From a business strategic perspective, knowledge management is about obsolescing what you know before others do, and profiting by creating challenges and opportunities others haven’t even thought about. In the bigger picture, the focus of knowledge management is on the ever-changing environment in which societies, organisations and individuals live, work, learn, adapt and survive. Business strategy mix is heavily loaded with knowledge content. Strategy design is based on customer knowledge, process knowledge, technology knowledge, product knowledge and so on. For successful business strategy evolution, knowledge strategy has to be in place to back the design and implementation of business strategy. This calls upon management to recognise Knowledge Management (KM) as a function supporting other business functions, so that these may perform excellently. KM function in the organisation remains a source for knowledge resource but it requires knowledge innovation matching the changing and competitive requirements of the business. Entovation International defines knowledge innovation as creation, evolution, exchange and application of new ideas into marketable goods and services for the success of enterprise, for the vitality of nation’s economy and for the advancement of the society.

viii Preface

This book is a repository of knowledge and knowledge management. It has nine chapters—covering topics from knowledge economy to knowledge development to KM technology. Human resource role and issues are discussed, and the book concludes with a chapter on the application of knowledge to business management, justifying a convincing case for creating a KM function in the organisation. It convincingly makes the case for an organisation to become a learning organisation. The book is presented in a text book format for young students aspiring to become successful professional knowledge workers. But while scripting the text, working professionals are also kept in mind and cases and questions are framed for professionals to resolve. The content of the book is supported by the material sourced from the internet repository and from published books and journals. They have been acknowledged and any omission would be an unintentional oversight. It gives me a great pleasure in acknowledging with thanks the contribution of Aishwarya Padhye, and Anuja Borker, communication designers who exhibited the entire subject symbolically in nine pictures. I would also like to acknowledge the following reviewers for their invaluable feedback: • V. S. Manjunath, NITTE Meenakshi Institute of Technology, Bangalore • Raj Karan Gupta, Galgotias Business School, Uttar Pradesh • Vijendra Solanki, Appejay Institute of Management, Uttar Pradesh • Rajeev Jain, Rajasthan Vidyapeeth University, Rajasthan • Himanshu Joshi, International Management Institute, New Delhi • Manisha Dubey, BVIMSR, Maharashtra • Sujatha, PSGIM, Coimbatore • M. V. Subha, Anna University, Coimbatore Waman S Jawadekar (Email: [email protected])

Organisation of the Book • • • • • •

The book has nine chapters and ’Knowledge Management (KM) Vocabulary’, a glossary. The first six chapters deal with main subject of knowledge management. Chapter Seven focuses on the human and organisation side of knowledge management. Chapter Eight is devoted to tools and technology that drive the KM function. Chapter Nine exposes the reader to success stories of KM applications. Knowledge Vocabulary, a glossary lists critical terms and key words in KM.

Chapter 1 Focuses on Knowledge Economy • Context and Relevance of KM in the Changing Landscape of Business and Paradigm Shift in the Way Business is Done. • Emergence of Knowledge Economy Demanding Knowledge Driven Strategic approach to Business Management and the Need of becoming a Learning Organisation

Chapter 2 Focuses on Data, Information, Knowledge • Data, Information, Knowledge, Business Intelligence • Types of Knowledge, Tacit and Explicit Knowledge • Knowledge: a Driver for Creativity and Innovation • Knowledge a Strategic Resource • Business Benefits of Knowledge

Chapter 3 Focuses on Management of Knowledge • Knowledge Management • Knowledge Development and Management Cycle • Thematic Analysis of Knowledge Management • Knowledge Transformation and its Dynamics • SECI Model and DKCU system • Business Case for Knowledge Management, Alber’s framework

Chapter 4 Focuses on KM Design and Architecture • Generic Model of Knowledge Management System • Challenges in Developing KMS • KM System Design and Architecture

x

Organisation of the Book

• Knowledge Construction Architecture • Implementation of KMS

Chapter 5 Focuses on KM for Business strategy and (Identification, Validation, Creation, Acquisition) • KM, Business Strategy and Knowledge Link • A Knowledge Strategy Framework • Validation of Knowledge through Knowledge Models • Creation and Acquisition of Knowledge • Knowledge Acquisition Techniques (KAT)

Chapter 6 Focuses on KM to Transfer, Measure, Capitalise and Control • Knowledge Transfer and Sharing • Knowledge Mapping • Knowledge Asset, Intellectual Capital and Property • Skandia Model for Measuring Intellectual Capital • Successful implementation of KM Initiative

Chapter 7 Focuses on Organisation Learning and Learning Organisation (Management of Human Capital) • The Concept and Building of a learning organisation • Five Core Disciplines of a Learning Organisation. • Organisation Learning • Human Resource Management for KM and Paradigm Shift in HRM functions

Chapter 8 Focuses on Tools and Technology for Successful KM Implementation • ICT, UCT, WiMAX Technology, Groupware Technology • Data Warehouse and Data Mining for Knowledge Search • Search Engines and Intelligent Agents • Knowledge Portal, Knowledge Products

Chapter 9 Focuses on Case Illustrations of Knowledge Management and Making a Business Case for Knowledge Management where following Tools and Technology are Used • Data Warehousing and Data Mining • Knowledge Portal, Knowledge Products • Intelligent Agents • Groupware Technology • Unified Communication Technology Solutions • KMS Applications

Contents Preface Organisation of the Book 1. Introduction to Knowledge Economy Context and Relevance of Knowledge Economy 3 The Changing Landscape of the Business 5 Role of Knowledge in Business Management 6 Paradigm Shift in the Way Business is Done 7 Knowledge Economy and Moore’s, Gilder’s, Metcalfe’s Laws 9 Distinctive Character of Knowledge Economy 11 Knowledge Economy Demands New Strategic Approach to Business 14 Knowledge Driven Network Organisation 16 Findings of the Association of Knowledge Work 17 India and the Knowledge Economy: Leveraging on Strengths and Opportunities (An Extract from the World Bank Report) 19 End Notes 23 Questions 24

vii ix 1

2. What is Knowledge? Data–Information–Knowledge–Business Intelligence 29 Attributes of Knowledge 34 Expression of Knowledge 36 Human Thinking and Learning 39 Tacit and Explicit Knowledge 44 Knowledge: A Driver for Creativity and Innovation 50 Knowledge: A Strategic Resource 52 Business Benefits of Knowledge 55 Tools for Knowledge Management 56 End Notes 57 Questions 60

27

3. Knowledge Management Knowledge Management 67 Why Knowledge Management Now? 68 Knowledge Initiative 72 Knowledge Management Process 75

65

xii Contents

Knowledge Management Processes 77 Knowledge Development and Management Cycle 79 Knowledge Networking 82 Principles Behind KM Success 83 Thematic Analysis of Knowledge Management 86 SECI Model: Knowledge Transformation and its Dynamics End Notes 101 Questions 104

94

4. Knowledge Management System Generic Model of Knowledge Management System 111 Knowledge Management System: Development Cycle 115 Knowledge Management System: Application Cycle 118 Challenges in Developing KMS 122 KMS Lifecycle 123 KM System Architecture 126 Knowledge Construction Architecture 129 Implementation of KMS 132 The Learning Concept and Knowledge Management System 137 End Notes 138 Questions 141

109

5. Knowledge Management: Development Introduction to KM 147 Establish a Knowledge Strategy Framework 154 Validation of Knowledge 156 Validation of Knowledge Through Knowledge Models Knowledge Creation 160 Acquisition of Knowledge 168 Knowledge Acquisition Techniques (KAT) 169 End Notes 180 Questions 183

145

157

6. Knowledge Management: Application Phase Knowledge Transfer 189 Knowledge Sharing: A Process 192 Knowledge Transferring Sharing and Tools 195 Codification of Knowledge 197 Build Knowledge Maps 201 Designing Knowledge Transfer and Sharing Strategy 204 Network Structures for Knowledge Transfer 208 Knowledge Asset, Intellectual Capital and Property 209

187

Contents xiii

Skandia Model for Measuring Intellectual Capital Successful Implementation of KM Initiative 216 End Notes 218 Questions 221

211

7. Organisation Learning and Learning Organisation Building a Learning Organisation 229 Five Core Disciplines of a Learning Organisation 234 The Concept of Learning Organisation 241 Organisation Learning 243 Organisation Knowledge 245 Human Resource Management for KM 247 Paradigm Shift in HRM Functions 250 End Notes 252 Questions 255

225

8. Knowledge Management: Tools and Technology Information and Communication Technology (ICT) 259 Unified Communications Technology (UCT) 261 WiMAX Technology 266 Data Warehouse and Data Mining, Business Intelligence 270 OLAP 276 Search Engines 277 Intelligent Agents 278 Knowledge Portal, Knowledge Products 284 Groupware Technology for Knowledge Transfer 289 End Notes 290 Questions 293

257

9. Case Illustrations of Knowledge Management Data Warehousing and Data Mining 297 Knowledge Portal 300 Knowledge Products 306 Intelligent Agents 309 Unified Communications Technology Solutions 312 Business Case for Knowledge Management 313 KMS Applications 317 End Notes 324 Questions 327

295

Knowledge Management Vocabulary References Index

329 333 335

1

Knowledge Economy

Chapter

(Paradigm Shifts in the Way Business is Done)

This Chapter Deals with • • • • • • • • •

Context and Relevance of Knowledge Economy The Changing Landscape of Business Role of Knowledge in Business Management Paradigm Shifts in the Way Business is Done The Knowledge Economy and Moore’s, Gilder’s, Metcalfe’s Laws Distinctive Character of Knowledge Economy Knowledge Economy and New Strategic Approach to Business Knowledge Driven Network Organisation India and the Knowledge Economy

Learning Outcome You will understand how globalisation of business has resulted in a paradigm shift in the traditional ways of business management. The shift in business is knowledge driven. The transition from industrial economy to knowledge economy is complete. Knowledge, knowledgeable people and technology are the enablers of the organisation.

“Knowledge is at the heart of much of today’s economy, and managing knowledge has become vital to the organisation’s success.” —Kluge “The transformation from a world largely dominated by physical resources to a world dominated by knowledge implies a shift in the locus of economic power as profound as that which occurred at the time of the industrial revolution.” —Burton-Jones

CONTEXT AND RELEVANCE OF KNOWLEDGE ECONOMY The 21st century is going through several changes and transformations impacting the economy due to globalisation of business, regulatory changes in international trade, increasing customer awareness, demanding customers, and unstoppable progress of Information and Communication Technology (ICT). Management gurus like Tom Peters, Gary Hamel, Peter Drucker and C. K. Prahalad have given several prescriptions to deal with the changing business scenario in an effective manner. The essence of their recommendations is that organisations should become more flexible, lean, flat and learn to be responsive to face the new challenges of the century. In context of India, the organisations which were ranked 100 in the nineties have not maintained their ranking in the last decade. New organisations have taken their place. Some of them have improved upon their ranking. The century is witnessing new business models emerging out of restructuring, redefining, reinventing the business, systems and processes. Those who did not address the challenges of change have climbed down in the ranking or are facing the risk of extinction. The single most important driver of this radical change is ICT, Information and Communication Technology, affecting both the internal and the external world of the organisation. ICT can be factored into six components. • Processing Computing, Collaborating and Communication • Interfacing and Connectivity Networking—LAN, WAN, Internet • Storage and Sharing DBMS and Delivery Technology • Hardware Computers, Laptops, PDAs, Mobile Phones, Mobile Devices • Software Operating systems, Languages, Packages and so on • Input Types Data, Text, Audio/Video, Multi Media

KEY TERMS • Globalisation of Business • Agricultural Economy to Knowledge Economy • Moore’s • Gilder’s • Metcalfe’s Laws • ICT Revolution • Business Transformation to Pull Model • Knowledge Society • Knowledge Driven Networked Organisation • Human Capital • Structural Capital • Customer Capital

All these components are continuously improving, becoming more efficient and effective in performing business operations. The all-round improvement in capabilities of these components have impacted business in the following manner. It is an ICT revolution which has made the following changes. • Process Short, Fast and Intelligent • Organisation Structure Flat and Lean • Business Model Distributed Globally, Automated Processes • Process Character Integrated, Maintaining Local integrity • Organisation Model Customer Centric Service Model • Organisation Working Collaborative The ICT revolution has transformed the business environment radically. It has affected the way we live, work and perform. The independent business organisations are now interdependent organisations. They collaborate to achieve their respective goals. They share information and have access to each other’s information. The process scope now extents beyond the organisation boundaries. All businesses have become customer centric. The customer initiates the process and the organisation responds. Customer requirements and their fulfillment are handled by the organisation and its alliance partners, each doing a limited role based on its core competency. Along with the resources, information and knowledge are also shared among them. If the history of business transformation is researched, it well be found that the core competency and the drivers have changed in almost every decade since the seventies. First, it was the ability to procure raw material, then possession of manufacturing technology, followed by capital and capacity strength, and now knowledgeable learned human resource. The same transformation can be put in different way—starting with agrarian economy, followed by industrial economy and now HR: knowledge economy. In the era of agricultural economy, land was an asset and the land owner engaged people to cultivate the land to grow crop by the season. The water was the only resource, available in plenty. The management strategy was to exploit the land for food production, limiting it to the owner’s requirement. It was a local affair of the land owner and the people around. Commodities were exchanged in return for labur. The critical resource was the land. Those who had land were the leaders. In the industrial age, people were not paid for what they had, but ware paid what they did and the employer told them how to do it. The management strategy was to turn raw materials into finished products more efficiently and effectively. Manufacturing technology, plant and equipment were the critical resources. The people engaged for converting raw material into product were paid for the hours spent by them in the factory. Business strategy was driven by manufacturing capacity and underlying technology. Those who were leaders in this activity were also business leaders. In the era of the Internet economy, the strategy was to get a bigger market, split and could distribute the process of manufacturing amongst those who can do a thing best in all respects, and make whole business competitive. The connectivity for speed and collaboration for productivity was the business mantra. The sharing among the business partners, very broadly, was that of factored process components, such as design, component manufacturing, assembly, distribution and delivery to the customer. The critical resource was management’s competence in core process management in such a way that the cost of product was competitive and the quality of the offer was very high. The business model was product centric as visualised by the management for the customer. It was termed Push Model, shown in Figure 1.1. The strategy was to exploit core competency by each business partner. Leverage was on what one could do best and the rest was done by others. The product strategy largely was driven by material and manufacturing

Product Strategy

Business Goal

Build Org Structure

Command and Control

Change the Strategy

Evaluate Achievements

Fig. 1.1 Push Model of the Business: Organisation Driven

resources. The management process was designed to push the product in the market. GE calls this model ‘Inside Out’.

THE CHANGING LANDSCAPE OF THE BUSINESS This century is termed as the HR: Knowledge Economy. The economy is driven by the knowledge, the information, and the people the organisations have. In this economy every aspect of the business has changed radically. Business model, strategy, systems and processes are now way different than earlier. The critical resource of the business organisation is ‘information and Knowledge’ possessed for proactive customer management. Manufacturing capacity and technology have become essential competitive necessities. But that is not enough; one should have customer knowledge in terms of requirements of functions and features of product or service, behavioural and operational needs, price, quality, the most important service, pre-and post-delivery. The business model is termed as customer centric ‘Pull Model’ shown in Figure 1.2. GE calls this model as’ Outside in’ Missing and Goal

External Signals

Fig. 1.2

Sense Customer Needs

Operational Signals

Build Flexible Structure

Knowledge Driven Participative Management

Knowledge Based Strategy

Pull Model of the Business: Customer Driven

In the knowledge economy, over and above the normal traditional management functions, like finance, materials and production, focus is on knowledge management. The organisations that possess and develop knowledge about market, customer, trends in economy, demographic changes and so on will survive and grow. Knowledge is the key driver which helps to conduct business operations correctly and also aids in improving the performance by 360 degree. There is a paradigm shift in the way the business is done. The employees are paid more for knowledge they possess and create. There is a change of focus in strategy, systems and processes as detailed below. • Focus on competitive advantage and not on profits • Focus on all round customer experience and not on customer satisfaction • Focus on attaining a status of zero customer problems and not on zero product or service defects • Focus on maximising revenue and not on control of cost

• Focus on business opportunity and not on its financial cost • Focus on competition as an opportunity and not as a threat to business • Focus of design on performance and not just on functions and features • Focus on recruiting passionate professionals and not on just professionals • Focus on managing competitive environment and not on just managing resources In the knowledge economy, organisation’s knowledge means, knowledge of individuals, teams, groups and employees, at large, about the business they are in. The knowledge includes customer requirement knowledge, product or service knowledge, problems and solutions knowledge, and so on. Also, organisations make conscious effort to build knowledge about emerging scenario in technology and its impact on business and competition. Knowledge has three structural components—people, processes and technology as shown in Figure 1.3. Together they form a body ‘knowledge’. People are the generators, users and custodians of knowledge. Technology is the facilitator to handle the knowledge efficiently and effectively. Processes are the enablers to create, store, and share the knowledge. People

Processes

Technology

Fig. 1.3

Structural Components of Knowledge

The organisations in knowledge economy are knowledge driven. They treat knowledge as an asset and regard it as competitive necessity. Some develop knowledge at the level of Intellectual Capital (IC) and build brand value around it. Knowledge economy’s mantra is collaboration. Efficient collaboration requires a well knit connectivity network for communication, exchange of information, establishing process links, and so on. The collaboration through network expedites the progress of work, saves cost of operations and increases benefits to customer, and attains higher business performance. The networks in this century are global. They span over different countries and work efficiently from all angles. The network structure includes LANs, WAN, VPN and Internet. The networks are secured for business operations and financial and material transactions. The organisations are building knowledge networks, communities and interest groups for mutual benefits. Today, networks help us to book airline and Railway tickets online, order grocery for home delivery, ascertain bank balance, transfer money from one account to other, check customer inventory and replenish it, (if due for replenishment) and sort out the queries on billing and payment. In all these activities, multiple agencies and organisations, each a separate legal entity, are involved in completing the activities. The networks and ICT potential have made this possible.

ROLE OF KNOWLEDGE IN BUSINESS MANAGEMENT The ICT is efficient and promises to do more, but what is its relevance to Knowledge Management. Knowledge is the necessity of today’s business management, and the network platform makes it technically feasible and economically viable. The 21st century recognises Knowledge Management (KM) as a top management function. To understand the relevance of KM better, let us examine how business does better by leveraging

knowledge and intellectual capital. Successful business operations and performance need following qualities in the management team and processes of the organisation. • Proactive decision and action to preempt the adverse impact, or to exploit the advantage out of expected development • Automated decision making systems and processes • Ability to prejudge customer requirements • Ability to anticipate competition moves • Ability to paint different probable emerging business scenarios due to changes in environment (social, political, technical and scientific) • Ability to develop newer and better sustainable competitive advantages • Ability to think the impossible, out of the box, and transform the business for the better. The relevance of Knowledge, Knowledge Management and Knowledge Management Systems becomes obvious and strong for achieving superior business operations and business performance. If you take business growth, customer satisfaction and superior balanced performance as the criteria to rank business organisations, you will soon conclude that knowledge driven organisations having these capabilities have come on top of the list. The glaring examples are ICICI in banking, Maruti Udyog Ltd in auto manufacturing, AMUL brand enterprises in dairy, Pharma and IT service companies, consulting organisations like Accenture, Cognizant, and so on. These companies are leaders in a number of ways in their domain because they essentially leverage on knowledge of something which has an impact on their business performance. Their strategies are built on the knowledge of: • Customer requirements—functional, behavioural and psychological • Technology which might assist in delivery, operations and performance • Process design which will make them happen • Competition moves • Emerging socio-political scenarios and changes in them • Emerging technology changes, and so on These business organisations have positioned themselves as customer caring companies, and they focus on creating value for the customer. They use knowledge to ride high on customer value chain. They create sustainable business advantages from the knowledge mix to remain ahead of competition. They distinguish themselves from others by the knowledge they possess. Knowledge driven strategies are the key differentiators between them and the competition.

PARADIGM SHIFT IN THE WAY BUSINESS IS DONE This century is witnessing and experiencing paradigm shifts in a number of areas. And knowledge is the key mover in making these paradigm shifts a success.

Industrial Society is now Information and Knowledge Society Any business, like agriculture, manufacturing, tourism, hospitality, technology, infrastructure, real estate or, health care can survive and grow if it is driven by information and knowledge. They are the only critical success factors. Let us list a information and knowledge entities in each business.

Agriculture Soil conditions and seeds, rainfall and temperature variations and their impact on crop output. Market needs and price changes, and so on. Imports and exports trade treaties. Manufacturing Whichever may be the product, manufacturing design is highly intelligent, and it selects technology in all processes, capable of making decisions based on the status knowledge. Manufacturing has become smart and self driven based on knowledge input which it gets on continuous basis.

Hospitality and Tourism The core competency in this industry is up-to-date knowledge about the people who are serviced according to their comfort, life style and social segment needs. Understanding customer behaviour and expectations and accordingly making changes in the service model is the key to success. Technology Technology, in character, is not static it changes or becomes obsolete. Businesses like IT and ITes run on technology platform. It is the key differentiator. Products and processes are technology specific and any change in it calls for changes in the product or service. Obtaining knowledge by keeping tab on technology trends and its life cycle is the survival need of the businesses in this sector. Infrastructure and Real Estate Knowledge about demographic changes, migration trends, upcoming cities and areas. knowledge of needs about housing, roads, public amenities, and so on, is an absolute must. Health Care Knowledge about demographic changes requiring different kind of health care services, hospitals, medicines, insurance protection, etc, is an absolute must. National Economy is Now a Component of the World Economy The 2008-2009 economic meltdown in the USA confirmed a number of things. One of them is that there is nothing like ‘National Economy’ free from the impact from other economies. US economic meltdown has impacted our national economy. The GDP growth rate has come down, stock market has crashed, employment market has shrunk, liquidity in the market is reduced, and there are no takers of bank loans inspite of low interest rates.

Organisation Hierarchy (command and control) is Now Replaced by Networked Arrangement (team and groups, cooperation and collaboration) (as shown in Figure 1.4) Command and Control: Top down (Execution by command as directed)

Fig. 1.4

Network-Team Structure: Collaborative (Execution by team, knowledge sharing)

Organisation Structures: Command and Control, and Collaborative

Business Processes are Now Knowledge Driven, Automated and Intelligent The business processes are now ICT enabled, fully automated and secured. The process design is such that in addition to processing the request it examines and evaluates it using the knowledge base. The process design processes the situation with validated rules and DSSs and uses artificial intelligence to decide and act. The organisations run their business operations using many software like ERP, SCM and CRM. The output of these software provide Business data on operations and performance. The data warehousing and mining systems provide knowledge about the business and how it is being managed. This knowledge is used in systems and processes for execution of various plans and operations.

Conventional Business Models are Replaced by Four E-Business Models: B2B, B2C, C2B and C2C Business organisations have transformed traditional business models into E-business models using ICT and Web technologies. The E-business models have transformed traditional models into lean, flat and flexible organisations. They run on their own knowledge bases and databases for transaction processing and decision making. Information and knowledge are the key resources to manage various business functions. All models are leveraged on ICT and Knowledge. ICICI Bank, E-bay and Business portals are same examples of E-business models.

New Business Domain, ‘Service’, has been Added In the new world of ICT enabled businesses, most functions and processes are automated. Human intervention is virtually eliminated. The customer requirement of guidance, support and answering of queries is serviced through e-interaction. The on-sight involvement is now indirect and virtual. ICT enabled business world has opened a new business opportunity—Service.

KNOWLEDGE ECONOMY AND MOORE’S, GILDER’S, METCALFE’S LAWS It would be interesting to review the progress of Economy from Agricultural to Knowledge Economy in the 21st century. The model has been shown in Figure 1.5. The 21st century business world is thriving on knowledge and knowledge economy. It is important to understand certain characteristics of this economy which are its strength. In this economy, people and organisations work on the network platform. People as individuals and as group are connected through the intranet/internet. They exchange ideas, share information and knowledge, and operate and perform a number of activities using the technology and knowledge at their disposal. The people, organisations and databases have independent identities and existence but they deal with any situation as a team or a group, a structure created to resolve the problem. This collaboration for achieving the common goal is now a possibility. Knowledge driven organisations are interdependent and do not have a fixed identified structure. They are formed and dismantled as and when required. Communication and information flow is point to point, points identified specifically to perform a particular task or activity. It is a network of individuals, teams or organisations. They work on two networks—computer network and human network. They perform through various connecting and coordinating tools and technologies, such as Group ware, Chat and Video Conferencing. In the knowledge economy, people and organisations have advantage of access to global knowledge and resources. Virtualisation, a new term that has emerged in the networked knowledge economy, beats the constraints of time, distance and location. Due to ICT implementation, an organisation of people needed to perform

Comman and Control Organisation Structure

No Formal Organisation structure

Land and Labour Driven

Manufacturing Technology Driven

Agricultural Economy

Industrial Economy

Knowledge Economy

People and ICT Driven Network Collaborative Organisation Structure

Fig. 1.5

Transition from Agricultural to Knowledge Economy

a particular task can be created at anytime. These organisations are temporary and are dissolved after the task is completed successfully. The business organisations in this economy work with business partners or alliance partners. Each collaborates to share a critical resource, and to participate in the operations to achieve a common goal. The organisation of people and resources through ICT network is incidental and not real, it exists in the virtual world. The product companies in IT business perform in the virtual world. They come together with their partners for product development, prototyping, testing, and so on. The virtual organisation may be formed for a specific goal, or to achieve a specific milestone in the project. They come together by signing a need based contract. When the contract obligation is over, the temporary organisation is dissolved. ‘Virtualisation’ as a character of business and knowledge economy can be seen in a number of places. • Business transactions done normally through paper documents are now done electronically. • People work from home, hotels and airport using Unified Communication Technology (UCT). They do not formally come together at one place at a fixed time. • Organisations in the service business have no physical office, with name & address. They perform in the virtual world. They provide guidance and help, and conduct demonstrations using ICT technology. For example, institutions providing training through Learning Management System (LMS) operate largely in the virtual world. • During a crisis, teams are formed at short notice to focus on task completion. Each team member contributes uniquely for achievement of the goal, i.e, resolution of the crisis. Virtual teams are formed in disaster management, lengthy and critical complex surgery, and so on. • People who have common interest and goal come together to share information, knowledge and experience for common good. Virtual communities are also called interest groups, community of practice and news groups.

The common thread in all virtualisation are: • Operation or activity any time, any where, without any barrier. • Organisation of people or knowledge resources is fragile, flexible and unstructured. Gets dissolved when the task is over. • Interface and connectivity is through the internet. • Processes and methods are evolved specific to the requirement. • It overcomes the barriers of technology, platform and language. • Organisation structure is modeled as a team, a network of knowledge workers. Organisations which use ICT extensively in all business operations are termed as Digital Firms. In a digital firm, relationships with customers, suppliers, and employees are through digitally designed systems and processes. ICT is a fundamental driving force behind virtualisation and knowledge economy. The rate of change and ICT has greatly increased over the past thirty years. Three laws Moore’s, Gilder’s, and Metcalfe’s, have a combined effect on the economics of knowledge and information management. Moore’s Law holds that the maximum processing power of a microchip at a given price doubles roughly every 18 months. In other words, computers become faster, but the price of a given level of computing power halves. Gilder’s Law holds that the total bandwidth of communication systems will triple every 12 months. It describes a similar decline in the unit cost of the net. Metcalfe’s Law holds that the value of a network is proportional to the square of the number of nodes. So, as network grows, its value grows exponentially, while the cost per user remains the same, or even decreases.

DISTINCTIVE CHARACTER OF KNOWLEDGE ECONOMY Traditional economy functions are driven by Resources. Resources are generally limited, are not easily available, there source is not known. Agricultural economy is driven by rain and its seasonal variations, crop patterns adopted by farmers, market conditions and demands of farm labour. It is more resource driven, but knowledge of farming, cultivation and marketing are necessary. Before globalisation, this knowledge requirement was limited to local conditions. After globalisation, knowledge about agriculture, cultivation, farm management, marketing, and so on, has become critical. Agriculture has become an industry requiring the implementation of scientific management principles and practices. It runs better if technology is also adopted in planning, operations and delivery of goods to customers and markets at large. The agricultural economy is now becoming knowledge driven. Knowledge about all facets of economy is a resource and is a critical success factor. Other factors, such as land, water, fertilizers, etc, are important but not critical for performance. Their knowledge is a necessity & knowledge about markets, prices, seeds, consumer requirements is a competitive advantage. The ITC experiment in West Bengal is an example of how knowledge and ICT can change the character of agricultural economy, from traditional to knowledge driven. The farmers and cultivators here are knowledge workers, and part of main business stream. Before globalisation, manufacturing capacity, technology and capability were the drivers of the industrial economy. Those who possessed these drivers were the leaders in their respective domains. Manufacturing capacity acted as a barrier to new entry. Managers of the economy looked for knowledge about new trends in manufacturing and technology. It was a critical success factor. Those who were up-to-date in knowledge

and used it to buy new technology, plants and equipments remained ahead of the competition. The economy largely worked on the ‘Push Model’. Raw material and supplies were important but not critical for business operations and performance. The optimum use of resources to maximise profits and shareholders, equity was the business mantra. The organisations in this economy were monolithic and large, and had a hierarchy of command and control. The trend was to do everything under one roof. The manufacturing cycle was ‘Procure – Manufacture – Deliver’. The customer was always ready to pay for what was being offered. With advancement of globalisation, this economy was challenged from different angles. The markets became large, competition became more severe and the information and knowledge flow became seamless and uninterrupted. The business initiative got transferred to the customer—the consumer. With easy access to information and knowledge, the customer body became more demanding. Their requirements crossed the boundaries of functions and features and included such requirements as operational and behavioural preferences, more personalisation of their needs and post sales support and service. They demanded a short delivery cycle from order to delivery. Price and quality factors became non-negotiable and moved from competitive advantage to competitive necessity. The economy became more risky and unpredictable. When the world became Uni-polar and Internet web technologies became a successful reality, the economy drivers changed from physical material resource to knowledge resource. Thus, the economy today is recognised as knowledge economy. Michel Porters six driving Forces of Competition affecting Enterprise became more relevant and impact making in the knowledge economy. These are: • Threat from substitutes • Threat from new design • Threat from new entrants • Business rivalry • Bargaining power of suppliers • Bargaining power of customers The strategies required to handle these threats are knowledge based. Knowledge about the environment, trends in business and competition moves is a critical input for building strategies. Knowledge has perhaps become the most important factor for determining the standard of living and managing the business. Today’s most technologically advanced economies are truly knowledge based. New Growth Theory is based on the work by the Stanford economist, Paul Romer, and others, who have attempted to deal with the causes of long-term growth, something that traditional economic models have had difficulty with. Following from the work of economists, such as Joseph Schumpeter, Robert Solow and others, Romer has proposed a change in the neo-classical model by considering technology (and the knowledge on which it is based) as an intrinsic part of the economic system. Knowledge has become the third factor of production in leading economies (Romer, 1986; 1990). Enhancing human capital is critical for GDP growth. The implication of knowledge economy is that there is no alternative way to prosperity than to make knowledge Management of prime importance. There are two kinds of knowledge, Tacit and Explicit. Tacit knowledge is knowledge gained from experience, lessons learned during execution of projects and insight gained with continuous problem resolution. In knowledge economy, tacit knowledge is as important as formal, codified, structured and explicit knowledge.

A knowledge driven economy is the one in which generation and exploitation of knowledge play a predominant part in the creation of wealth or value. In the industrial era, wealth was created by using machines to replace human labour. Many people associate knowledge economy with high technology industries, such as telecommunications and financial services. In knowledge economy, the importance of intellectual capital is highest. Intellectual capital is a firm’s source of competitive advantage. Figure. 1.6 shows the three elements which together build intellectual capital.

Human Capital Experience, Know how, Skills of Individuals

Structural Capital Systems and Processes, Networks, Software Knowledge Bases Knowledge Assets

Customer Capital Loyal and Profitable Customers, High Customer Satisfaction Index, Insight into Customer Requirements

Fig. 1.6

Elements of Intellectual Capital (IC)

In knowledge economy, organisations must learn how to recognise changes in intellectual capital and their reflection on business operations and performance. Knowledge economy driven by ICT helps people to release their creative potential and knowledge. Employees with their experience in working, develop knowledge, brainpower, know-how and improve processes. Simultaneously, they develop ability to continuously improve these processes. Thus intellectual capital and the ability to use it in strategy development is the organisation’s competitive advantage. Competency Models seek to define and classify behaviours of successful employees and calculate their market worth for the knowledge they possess, while Business Worth Approach seeks to consider the value of information and the costs of missed or under-utilised business opportunities. The value of this knowledge is so high that it outweighs the value of physical assets. The difference in the two is the intellectual capital. How do we measure an organisation’s intellectual capital? One tool being widely used is the Kaplan and Norton’s Balanced Scorecard, which combines financial measures with non-financial measures such as internal business processes, learning and growth and various customer related measures (Kaplan and Norton, 1996). In the ICT driven knowledge economy, consumers can now find the prices and price variations offered by all vendors for any product. Suppliers can know about new markets, new products and about competition. The processes are transparent and one can track the status of any aspect of the business. The organisations conduct their business by outsourcing the work to other vendors, and through alliance partners. All those individuals who have the required knowledge form teams or groups to perform the specific task. The organisation structures are building on network model, where nodes are individuals; business partners, each possessing unique competence, knowledge, process and capability.

In knowledge economy, the competition is continuously on the rise and makes a larger impact. Products and processes can be swiftly copied and thus the competitive advantage gets wiped out. Therefore, competition and innovation go hand-in-hand to keep sustainable competitive advantage in place. Organisations rely on knowledge to create strategic advantage through creating the capacity to excel in carefully selected areas and/or by creating innovation capabilities. The selected areas are key result areas, namely product or service quality, customer service, reduced time cycle and faster response impacting on cost and performance. Knowledge economy differs from traditional economy in several key aspects. Knowledge economy is not characterised by scarcity, but rather by abundance of resources. Unlike most resources that deplete when used, knowledge actually grows through application. It gets validated and revalidated by user experience. The impact of location, very important in agriculture and industry, is diminished in knowledge economy, and the virtue of ‘near to market or near to raw material’ is no longer so important. Virtual marketplaces and virtual organisations are very common. Such virtualisation is not possible in traditional economy. Knowledge enhanced products or services can command price premiums over comparable products with low embedded knowledge or knowledge intensity. Knowledge assets remain difficult to account for in balance sheets.

KNOWLEDGE ECONOMY DEMANDS NEW STRATEGIC APPROACH TO BUSINESS In knowledge economy, the organisations need to think on strategy in an all together different way. First, the business model has changed to the customer centric Pull Model. The threat perception to business is more competition oriented. Free flow of ICT knowledge and its adoption by competing organisations makes competition’s edge cutting, such that it is likely to hurt the organisation’s business. Resource based growth and market strategies are no longer adequately effective in challenging competition. The customer centric business model needs strategies which focus on customers and their requirements. The customer in knowledge economy is well informed about the availability of products and their sources. They are blessed with wide choices in terms of price, range, model, capability and specifications. They are in a position to articulate their needs correctly and dictate their terms and conditions. For example, laptop and desktop computers, hotel, tourism, banking, insurance, automobile, Colour and cosmetics, White goods, and consumer durables are some businesses which are highly customer centric and knowledge driven. The management of these businesses needs strategic approach heavily weighed by customer expectations. Due to customer awareness, organisations face a number of challenges which never lose their threatening impact. Some of them are: • Pressure to reduce price and cost and raise productivity • Sudden emergence of competition from unexpected quarter • Dynamic nature of customer needs due to dynamic environment • Competitive advantages becoming suddenly necessities • Pressure to create differentiation in value terms • Business partners becoming more demanding Organisations need a radical change and shift in their strategic thinking to face these challenges. Central to the strategy is customer value proposition. The model for knowledge driven strategic thinking for customer driven businesses is shown in Figure 1.7.

Dynamic Global Environment

Dynamic Customer Environment

Demands New Value Proposition, Innovative Differentiators

Knowledge: Customer, Process, ICT, Environment Innovative Strategy, Whose Dimensions Are: Price Delivery Service Value

Helps to develop Strategy

Flat, Lean Learning Organisation Structure

Help to Evolve Strategy Business Partners

Fig. 1.7

Model for Knowledge Driven Strategic Thinking

To implement the strategy, organisations must be lean in size, flat in structure and driven by ICT. The people, knowledge workers in such organisations are always configured in self managed teams, virtual teams. These teams work in the flexible networked environment of business and alliance partners. The enabling technologies supporting this are Internet/Intranet/ Extranet, Voice mail, Videoconferencing, E-mail, Groupware, Mobile computing and communications, and Knowledge portals. The challenges call for evolving innovative strategies to build value differentiators which turn out to be of competitive advantage. The competitive advantage supports efforts for gaining new customers and retaining old ones with more profitable business. In some cases and scenarios, organisations come up with new markets, which have never been tried before. The innovative strategy design and its implementation is successful if it is supported by the Organisation’s knowledge and its knowledge networking. Charles Savage, author of fifth generation management, coined the term ‘Knowledge Networking’. It has been developed on two concepts: • Strategic resource of knowledge • Human networking initiative Knowledge networking is defined as the process of combining knowledge nodes and sharing each other’s knowledge, experiences, talents, skills, capabilities and aspirations in a pattern to generate strategic competitive advantage. The characteristics of such knowledge networking are: • Basis for developing relationship • Path for information flow and communication • Node could be an individual, a formal group or a team • Node is a starting or ending point of any flow • The links change with the change in configuration

• The network does not have a fixed number of nodes • Interaction and communication could be one-to-one or many-to-many • Node is a centre of knowledge • The network is flexible, gets changed with addition or separation of node Knowledge networking helps to develop and share knowledge among the nodes. It fosters openness and collaboration between them. The successful network functioning builds relationship between members of the team and among the teams. The different knowledge centres collaboratively generate new knowledge providing better insight into the problem.

KNOWLEDGE DRIVEN NETWORK ORGANISATION The functional characteristics of knowledge driven organisation are different from the traditional hierarchy based functional organisation. Enterprise software like ERP, SCM and CRM have made the management process integrated through seamless flow of information across departments. These software are now web enabled where by business partners become a part of the organisation structure. However, the working and functioning of the organisations are still hierarchical, based on the authority structure. The flow of information is top-down or bottom-up. The information design is largely function oriented, and sharing across the functions is very limited. In the knowledge economy, this traditional hierarchical model is now a network model. The hierarchy is maintained for position recognition and for administrative relationship. The working is through teams, groups formed formally or otherwise. The access to information is free and unlimited to the members of the team. Authority, leadership and decision making are driven by knowledge. The characteristics of a network driven organisation, by virtue of its working, are: • Multi-directional knowledge flow and sharing • Flexible and adaptable teams dedicated to repetitive tasks • Team members continue to be located at one recognised location • They work in virtual mode on knowledge network • Organization uses ICT extensively. • Teams have flat and largely non-hierarchical structure In knowledge economy, people in the business organisation are arranged in hierarchical structure for administration, compensation and for recognition of position, not only for superiority but also for their contribution to the business. But an organisation, in reality, works in network where people form teams, groups, and work collaboratively to achieve the goals. In reality, every business organisation has two people structures, hierarchical and network, for administration and business management, respectively. The people manning such organisations work on technology platform and ICT enabled business processes. They are termed as knowledge workers. A knowledge worker is a person whose work needs knowledge to be a successful. He uses knowledge to be creative and innovative and, in the process, knowledge is created, stored and shared. Working extensively in this manner, the team of knowledge workers develops intellectual capital, thus raising the market value of the business organisation. The shift from traditional organisation to knowledge driven organisation is due to complex nature of the business today, requiring a radically different approach to operate and perform effectively. Now, in the new scenario, information about resources, milestones achieved or not achieved and use of information driven DSSs is not sufficient. The decision making is largely, unlike in traditional organisation, knowledge driven.

This means that besides data and information specific contextual knowledge is needed to assess and decide the next course of action. Table 1.1 below illustrates decision v/s knowledge requirements. Table 1.1 Decision Type and Relevant Knowledge Areas Decision Type

Knowledge Areas

Strategic Decisions

Emerging business opportunities, Technology competition moves, Probable threats, Risk management

Short-term Business Decisions

Make or buy, Outsource, Product Improvements, Material choices, Costs/ Benefits Allocation of resources, Financing, etc.

Operations Decisions

Rules and policy on order acceptance, Pricing, Delivery preferences, Credit worthiness, Prioritisation, Trade offs, Customer and vendor requirement preferences, etc.

A knowledge driven network organisation has multiple people and knowledge networks integrated to perform. These networks are the platforms to share knowledge and seek advice and solutions. They are not stable or static. Some are fairly stable when formal teams or groups are formed in specific areas, such as maintenance, post sales support, design, etc. But some networks are formed as and when the problem arises. Such teams come into existence for the specific purpose of problem resolution. These networks pull together disparate first knowledge to make a new knowledge set to give new insight and to solve the problem. In the knowledge driven network organisation HR use is not only efficient but is also effective, producing the desired business outcome. It makes HR smarter and useful, an asset to the organisation. Knowledge management in the organisation is managed through Information and communication technology (ICT). ICT supports main KM processes, finding/ identifying, creation, storage, sharing, searching and integration. Table 1.2 shows the KM processes and the enabling ICT tools. Table 1.2 KM Processes and ICT Tools KM Processes

ICT Tools

Identifying knowledge Creation of knowledge Searching knowledge Utilising knowledge

Finding events and experiences from e-records, databases, files and folders Organising, editing, processing and using diagramming, modeling presentation tools Search engines, Domain Web Portals DSSs, Developing business rules and embedding into information and knowledge based systems

Sharing knowledge Integrating knowledge

E-mail, intranets, extranets, knowledge databases, knowledge portals Groupware technology, integration in enterprise software

FINDINGS OF THE ASSOCIATION OF KNOWLEDGE WORK The report of the Association of Knowledge work (AOK) sums-up knowledge management. It states that managing knowledge is not simply the latest management ‘fad’. It is a shift in the value of knowledge due to fundamental changes in technological, political, social, economic, business and work environments, brought about by the passing of the industrial age and the arrival of the knowledge economy. In the industrial age, people were not paid for what they knew, but for what they did and their employer told them how to do it. The

management strategy was to turn raw materials into finished products ever more efficiently and effectively. People were liabilities, expensive tools that represented the largest cost of doing business. Peter Drucker coined the term ‘knowledge worker’ nearly 50 years ago. By the 1980s and the 1990s, the world began to realise that open and global electronic communication was resulting in a sea-change in the social, political and economic order. In 1995, Ikujiro Nonaka and Hirotaka Takeuchi published The Knowledge Creating Company and, for the first time, Michael Polanyi’s distinction between the tacit (or intangible) and the explicit (or documentable) was introduced into common business language.

Today there is no such thing as a non-knowledge worker and, together, knowledge workers are the new shop floor of every organisation. Knowledge workers are everywhere. They are not only inside the organisation, but also outside: suppliers, allies, partners, customers, and even competitors. People at work have covertly used short cuts, informal communications, bootleg files and a whole host of guerrilla tactics to help them work better regardless of official protocol. The new order of the knowledge age will encourage them to get out of this stealth mode and into covert initiatives. Savvy managers have begun to think of these knowledge resources not just in terms of ‘intellectual capital’, but also in terms of ‘social capital’. In short, people are no longer ‘personnel’. They are the company. That is an unsettling message for managers stuck in the industrial age. And those managers continue to inhibit the full transition to knowledge based enterprise, relying on narrowly defined job descriptions, vertical organisational charts that resemble human assembly lines, clearly documented procedures and guidelines—all leaving little space, if any, for individual creativity or cross-functional collaboration. The new model of power is a cycle of learning quickly, sharing what has been learnt while it is still valid, unlearning what no longer works and then re-learning. The current set of behaviours is based on power as a function of understanding, facilitating information and knowledge flow. Meanwhile, many business leaders feel threatened by the untidy and cross-cutting nature of bottom-up initiatives that could undermine their control. Those who are hostile to the notion of distributed empowerment may never see the true value of the new perspective. Some are in denial, rejecting the ‘knowledge phenomenon’ as just another fad. Others delay and avoid acceptance by operating with a traditional lens that resists change. They seek justification, analysis of competition, best practice examples, business case examples based on traditional return on investment criteria, and so on, to avoid action rather than having to plunge headlong into the uncharted, fluid imperatives of the new order. Two domains compete for primacy in the modern workplace. One, the domain of power and hierarchy secured by decision making and control; the second, the domain of knowledge and expertise, the foundation of creativity and innovation. The first domain is ruled by ‘Whoever’s calling the shots by command and authority’. The second is ruled by the knowledge ‘Who’s got the smarts’. The person calling the shots can take measures to enable or disable the person with the smarts. Disablement was too often the tactic of choice in the industrial age. In the 20th century, the emphasis was on trying to arrange and re-arrange things so the person who called the shots could get better control of the one with the smarts. This game has been one of diminishing returns. All economic sectors are going through major and rapid transformations. Economic success in this fast-paced environment requires considerable agility and adaptability which are hampered by the snail’s pace of a directive and decision making system based on a chain of command.

Communities of practice (CoPs) are moving to centre stage as the place where raw knowledge combines and combusts to gain and maintain competitive advantage. CoPs are environments of empowerment, high trust, knowledge sharing, collaboration, creative thought, initiative and accomplishment. They are not the same, however, as teams appointed by management to carry out specific tasks. At the same time, some see CoPs as a formal part of the hierarchy, receiving requests from management to produce agreed-upon outcomes. A true knowledge-intensive organisation is comprised of self-motivating, empowered workers who know their knowledge is important to the performance of their organisation. Such a change in culture has developed significantly in recent years. It has changed the way staff work, share, learn, and respond to clients’ needs. It has increased productivity and created communities within organisations; it has fostered a culture where staff is eager to share knowledge and wisdom. (Source: Jerry Ash is founder of AOK and special correspondent to IK.

The Evidence of Entry into Knowledge Economy There is sufficient evidence that we are now in knowledge economy even though a large percentage indicates dependence on the agriculture and the industrial economies. In India, all three will prevail for some time to come. In all the three sectors, information and knowledge are recognised as key critical resources. Agriculture’s success depends on getting the knowledge of how monsoon would behave, which crop would be ideal for growing and would be a commercial success. The emphasis is on knowledge transfer and sharing with farmers the knowledge is required about inputs in farming to ensure that crops cultivated so as to give high yield per acre. In the industrial manufacturing domain, the pressure is to develop competitive advantages using innovative ideas. The knowledge of people, processes and technology are the drivers to generate knowledge which can be used to improve the business. The organisations today are constantly researching into knowledge, more particularly customer knowledge, process knowledge, technology knowledge and people knowledge. The reason is business strategy now is knowledge driven & supported in implementation. The customers now ask for smart products and intelligent service options. The environment also requires certain processes that do not pollute or disturb the ecosystem. The automobile, pharmaceuticals, services, tourism, hospitality, banking and insurance industries have become competitive, and growth is possible if knowledge is used for developing innovative ideas to compete. Most of the organisations are gearing themselves to become learning organisations.

INDIA AND THE KNOWLEDGE ECONOMY: LEVERAGING ON STRENGTHS AND OPPORTUNITIES (AN EXTRACT FROM THE WORLD BANK REPORT) One of the world’s largest economies, India, has made tremendous strides in economic and social development in the past two decades and is poised to realise even faster growth in the years to come.

Embarking on a New Growth Path India has a rich choice set in determining its future growth path. Which growth path India embarks on in the future will depend on how well the government, private sector and civil society can work together to create a common understanding of where the economy should be headed and what it needs to get there. India can no doubt reap tremendous economic gains by developing policies and strategies that focus on making more effective use of knowledge to increase the overall productivity of

the economy and the welfare of its population. In so doing, India will be able to improve its international competitiveness and join the ranks of countries that are making a successful transition to the knowledge economy.

Embracing the Knowledge Economy The time is very opportune for India to make its transition to the knowledge economy—an economy that creates, disseminates and uses knowledge to enhance its growth and development. The knowledge economy is often taken to mean only high-technology industries or information and communication technologies (ICTs). It would be more appropriate, however, to use the concept more broadly to cover how any economy harnesses and uses new and existing knowledge to improve the productivity of agriculture, industry and services and increase overall welfare. In India, great potential exists for increasing productivity by shifting labour from low productivity and subsistence activities in agriculture, informal industry and informal service activities to more productive modern sectors, as well as to new knowledge based activities—and, in so doing, to reduce poverty and touch every member of the society. India should continue to leverage its strengths to become a leader in knowledge creation and use. To get the greatest benefits from the knowledge revolution, the country needs to press on with the economic reform agenda that it put into motion more than a decade ago and continue to implement the various policy and institutional changes needed to accelerate growth.

Advantage India India has many of the key ingredients for making this transition. It has a critical mass of skilled, Englishspeaking knowledge workers, especially in the sciences. It has a well-functioning democracy. Its domestic market is one of the world’s largest. It has a large and impressive Diaspora, creating valuable knowledge linkages and networks. The list goes on: macroeconomic stability, a dynamic private sector, institutions of a free market economy, a well-developed financial sector, and a broad and diversified science and technology (S&T) infrastructure. In addition, the development of the ICT sector in recent years has been remarkable. India has created profitable niches in information technology (IT) and is becoming a global provider of software services. Building on these strengths, India can harness the benefits of the knowledge revolution to improve its economic performance and boost the welfare of its people. This report provides a ‘big picture’ assessment of India’s readiness to embrace the knowledge economy and highlights some of the key constraints and emerging possibilities confronting India on four critical pillars of the knowledge economy: • Strengthening the economic and institutional regime • Developing educated and skilled workers • Creating an efficient innovation system • Building a dynamic information infrastructure It stresses that to be competitive in the global knowledge economy of the twenty-first century, India should continue to focus its efforts on further reforming its overall economic and institutional environment and improve its overall trade and investment climate. Addressing issues in this domain will be the key requirement, because it sets the overall incentive framework needed to improve performance across the economy. The report further underlines that for India to leverage its strengths and opportunities on a global scale, it needs to undertake significant reforms and investments in building education and skills, strengthening its innovation system, and further bolstering its information infrastructure. To create and sustain an effective

knowledge economy, India must undertake systemic integration of reforms in the above four domains to strengthen its competitive advantage. The following are some of the key issues that India needs to address in each of the four pillars to spur growth and innovation and, in so doing, increase economic and social welfare.

Building a Dynamic Information Infrastructure Rapid advances in ICTs are dramatically affecting economic and social activities, as well as the acquisition, creation, dissemination and use of knowledge. The use of ICTs is reducing transaction costs and lowering the barriers of time and space, allowing the mass production of customized goods and services. With ICT use becoming all-pervasive and its impacts transformational, it has become an essential backbone of the knowledge economy. The information infrastructure in a country consists of telecommunications networks, strategic information systems, policy and legal frameworks affecting their deployment and skilled human resources needed to develop and use it. India’s telecommunications sector has registered rapid growth in recent years, spurred by reforms to open markets, and introduced more competition. Many domestic and international private sector entrants are now providing consumers with high-quality services at low prices. As a result, some spectacular successes have resulted: more than 47 million people had mobile phones at the end of 2004! Fierce price competition has resulted in Indian mobile telephony becoming one of the cheapest in the world. This has been a boon, especially to people in India’s 600,000 rural villages, which have had no access to communication through traditional means, such as fixed lines. But now, from fishermen at sea and brokers ashore in Kerala to farmers in Punjab—people in industry and farming are embracing wireless technology for economic activity, and to do business and increase their profit margins. While India’s progress has been very impressive, the rest of the world is also advancing rapidly. Thus, even greater efforts should be made to make the information technologies available to more people throughout India by • Creating an efficient innovation system • Building a dynamic information infrastructure. Figure 1.8 benchmarks India’s relative global position in the global knowledge economy based on a methodology using three indicators for each of the above four pillars. It shows that India is at the top of the bottom third of the global distribution, and that its relative position has improved a little in the last decade. However, this book highlights India’s tremendous potential to make dramatic improvements in its overall knowledge readiness. India can also boast of remarkable and impressive global achievements in the IT sector. According to the National Association of Software and Services Companies (NASSCOM), the Indian IT market has grown from $1.73 billion in 1994–95 to $19.9 billion in 2003–04, accounting for about 3.82 per cent of India’s GDP in 2003–04 and providing employment for almost a million people. India’s IT services are moving up the value chain, and India is now undertaking new and innovative work, such as management for clients of IT-related business processes. It is making an impact also in IT consulting, in which companies such as Wipro, Infosys, and Tata are managing IT networks in the United States and re-engineering business processes. In fact, Infosys was ranked the ninth most respectable IT company in the world in 2004, behind Hewlett Packard, IBM, Dell, Microsoft, AP, Cisco, Intel and Oracle. In chip design, Intel and Texas Instruments are using India as an R&D hub for microprocessors and multimedia chips. The success of the IT industry on the whole influenced competitiveness in other sectors as well by building confidence in Indian industry, enhancing the country’s brand equity in the world and offering entrepreneurial opportunities on a global scale. In the future, it is expected that India will make inroads in areas such as financial analysis, industrial engineering, analytics and drug research.

Telephones per 1,000 people (71.00) Main Telephone (2.78) ICT lines per 1,000 Expenditure as % of GDP (46.30) Mobile phone per 1,000 (24.70)

(5.18) E-Government

(3.20) International telecommunications, cost of call

Computers per 1,000 people (7.20)

(174.86) Internet users per 10,000 people (0.82) Internet hosts per 10,000

Fig. 1.8

TV Sets per 1,000 (83.00)

(60.00) Daily newspapers per 1,000

Radios per 1,000 (120.00)

India’s Scorecard on Information and Communications Technologies, Selected Variables, Most Recent Period.

Several factors have contributed to India’s success in the IT industry including the existence of a highly skilled, English-speaking workforce coming out of India’s engineering schools and earning lower wages than European and U.S. counterparts, low dependence of IT on physical infrastructure, the Indian Diaspora, and the introduction of current account convertibility and easing of controls and regulations in the early 1990s. The Indian government, in keeping pace with up-to-date technological advancements, announced its Broadband Policy in 2004 to provide an impetus to broadband and Internet penetration in the country.

India is well positioned to take advantage of the knowledge revolution to accelerate growth and competitiveness and improve the welfare of its citizens, and should continue to leverage its strengths to become a leader in knowledge creation and use. In the twenty-first century, India will be judged by the extent to which it lays down the appropriate ‘rules of the game’ that will enable it to marshal its human resources, strengths in innovation, and global niches in IT to improve overall economic and social development and transform itself into a knowledge-driven economy. Sustained and integrated implementation of the various policy measures in these domains would help to reposition India as a significant global economic power, so that it can rightfully take its place among the ranks of countries that are harnessing knowledge and technology for their overall economic development and social well-being. (Source World Bank Institute Finance and Private Sector Development Unit South Asia Region, The World Bank, India and the Knowledge Economy Leveraging Strengths and Opportunities By Carl Dahlman, Anuja Utz WBI Development Studies, The World Bank Washington, D.C.)

In summary, for several decades the world’s best-known forecasters of societal change have predicted the emergence of a new economy in which brainpower, not machine power, is the critical resource. But the future has already turned into the present, and the era of knowledge has arrived*. The new source of wealth *

Source: ‘The Learning Organization,’ Economist Intelligence Unit.

is knowledge, and not labour, land or financial capital. It is the intangible, intellectual assets that must be managed in the economy. This move from an industrially based economy to knowledge or information based one in the 21st century demands a top-notch knowledge management system to secure a competitive edge and a capacity for learning. The knowledge based economy to foster innovation relies increasingly on technology and knowledge as factors of production and wealth creation—in addition to labour and capital. The technology and knowledge in KE are transforming wealth creation work from physically based functions to knowledge based functions. The knowledge economy rests on three pillars: • The role that knowledge plays in transactions that is, what is being bought and sold; both the raw materials and the finished goods • The concurrent rise in importance of knowledge assets, which transform and add value to knowledge products • The emergence of ways to manage these materials and assets, or KM

End Notes • This century is witnessing and experiencing paradigm shifts in number of areas. And knowledge is the key mover in making these paradigm shifts a success. • The history of business transformation records that the core competency and business drivers have changed almost every decade since the seventies. First, it was the ability to procure raw material, then possession of manufacturing technology followed by capital and capacity strength, and now knowledgeable learned human resource. • ICT revolution has transformed the business environment radically. Independent business organisations are now interdependent organisations. They collaborate to achieve their respective goals. They share information and have access to each other’s information base. The business process scope now extents beyond the organisation’s boundaries. The customer initiates the process and the organisation responds. • The knowledge has three structural components, people, processes and technology. Together they are termed as body ‘Knowledge’. The people are the generators, users and custodians of knowledge. Technology is the facilitator and an active participant in the knowledge management process. • Organisations use knowledge to ride high on the customer value chain. They create sustainable competitive business advantages from the knowledge mix to remain ahead of the competition. Knowledge driven strategies are the key differentiators between them and the competition. • The relevance of knowledge, knowledge management and knowledge management systems becomes very obvious and strong for achieving superior business operations and business performance. • If you take business growth, customer satisfaction and superior balanced performance as the criteria to rank business organisations, you will soon conclude that knowledge driven organisations have come on top of the list. • Knowledge driven organisations are interdependent and do not have a fixed structure. They are networks of individuals, teams or organisations. An organisation works on two networks, computer network and human network. They perform through various connecting and coordinating ICT tools and technologies, such as Groupware, Chat and Video Conferencing.

• The implication of knowledge economy is that there is no alternative way to prosperity than to make knowledge management of prime importance in the organisation. There are two kinds of knowledge, tacit and explicit. Tacit knowledge is knowledge gained from experience, lessons learned during execution of projects and insight gained with continuous problem resolution. In the knowledge economy, tacit knowledge is more important than formal, codified, structured and explicit knowledge. • In knowledge driven economy, generation and exploitation of knowledge plays a predominant part in the creation of wealth or value. In this economy, the importance of intellectual capital is highest as it is an important factor in valuation of the organisation and its business. • In knowledge economy, the business model has changed to the customer centric Pull Model. The threat perception to business is more competition oriented. Resource based growth and market strategies are no longer adequately effective to challenge competition. The customer centric business model needs knowledge driven strategies to focus on customers requirements. • Knowledge networking is defined as the process of combining knowledge nodes and sharing each others, knowledge, experiences, talents, skills, capabilities and aspirations in a pattern to generate strategic competitive advantage. • Knowledge networking helps to develop and share knowledge among the nodes, the centres of operations. It fosters openness and collaboration between the nodes. Successful network functioning builds relationships between members of the team, and among the teams. The different knowledge centres collaboratively generate new knowledge, providing better insight in to the problem. • Focus is on competitive advantage and not on profits. • Focus is on all round customer experience and not on customer satisfaction. • Focus is on attaining a status of zero customer problems and not on zero product or service defects. • Focus is on maximising revenue and not on control of cost. • Focus is on business opportunity and not on its financial cost. • Focus is on competition as an opportunity and not as a threat to the business. • Focus of design is on performance and not just on functions and features. • Focus is on recruiting passionate professionals and not on just professionals. • Focus is on managing competitive environment and not on just managing resources. • In the Knowledge economy, the traditional organisation model is now a network model. The working is through teams, groups formed formally or otherwise. Information access is free and unlimited to the members of the team. Authority, leadership and decision making and driven by knowledge. • In a knowledge driven network organisation, HR use is not only efficient but is effective, producing the desired outcome. It makes HR smarter and useful to the organisation. The team of knowledge workers develop intellectual capital, thus raising the market value of the business organisation.

Questions 1. In the context of India, identify the decades which could be termed predominantly as agricultural, industrial, Service, and knowledge economy. 2. Explain why 21st century is termed as knowledge economy.

3. Following are the characteristics of knowledge economy. Explain. • Knowledge, a key driver and enabler • Uses more intangible knowledge assets • It is networked • It is digital • It is virtual 4. Explain using Figure 1.1 how people processes, and technology are structurally connected or dependent on each other. 5. The characteristics of a network based, knowledge driven organisation, by virtue of its working, are as under: • Multidirectional knowledge flow and sharing • Flexible and adaptable teams dedicated for repetitive tasks • Team members continue to be located at one recognised location • They work in virtual mode on knowledge network • The organisation uses ICT extensively • Teams have flat and largely non-hierarchical structure 6. Evaluate your organisation on the following: • Focus on competitive advantage • Focus on all round customer experience • Focus on attaining status of zero customer problems • Focus on business opportunity • Focus on competition as an opportunity • Focus of design on performance, not just on functions • Focus on recruiting passionate professionals • Focus on managing competitive environment 7. Explain giving reasons, how Information and Communication Technology ( ICT) has brought about the following changes: • Process: Short, fast and intelligent • Organisation Structure: Flat and Lean • Business Model: Distributed globally • Process Character: Integrated Automated processes, but maintains local integrity • Organisation Model: Customer centric service model • Organisation working: Collaborative 8. What are the advantages of the following? • Knowledge network • Knowledge driven ‘Pull Model’ 9. Knowledge economy and due to customer awareness, the organisation faces a number of challenges. Some of them are: • Pressure to reduce price and cost, and to raise productivity • Sudden emergence of competition from unexpected quarter

• Dynamic nature of customer needs due to dynamic environment • Competitive advantages suddenly becoming necessities • Pressure to create differentiation in value terms • Business partners becoming more demanding Explain how knowledge initiative and knowledge driven strategies would help to deal with these challenges. 10. What are the distinct advantages for a firm to go digital? How and why does it affect organisation structure and speed of delivery to customers both internal or external.

What is Knowledge?

2

Chapter

(Data-Information-Knowledge-IntelligenceBusiness Intelligence)

This Chapter Deals with • • • • • • • • •

Data, Information, Knowledge, Business Intelligence Attributes of Knowledge Expression of Knowledge Human Thinking and Learning Types of Knowledge Tacit and Explicit Knowledge Knowledge: A Driver for Creativity and Innovation Knowledge a Strategic Resource Business Benefits of Knowledge

Learning Outcome You will understand the continuum from data to knowledge and the distinctive character of knowledge by its attributes. You will be more clear on knowledge domain by knowing it’s different shades expressed by class, type and nature. You will realise the benefits of knowledge and its strength: a driver for creativity and innovation.

“Knowledge can be seen as the entirety of cognitions and abilities which are used by individuals to solve problems. This comprises theoretical perceptions as well as pragmatic day-to-day rules and guidelines and is an organised set of statements of facts or ideas, presenting a reasoned judgement or an experimental result.” —Klaus-Dieter Thoben, Frithjof Weber, Michael Wunram University of Bremen, Faculty of Production Engineering, Bremen Institute of Industrial Technology and Applied Work Science (BIBA) at the University of Bremen

DATA–INFORMATION–KNOWLEDGE–BUSINESS INTELLIGENCE Which is the easiest way to understand knowledge? Is to know what it is not. We use words data, information and knowledge about the precise meaning without bothering interchangeably. But it does not matter in the day-to-day communication exchange. So we begin with understanding of data, information and knowledge.

Data Data consists of discrete, objective facts about events. It says nothing about its own importance or relevance. Data is essential raw material for the creation of information; it can be quantitative or qualitative. Data could be a number, an image, or words, or sounds whose existence have no context. It does not represent anything, it is a lifeless entity. Its existence could be the result or outcome of some process. It does not evoke any response. It cannot be interpreted. It may have a structure or may be unstructured. Data is defined as raw numbers, images, words, sounds which are derived from observation, or measurement, or processing. The content of the data is events and results, thereby. It is in the form of transactions. Its purpose is to represent a ‘thing’ as precisely as possible. The human process of obtaining data and understanding its purpose is human observation supported by IT enabled systems. The organisation’s goal is to process raw data with automation, with the purpose of clearly coming out with some representation. Over the period, such data together represents a block of great value. For example, 6-9-1938 is a set of numbers. It does not convey anything nor does it evoke any response. Also, if a graph of a ‘line’ is drawn without mentioning the X and Y dimensions, it does not mean anything. The straight line does not indicate whether it is a graph of rising sales, or strength of students in the class, or the daily temperature.

KEY TERMS • Data • Information • Knowledge • Business Intelligence • Knowledge Structure: Data to Knowledge • Knowledge a Strategic Resource • Knowledge Assets • Intellectual Capital • Intellectual Property.

With this background, one may assume that data is not important for the business. However, this is not true. Many organisations, like banks, insurance and the companies hospitality industry are data driven. Many processes need data to progress in their business management. Data comes about through research, gathering from different sources, and through transaction processing. Example: Census data, rainfall statistics.

Information When data is represented with context it has some meaning. Information in data that is organised in a way that makes it useful for an end-user to make decisions. It represents something. It evokes some mental response. The set 6 9 1938 when mentioned as ‘dd mm yy’ becomes a date. If it is further supplemented as the day of birth, it becomes a birth date. When a straight line graph is qualified by the subject ‘sales in Units’ with month and quantity sold on the X and the Y axes, it conveys the information that the graph shows sales growth by the month. It also shows that sales have slumped in the second quarter. It evokes a mental response. Information has specifications of some entity. Hence it represents that entity meaningfully. Information has some intellectual input making it more responsive to the reader, or the viewer. When an organisation conducts market research, it collects data about consumer behaviour. When the business analyst analyses this data using statistical tools, it defines consumer behaviour in terms of choices, options, preferences and associations. The marketing manager’s mind starts building the behaviour model of the consumer. The strength and quality of the information may evoke strong or weak responses in the mind of the reader or the viewer. Information, in most cases, promotes some decision or action. If not, it, at least, invites attention or alerts the reader about the information. Data when processed with some context becomes information. The information represents something meaningfully. It may have surprise value. It evokes a mental response. When data is processed over a time, or region, or any other referential key or some other context, it reveals information. The purpose is to interpret the trend and its pattern. The entire processing of interpretation is judgmental. The organisation and the concerned people look at this process as a support to decision making in the same or in a different area. The information, in contrast to data, reduces uncertainty due to additional value added by interpretation of trend and pattern. Example: Census education data analysis based on gender reveals information on literacy percentage of men and women. When rainfall data is analysed by seasons for the last 20 years, it shows rainfall percentage by seasons, indicating the rainfall pattern.

Knowledge According to a dictionary definition, knowledge is ‘the fact or condition of knowing something with familiarity gained through experience or association; acquaintance with or understanding of a science, art, or technique; the fact or condition of being aware of something’ (Merriam-Webster, 2001). Knowledge is broader than information and data, and requires understanding of information. It is contained in the relationships of information, its classification, and its meta-data. It is an outcome of understanding and insight gained through experience of doing something repeatedly, solving a number of similar problems, and so on. The experience develops into thumb rules, guidelines, procedures, models to deal with new situations. Some authors call knowledge ‘Actionable Information’. Knowledge is built out of experience. The experience is gathered out of learning by doing something. Learning takes place by experience, by example and by discovery. Knowledge emerges out of application of data and information. The knowledge has more intellect into it compared to data

& information. It is a fluid mix of framed experience, values, contextual information and expert insight that provides a framework for evaluating and incorporating new experiences and information. Information, processed analytically in some manner, gives meaning of substantial value. The value could be that information shows some pattern, trend or a cause-effect relationship among variables. It helps, with great certainty, to interpret, forecast or predict events or results in the future. This is knowledge. Information starts becoming knowledge when it contents expert information useful for problem solving. It is more valuable when knowledge emerges in the form as ‘lessons to learn’. These lessons further become more valuable if knowledge is explicit. Knowledge is of a high value when it comes out of experience. Knowledge, in an organisation, is viewed as an input for decisive action. Its use over a period makes it more sharp and focused, as it is enriched by use, time and again. Knowledge (set of information) is built out of experience of doing certain things. It is an intelligent observation of cause and effect. It provides better insight in to the situation by providing different views or perspectives for the problem, and helps to solve the problem effectively. Example: Information on literacy percentage when linked to socio-economic background reveals the reasons behind it. It is knowledge which provides a solution to eliminate illiteracy. When information obtained from market research data analysis confirms certain buying behaviour in terms of choices, preferences, and so on, it becomes knowledge about consumer behaviour. When this information is seen in context of marketing strategy, it suggests the impact of strategy on the consumers and their behaviour. The collection of these value inputs is knowledge about consumer behaviour and the effectiveness of the marketing strategy. Information may evoke action response but knowledge evokes strategic response. Hence, knowledge is the result of intelligent processing of information or information set. Knowledge is a set of information which provides capability to understand, differentiate and view situations in different perspective, and further enables to anticipate its implications, judge its effects, and suggest ways or clues to handle the situations. Thus, we can say that: • Experienced application of information in solving a variety of problems creates ‘knowledge’ and it enriches over a period of time. • The advantage of knowledge is that it provides better insight in to the problem, creates different views or perspectives and helps to solve it effectively. This results in saving of time needed to search for a solution in difficult times. The knowledge is specific to the domain and the nature of the problem. Knowledge can take different representation. It could be a systematically organised fact which conveys a meaning to the reader. A Sensex index chart of share prices is a factual representation of how the stock market has behaved. Knowledge can be modeled into a rule or a procedure. For example, while driving on the highway, if the petrol tank gauge shows that the tank is almost empty is an indication that the petrol should be filled at the first petrol pump one comes across. In the share market, there is a golden rule that if a share price has gone up by 15 %, then sell the shares. The knowledge could be modeled as ‘Heuristic’, i.e., a thumb rule which if followed would produce right results in most cases, but not always. Knowledge is always bound to human beings and is impossible to digitalize. Once it is ‘explicated’, it becomes information. Sveiby, 1997, as cited in Miller, 2002, presents distinguishing factors between information and knowledge. Table 2.1 and Table 2.2 give the differences between information and knowledge.

Table 2.1 Distinguishing Factors between Information and Knowledge Information

Knowledge

Static

Dynamic

Independent of the individual Explicit Digital

Dependent on individuals Tacit, may be explicit over time Analogue

Easy to duplicate Easy to broadcast

Must be re-created Face-to-face mainly when tacit Easy to broadcast when explicit

No intrinsic meaning

Meaning has to be personally assigned

Distinguishing factors between Information and Knowledge Source Sveiby, 1997, as cited in Miller, 2002 Modified

Knowledge has become an essential component of business and its management. It is an input for creativity and innovation, for building competitive business strategies. It helps to create competitive advantages to beat competition. Knowledge, therefore, is recognised as an asset, a capital. It is derived from information in the same manner as information is derived from data. In competitive business, decision making, at all levels, is knowledge driven, and some of it is information driven. Knowledge generation has two sources, information route and experienced application of information set for decision making. For example, investor’ knowledge results from comparative analysis of information in the balance sheets of the two companies and the domain knowledge of the business. But, a plant maintenance manager has knowledge of fixing the problem out of experience gained by solving different problems of the same nature. This knowledge gives him quick diagnosing ability and solution approach. Knowledge has to be built with business focus and purpose, resulting from interaction with resourceful people, by knowing and understanding their experiences in problem solving. Knowledge is not necessarily drawn from within the organisation. It can have a component drawn from outside. Knowledge alone can give competitive advantage. In customer driven service business, customer knowledge, in terms of expectations, and buying behaviour in different segments alone can help build distinguishing competitive advantages. In summary, knowledge is a bundle of information, perceptions, analytical and application skills, training and experience of using all this in solving problems in key areas of business. It is often called actionable information. When we say knowledge is built from experience, it means that the person holding knowledge has ‘learnt’ something from experience. Further, the person is able to integrate meaningfully the facts, results, processes and information used for decision making. The result of this integration is the knowledge. More of such experience adds value and precision to knowledge. Learning occurs by experience, by example and discovery. All people cannot learn fast because their learning ability may be low. Acharya, and Jugbandhu have given select characteristics of knowledge. (What is Knowledge, April, 2001) • Knowledge involves human interaction, expression and communication with reality. • Knowledge has attributes of significance. • Knowledge is a dynamic concept. It changes its character and content with time. It becomes obsolete over a period of time. • Knowledge has an economic value. Therefore, it is used for creating competitive advantage.

• Knowledge is built out of perception, skills, training, common sense and experience gathered in working, interaction, observation and analysis of the data and information. • Knowledge is also termed as actionable information. Michael Earl of the London Business School suggests a different classification based on six different parameters. Table 2.2 exhibits the distinctive characteristics of data, information and knowledge. Earl’s Distinction of Data, Information & Knowledge. Table 2.2 Distinctive Characteristics of Data, Information and Knowledge Parameter

Data

Information

Knowledge

• Content • Form

Events Transactions

Trends Patterns

Expertise Learning

• • • •

Representation Observation Automation Business data

Manipulation and Interpretation Judgement Process Decision making Uncertainty Reduction

Apply and Share Experienced Observation Excellence Better insight Better vision

Purpose Human Organisation’s goal Value

At this stage, it is necessary to understand that data, information and knowledge are not static in content. That is, they undergo changes in qualitative terms as more of each is generated and used in various applications. Knowledge has validity directly proportional to its utility in value terms in solving the problem. No knowledge is valid for all time. It needs to be revalidated continuously as the problem may have undergone a change, or better knowledge may be available to solve the problem. Further every knowledge, over a period of time, becomes general knowledge, a well documented information. Search for new knowledge through the knowledge discovery process must be continuously on. At this juncture, it is necessary to understand the precise difference between information and knowledge. Though knowledge is the outcome of data-information analysis, at some stage, both are different. Knowledge is a concept, an insight, an embedded product with well defined application. It remains unaltered for all time till it is improved upon, or knocked out, or replaced by something new. Knowledge provides capability to decide and act. Information does not give capability to act. Knowledge has problem solving potential while information does not have such potential. Knowledge creates new vision and opportunity, while information may open short-term vision or opportunity. Knowledge, at some stage, can be measured in value terms, but information cannot be measured in value terms. Information is always available in coded format but knowledge, in all cases, is not available in coded format.

The Objectivist Philosophy of Knowledge The objectivist views knowledge as an entity or object. It is an undisputable fact. The objectivist prefers explicit knowledge over tacit knowledge. Knowledge is an intellectual processing of data and information. It, being an entity, can be possessed by people. It can be in the form of a computer program, a diagram, a system, such well defined objects. It can be in embedded form in DSS, Tools, Machine and expert systems. The knowledge can be developed independent of individual’s subjectivity. Since knowledge is an entity or object, it can be processed at will, it can be codified for convenience and common understanding, and it can be stored in central repository in structure. Technology plays a key role in knowledge management processes.

Practitioner’s Philosophy of Knowledge The practitioners view knowledge as an experience gained in practicing some activity for obtaining some desired results. They believe it cannot be easily put into any form. It is captured, experienced and improved upon while using it for some application. Knowledge is triggered by an individual’s experience but it gets consolidated socially by a group of people. Since it is highly people oriented, it is contested by others who have different experience and hence knowledge. It is multi-dimensional and emerges out of continuous process of tacit to explicit; they are inseparable from each other.

Data–Information–Knowledge–Intellectual Capital Continuum This continuum from data to knowledge and IC can happen in two ways. One where data is sourced from a ‘data store’, like files, folders, disks and databases. And the other is where data is sourced from experts or human beings. Both paths of knowledge generation lead to creation of human capital, intellectual capital, and creation of intellectual property. In data continuum, data is captured and processed using different data processing tools, revealing new insights, patterns, trends, relations, and so on. Pooling these together creates human capital and intellectual capital. In HR continuum, the source of knowledge is experts, specialists and domain experts contribute to knowledge development through tacit knowledge. This route also creates intellectual assets, knowledge products.

Knowledge, IC, Products, Processes Data From Multiple Data Stores

Selected Data Extraction and Processing

Fig. 2.1

DWH Data

Information

Data Mining

Processing with Context

Business Data Processing for DWH

Analysing, Interpreting, Inferring the Results and Developing Knowledge

Store, Transfer, Share, Improve Revalidate

Data Driven Continuum of Knowledge Creation

ATTRIBUTES OF KNOWLEDGE Characteristics of Knowledge Harlan Cleveland describes six characteristics of knowledge in his book ‘The Knowledge Executive’. They are described below.

Concepts, Ideas, Hunch, Relations, Thumb Rules, Best Guess

Observation, Visualisation Analysis, Guessing, Judging, Forming Thoughts

Fig. 2.2

Application of Analytics, Conceptual Prototyping Interactions, Informal Exchange of Thoughts

Framing Models, Procedures, Heuristics

Experimenting, Testing Validating, Designing Solution Models, Programs and Embedding

Embedded in Systems DSS, Programs

Explicit Confirmation of Solution Models, Programs by Application in DSS, Designing Products, Obtain Licenses, Patents

Knowledge, Products, Patents, Licenses

Store, Transfer, Share, Improve, Revalidate

HR Driven Continuum of Knowledge Creation

Expandable Knowledge, on use, expands, becomes more rich. Example: Customer behaviour knowledge is expandable with more consumer behaviour research, customer feedback on product or service usage, and so on. Knowledge cannot be a constant entity as it changes with experience of using it. Compressible It can be compressed by codes, symbols and diagrams. Example: Knowledge of product usage under different conditions is documented in product manual and in some cases, it is posted on the website of the organisation. Product knowledge normally has text accompanied by process diagrams, pictures, standard symbols, etc. One can examine the TV manual, vehicle manual, camera manual, and all such manuals. Knowledge in these manuals is compressed using codes, symbols and diagrams.

Transportable On compression or otherwise, it can be moved from one location to other through network. Example: Systematically compressed knowledge can be stored on any electronic media, server or database for access to download or transfer through network. Sharable It can be shared and does not reduces in any manner on sharing. Example: Since knowledge is on media, it can be shared selectively with selected people backed by security measures. Sharing of knowledge makes it more enriched due to experience. Sharing encourages its use more intelligently. Internet and Intranet and network of knowledge workers share knowledge for collaboration in work. Diffusive It is easy to diffuse if not protected wisely.

Example: Knowledge being of high economic value runs the risk of getting diffused or stolen. Hence, it needs protection. Confidential data, information and knowledge need security cover of highest order to mitigate the risk of diffusion in wrong hands. Substitutable It substitutes or replaces the need for other resources. If knowledge is not available at branch location, an expert needs to rush to the branch. If the knowledge possessed by the expert is available in knowledge data base then it substitutes the expert resource. Example: When computer vendors developed knowledge based on line support Systems for their customers, the number of support engineers reduced. The distributed knowledge, know how, was systematically programmed for online support.

EXPRESSION OF KNOWLEDGE Knowledge, for more understanding and expression, can be classified in seven ways. Procedure This knowledge systematically guides how to execute a task or conduct an activity. The procedure details the steps to be carried out and skills and tools required to complete the task successfully. Knowledge when used repeatedly in a particular manner becomes an automatic application to perform some task or activity. It becomes a procedure well accepted by all. Knowledge is expressed in a procedural format. Declarative This knowledge declares the ‘cause and effect’ immediately. For example, if body temperature is 99°C or more, the person has a fever. If blood pressure is more than 100 points, chances of heart attack are very high. Thus knowledge is a declarative statement of the cause and effect relationship.

Structured When knowledge can be organised in a structured manner using some reasoning or logic, it is termed as structured knowledge. The engineering drawing is a structured knowledge explaining the design, the relationships between different systems, and so on. Knowledge is expressed in hierarchical, network or layered structure. Experiential This knowledge is built out of different events, episodes or pre-planned experiments. For example, study of accidents on Highways and Freeways during night reveals certain characters of drivers and their style of driving. This reveals association of accidents to certain types of drivers. These findings are obtained from research and analysis of available data or data obtained through setting up an experiment.

Semantic When knowledge is organised in structured manner using engineering and scientific facts, it is termed as semantic knowledge. Knowledge is built on sound concepts, theories, facts and relationships among different variables and constants. For example, body weight has an impact on blood pressure and blood sugar which may lead to stroke or cardiac arrest. It requires regular check up from a cardiologist. Know how Know how is more precise, and is at variance with knowledge. Know how is the knowledge which is built out of practical experience obtained by applying knowledge. Know how is more useful in building expert systems. It is an expression of the knowledge which has more value due to a component of experience gathered by application of knowledge. Rule Knowledge when precise and complete and on application gives the same outcome, it is termed as a rule. This is an expression for the well defined, logical flow of set of instructions which, when applied by anybody, give the same result. It is far superior to procedure. Program When knowledge is recast into a set of instructions, arranged in a logical sequence, giving regard to conditions and standards, etc, it is termed as programme. Program continues to give same results till it is changed. The software program is an example of knowledge as a program.

Heuristics It is a knowledge which built on some reasoning of credibility, inductive or deductive. The outcome will not be as precise as in the case of procedure, rule or programme.

Coded Expression to Knowledge Codification is a process of converting the knowledge into a form, termed as code, which a user can identify, extract and use for business gain. In simple terms, it means ‘writing’, or writing it down to make knowledge independent of people to make it an organisational resource. It sounds very obvious and simple but in most organisations the ‘writing it down’ practice is almost absent. It needs to be formally put into use for knowledge management. Technical knowledge, by virtue of its character, gets written down or documented as a part of its own process, ‘generation to application’, in the form of drawings, pictures, notes, and so on. But there are no widely accepted practices or methodologies for knowledge which is not technical and is sourced from experts and specialists. This knowledge is less formal and is documented in the brains of experts and specialists. Codifying this knowledge, a tacit knowledge, is very difficult, and it can possibly be codified a document at a very high cost. Furthermore, absorbing such knowledge is time consuming and is a cost to the organisation. Instead, users prefer to interact and understand this knowledge from people who have it. But this process also has a cost as no formal interaction opportunities are available. One-to-one interaction is possible, though difficult and impractical, at a very high cost of expert’s time. It is bad practice to issue mandate for codification during normal working, sourcing from project reports, proposals, financial reports, cases and case study reporting, etc. This may not happen and is also difficult to make it publicly known to all. It is also difficult to select knowledge which is worthy of codification. Knowledge is worth codifying in a coherent form if it satisfies the following criteria. • It has business value or economic value of significance, because it helps people to think better than before, design better, deliver faster, reduce customer rejects and develop lean and efficient processes. • Many people within and outside the organisation demand it. • The chance of losing knowledge is high as experts may leave the organisation.

Creative and Innovative Knowledge Knowledge irrespective of its type, kind class and philosophy, provides an opportunity to grow fast, beat competition and create sustainable competitive advantage. The business can be leveraged on knowledge to take it to higher order of performance. It may change its direction, bringing more business opportunities to grow or expand. Knowledge may enable the organisation to become lean and cost effective and deliver high customer value. Knowledge, therefore, is the mother of creativity and innovation. Number of examples can be given to support this argument. Some well known examples are given here. • Tata Motors, customer knowledge about aspirations, expectations, purchasing power and dream to have a four wheeler gave rise to an opportunity to design and produce the ‘Nano’ passenger car. This knowledge created a number of opportunities for vendors and suppliers to innovate their products and processes. • The process knowledge coupled with technology knowledge gave an opportunity to reengineer processes resulting in a lean manufacturing process. The processes became more intelligent by embedding knowledge driven decision processes into the manufacturing process

• Knowledge combination gives rise to new creative and innovative opportunities to take the business forward. The knowledge of location through GIS and customer service requirement knowledge together decide which service vehicle on the road would reach the customer location earliest. When experts from diverse domains come together and interact objectively they bring out new opportunities which often are innovative, giving edge to overcome competition to the organisation. Creativity and Innovation are outcome of experts, knowledge based interaction on various issues.

Intelligence Intelligence is next to or beyond knowledge. It is human and judgemental. Intelligence enables one to identify and solve the problem and how to solve it. Intelligence guides the use of knowledge. It is the capacity to respond to specific opportunities and challenges as they emerge. It is the capacity of an individual to acquire knowledge and apply it effectively to resolve problems. Intelligence, in broader sense, is an assembly of data, information and knowledge, collected and configured to address certain issues and problems. Military intelligence, business intelligence and clinical intelligence are examples of special cases of intelligence. Intelligence is the capacity to acquire knowledge and apply it effectively to solve the problems, build strategies, and so on. Intelligence enables to improve the quality of knowledge acquired from experience gained on its application. We deliberate here more on business intelligence.

Wisdom Wisdom is the knowledge with deep insight. Wisdom supported by core knowledge ensures smart application of knowledge in problem solving. It extracts more value out of knowledge. Knowledge with insight (Wisdom) makes it easier to decide ‘where and where not’ it should be used. Wisdom is the accumulated experience and learning from knowledge application while solving the problems. While wisdom refers to our efficient use of knowledge, intelligence refers to our effective use of knowledge. The process of moving from Data to knowledge and then intelligence is a well defined one. We will deal with it in a later chapter. Data to wisdom can be viewed in a hierarchical structure as shown in Figure 2.3.

Wisdom

Objective Assembly of Knowledge

Intelligence

Knowledge Information

Context Processing

Fig. 2.3

Ability to Think Judiciously the Application of Intelligence

Data

Hierarchical Structure: Data to Wisdom

Analytical Processing

HUMAN THINKING AND LEARNING At the core of knowledge and related initiatives, processes and activities is human learning. Figure 2.4 shows a model of the human learning process.

Fig. 2.4

Academic Search, Research and Assimilation of Thoughts

Building Concepts, Basics, Fundamentals

Sharpening the Conceptual Foundation

Intelligent Observation of the Environment

Application to Problem Resolution

Forming Ideas, Giving shape, Building Thumb Rules, Solution Models

Gaining Experience In analysis, Reading Understanding of the Insight. Building Application Skills

Body of Lessons

Human Learning Process

The human learning process is a long one and squarely dependent on individuals and their intrinsic abilities to view situations from different angles, and connect conceptual constructs to resolve the problem situation. When lessons become more valid for application and provide confirmed problem–solution relationship, the body of lessons become knowledge. This may be tacit or explicit and may belong to any class. The human learning process described for individuals is also applicable to groups or teams coming together to achieve something concrete. For example, a project manager and his team learn together a number of lessons of better project management. A group of fire fighters equipped with fire fighting equipment learns a number of lessons during the course of various fire extinguishing challenges. New group learning processes are always emerging and the lessons are learnt by the team. It becomes a body of lessons when the group comes together and deliberates on them to build aids and tools to perform better. When individuals, groups or teams come together under the umbrella of the organisation, it becomes the organisation learning process. The organisation builds lessons in the management, strategy, functions and operations of the business. It delivers better with the help of organisation learning process. This learning or lessons could be in the form case studies, legal or technical documents, models, etc. When an organisation has a vast body of lessons in business management, it is declared as expert in the specific domain. Such lessons and learning over a period become knowledge. Some of it is an asset, an exclusive possession of the organisation, so it becomes intellectual property of the organisation, protected by law. The learning processes of an individual, group, and organisation are driven by two drivers. • Experience of application Learning and building lessons by trial and error, working and reworking, engineering and reengineering. • Example Learning and building lessons by example, illustration and cases.

• Discovery Learning and building lessons through prototypes, experiments, organised research, and so on. Let us illustrate these concepts about knowledge with an example from the domain of health care. • Procedural Taking blood pressure of a patient every hour is procedural knowledge. Para medical staff of the hospital is trained by procedure to record BP of the patient using a machine. • Declarative This knowledge declares the cause and effect immediately. For example, if body temperature is 99°C or more, the person has a fever. If blood pressure is more than 100 points, chances of heart attack are very high. • Structured A record of various pathological tests and X-rays together is structured knowledge about the patient’s health to confirm the symptoms into a diagnosis. The arrangement of knowledge is presented in hierarchical order. It is also read by the doctor in the order of importance and relevance. • Experiential The doctor prescribes medicine to the patient, collects feedback on its impact and adjusts doses to fix the health problem. The experience of using a particular prescription and its effects on the patient is experiential knowledge. • Semantic Knowledge When knowledge is organised in a structured manner using engineering and scientific facts, it is termed as semantic knowledge. For example, body weight has an impact on blood pressure and blood sugar which may lead to a stroke or cardiac arrest or may affect the kidneys. It requires regular check up from a cardiologist. • Tacit The cardiologist has experience of different types of patients young and old male and female nature of work and degree of stress and tensions, etc. This gives him tacit knowledge of differentiating one patient from an other though diagnosis is same in all cases. He drafts the prescription and doses accordingly. • Explicit The cardiologist, in standard case of patient, puts on paper a prescription specifying order, doses, timings and tests to be conducted and health parameters to be noted in a particular fashion or practice. The knowledge and its use are coded in the language of the hospital. Explicit knowledge here is objective, impersonal, context independent. In other words, explicit knowledge held by all cardiologists of same competence would be the same. The application of knowledge in all cases would be identical.

Business Intelligence In global business environment, business operations have become complex due to the competitive nature of the business. The managers need to understand this complexity, its implications and its impact on business performance. Such understanding is possible only when access to multiple information sources is readily available through tools, methods and processes. The assumption here is that the organisation has developed information systems to cater to this need for business management. Business intelligence is a set of concepts, methods and processes to improve business decisions using information from multiple sources and applying experience and assumptions to develop an accurate understanding of business dynamics. It is a combination of methods and processes with tools to extract information from various sources. It enables the gathering, management and analysis of data to produce information which represents the new scenario. This information is distributed to people throughout the organisation to improve strategic and tactical decisions to deal with the new situation effectively. Let us take an example of military intelligence to understand the meaning of Business intelligence.

Command headquarters near Line of Control (LOC) continuously need military intelligence support to extract information and knowledge to understand the meaning, motive and objective of troop movements across the border. Troop movements across the border happen in small or large number any time of the day. But border security force must understand the motive behind such movements to evolve military strategy to counter the move. To understand the meaning and motive behind the movement, a variety of information from various sources is needed. It, therefore, needs tools and applications to access, extract, model and interpret the information. Information about the enemy in terms of their number and GI about their position, equipments and ammunition being carried, depots and Vehicles, and so on, is required. Suppose such data and information along with knowledge about all earlier movements mean that ‘soldiers are likely to sneak in from a particular location on the LOC during the night. To counter this move, the commander should have access to data, information and knowledge about own establishment and resources to plan his strategy. He requires information about soldiers near the position of LOC, military hardware support for night operations, geographical information and clear understanding of terrain to plan counter offensive. All this information needs to be maintained by a separate system infrastructure, and tools need to be provided to extract this information and collate it for understanding the meaning of troop movements and generating counter military strategy. The tools, methods and processes developed by the military establishment are collectively called military intelligence.

The power of business intelligence actually relies on the knowledge acquired through the analysis of various reports taken using business intelligence reporting tools. Business intelligence reporting tools, or OLAP Tools, provide different views of data by pivoting or rotating it across several dimensions. Business intelligence tools are capable of displaying data in several formats, like tables, pivots, charts, query results and reports. Business intelligence succeeds when the organisation first determines what constitutes ‘intelligence’ for the current business scenario and then proceeds to establish systems and processes to produce that intelligence. A competitive business organisation has following business intelligence (BI) in place. • Multidimensional analysis of key results or events • Data mined view of a situations • Forecasting models • Business analysis (OLAP) diagnosing the problem • Visualisation for different perspectives • Querying and reporting systems • Knowledge management for knowledge applications • Balance scorecard preparation • Digital dashboard preparation • Enterprise portal implementation • Relevant databases

Modeling and Analysis techniques for Business Intelligence BI requires extensive use of modeling and analysis techniques. Let us briefly discuss what they are and how they are used.

Business Modeling A business model provides information in a graphical way, in diagrams, to the members of an organisation to understand and communicate the business rules and processes effectively. Business process modeling, process flow modeling and data flow modeling are sub-categories of business modeling.

Data Modeling Data modeling is about representing the real world set of data structures or entities and their relationships in the form of data models, required for a database creation. Data model is a visual representation of the database. It consists of types and phases, like conceptual data modeling, logical data modeling, physical data modeling, enterprise data modeling, relational data modeling and dimensional data modeling. It provides tabular picture of an entity by its attributes and relationship structure. For example, data model of a product would be product, unique key for identity and its various attributes. The product has relationship with customer, production unit and processes. Product model shows these relations by ER diagrams. Let us take an example of an organisation which sells a product to a customer. • Customer data model Customer name, customer code, address, type of business, credit limit, customer rating, type of customer • Product data model Product name, product code, product model, application, price • Customer – Product Relation Model Customer

Orders

Product

Product and customer relation is expressed by the ER diagram, where relation between the customer and product is described as ‘Ordering’. And this relation is in ‘one to many’, i.e, customer orders many products in one purchase order. For that matter, any relation between two entities is knowledge.

Dimensional Modeling Dimensional model comprises of a fact table and many dimension tables, and is used for calculating summarised data in different perspectives. A fact table contains various measures or facts, like sales amount, production amount, etc., whereas a dimension table describes the particular entity, like time, state, etc., based on which the required facts are measured. Let us take an example of ‘product returns’ from the customer, returned for various reasons. (See Figure 2.5). The product returns is a fact table which shows quantity, reasons and value of return. This information has four dimensions-customer segment, product group, factory where product is manufactured and the process and technology used. Any alarming situation due to product returns needs to be understood from these four dimensional perspectives. The BI of the organisation has processes, methods and tools to access, extract and transform the information in a meaningful context-sensitive format to investigate the causes of return to take corrective action. The returns are measured by these four dimensions.

ETL, An Implementation Process ETL, an acronym for ‘Extraction, Transformation and Loading’, is a collection of application tools associated with extracting data, transforming that data into business data and finally loading it into a data warehouse.

Process & Technology

Legend Dimension Tables

Customer Segment

Product returns From Customer: Quantity, Reasons of Return and Value

Product Group

Fact Table

Factory Unit

Fig. 2.5

Fact Table and Dimensions of Product Return

ETL tools populate the data warehouse. The transformation involves several processes, like data cleansing, data profiling, data type conversion, validating for referential integrity, performing aggregation, if needed and de-normalisation and normalization of data.

OLAP OLAP, an acronym for ‘Online Analytical Processing’, is a technique by which the data, sourced from a data warehouse or data mart, is visualised and summarised to provide perspective multidimensional view across multiple dimensions. Generally, OLAP refers to OLAP Tools (for example, Cognos, Business Objects, etc.) that help to accomplish these tasks.. OLAP tools provide options to drill-down the data from one hierarchy to another. OLAP tools visualise data in an understandable format, like in the form of Scorecards and Dashboards, with Key Performance Indicators enabling managers to monitor and take immediate action.

Data Mining Data mining is a set of processes related to analysing and discovering useful, actionable knowledge from data warehouse, data stores or data sets. This knowledge discovery suggests patterns or behaviours within the data that lead to some strategic thinking leading to profitable business action. Data mining generally requires large volumes of business data, including its meta data, to explore the knowledge. Once the required amount of data has been accumulated from various sources, it is cleaned, validated and prepared for storing it in the data warehouse or data mart. BI reporting tools capture the required facts from the data to be used by the knowledge discovery process. Data mining can be accomplished by utilising one or more of the traditional knowledge discovery techniques, like Market Basket Analysis, Clustering, Memory Based Reasoning, Link Analysis, Neural Networks, and so on.

Ontology An ontology is a formal specification of the vocabulary to be used in specifying knowledge. It may be thought of as a network of objects, each of which has attributes or properties unique to that object. The purpose of ontology is to provide a uniform, text-based, intermediate representation of the knowledge types, specific to a development effort that is understandable by either humans or machines. The intermediate representation provides a means of describing knowledge, at any level of granularity, without expert knowledge

of the specific technologies that will be used to implement that knowledge. This representation is useful on a number of levels. They are listed below. • For users, who need to describe knowledge to be added to the system, ontology offers a standard vocabulary and guidance in creating precise specification. • For developers, who need to understand what knowledge is already in the system, the intermediate representation provides a rich description of the knowledge and an index to its representation within specific technologies. • For technical writers, who need to unambiguously describe behaviour, it offers a domain-specific (but technology-independent) vocabulary. Use of ontology as an intermediate knowledge representation form also allows the underlying technologies to be upgraded or replaced, as needed. Ontology should expand on any work already done to standardise the terminology used in a given domain and to include objects of all types relevant to the project. The anticipated evolution of ontology is that it will begin with the identification of certain simple terms and their arrangement within a network or hierarchy. As experience is gained in representing the knowledge, complex terms will emerge that act as a means of functionally grouping a number of simple objects together (for example a problem/resolution might consist of one or more events, the associated underlying failures and one or more procedures). One metaphor for this is LEGO building bricks; a fixed set of objects is defined, each with its own properties and ways in which it can be connected to other objects. Users may choose to instantiate objects, assemble them in a precisely pre-defined manner (similar to buying a LEGO model and assembling it as defined in the instructions), elaborate on a pre-defined model, or assemble them in some novel but useful fashion. Ideally, all of these approaches are supported. A software based tool supporting ontology should be able to do a number of different things: • Creation Given a simple or complex object type, lead the user, with form and menu based interfaces, through supplying the necessary information. Knowledge of an underlying representation, such as the Knowledge Interchange Format (Genesereth and Fikes, 1992), should not be required. • Browsing Enter the ontology from any point and browse the representation in the manner of a hypertext document. Alternatively, enter key words and view all related terms. The task of figuring out whether something is already in the system should be made as easy as possible. • Guidance Use the attributes and relations that have already been defined to dynamically identify object types, or guide the creation of new object types. For example, present a menu of attributes and relations to the user. As they cumulatively select the appropriate terms that they know they need to define, they see a list of all those object types that contain that term. The list should quickly get small enough for the user to either identify the correct object type, or realise that he needs a new object type (in which case, the terms selected would serve as the basis for formal specification of that type). In addition, it is expected that any software developed would actively support the knowledge acquisition and management process and be easily modified in response to changes or refinements in the process. (Source A Process for Knowledge Acquisition and Management, Jeffrey D. Kenyon, Member Technical Staff, US WEST Information Technologies, Inc.1801 California Street, Suite 1640, Denver, CO80202)

TACIT AND EXPLICIT KNOWLEDGE Knowledge, on creation, can be put into two types, tacit and explicit.

In a knowledge creating company, evolving process of tacit to explicit and back, is a dynamic interaction, a kind of spiral of knowledge evolution. The Masushita’s Ikuko Tanaka story explains this cycle. • First she learnt the tacit secrets of the Osaka International Hotel baker (Socialisation/ Interaction). • Then, she translated these secrets into explicit knowledge that she could communicate to her team members at Matsushita (Articulation/ Externalisation). • Further, the team standardised this knowledge by systematic organisation and documented it into a manual, or workbook, for use in product preparation (Combination/ Packaging). • Finally, the experience of using this knowledge made team members’ tacit knowledge base richer by the day (Internalisation/ Absorption). The story tells how the knowledge of the baker was used in production of the home bread making machine. Explicit knowledge is objective and context independent, and can be coded for its management. In contrast, tacit knowledge is subjective and context specific, and cannot be coded by any means. Tacit is personal while explicit is impersonal. The Time Series Forecasting model is explicit knowledge, created to forecast any entity in relation to time, using past data. Its objective is to forecast. It is context independent as it can be used for forecasting sales, production, rainfall or population. Further, the Time Series Model is coded in the form of an equation using two or more variables. The knowledge of a medical consultant, say a physician, is tacit as it is developed over a period through examination and investigation of tuberculosis patients. It is context specific (tuberculosis patients), and is subjective so far as its application is concerned. The knowledge can be used for diagnosis, treatment or monitoring the effect of prescription on the patient’s well being. Being subjective and context dependent, it is difficult to code for general purpose application. Knowledge, tacit or explicit, builds capability and understanding that enables to envision different ways of handling situations and anticipate its implications and impact on the environment.

Explicit Knowledge Explicit knowledge can be articulated into formal language text, mathematical expressions, specifications, manuals, etc. Explicit knowledge, in electronic media, can be readily transmitted to others. Also, it can be easily processed by a computer, transmitted electronically or stored in databases: • This knowledge can be systematically expressed; it is possible to code and it can be stored, transferred and shared through any medium. • Explicit knowledge is that which is written down or expressed in some tangible form, such as in a procedure manual, document or computer database. • Examples Dictionary, recipe book, software product, ready reckoner, rule, procedure, programme, heuristics and solution model.

Tacit Knowledge It is a personal knowledge embedded in individual experience and involves intangible factors, such as personal beliefs, perspective and the value system. Tacit knowledge is hard to articulate with formal language like explicit knowledge. It contains subjective insights, intuitions and hunches and conceptual models of solutions. In addition, there are two dimensions to this knowledge. For communication, this knowledge must be converted into words, models or numbers to understand and to communicate. It cannot be shared or

transferred easily as it is not possible to code. It is subjective, personal, may have a bias, context specific and difficult to share due to its nature. It is termed as insight, experience, judgement, ability to differentiate, and is also termed as know how and know why. Examples Knowledge possessed by consultants, strategists, scientists, designers and Architects. Some key features of tacit knowledge are: • Highly personal • Hard to formalise and therefore difficult to communicate to others • Deeply rooted in action and in an individual’s commitment to a specific context, profession, activities of a work group or team • Something that we simply know, possibly without the possibility to explain • Human beings are the storage medium of tacit knowledge • Not very easily amenable to technology

Technical Dimension (procedural) Knowledge This encompasses the kind of informal and skills often captured in the term know-how. For example, a craftsperson develops a wealth of expertise after years of experience. But a craftsperson often has difficulty articulating the technical or scientific principles of his or her craft. Highly subjective and personal insights, intuitions, hunches and inspirations derived from bodily experience fall into this dimension. This is largely procedural tuned and refined for each problem resolution. The tacit knowledge user develops own approach to each problem step by step with specific context of the problem. It is a procedural sequential approach which may undergo a change when applied to new problem. Cognitive Dimension This consists of beliefs, perceptions, ideals, values, emotions and mental models so ingrained in us that we take them for granted. Though they cannot be articulated very easily, this dimension of tacit knowledge shapes the way we perceive the world around us. (Source Nonaka & Takeuchi). This dimension takes care of the influence of beliefs, values & strong association of problem & association built over a period of time. Knowledge can be better understood if it is put in a matrix divided into two parts ariculated and Coded by and the nature is explicit. The second is tacit knowledge, not coded and not articulated but embodied in the minds of individuals. Knowledge: • Explicit Knowledge: Creater: Nature: Store: Share: • Tacit knowledge: Creater: Nature: Store: Share:

Individual

Group

Organisation

Competence

Collective assets

IC & IP

Memory On demand On request Interaction

E-Document Collaboration through Groupware

Servers Authorised access Tech.

Capability

Know how

Human capital

Memory Work Together

Collective memory. Demonstrate, participate

Organisation memory. Conference Seminar.

Let us discuss the knowledge types more precisely with examples.

You and The Taxi Driver When we visit a new city for work, or for important meeting, the first thing we do is collect the map of the city, showing lanes, roads, important landmarks, airport, railway stations, bus terminal, places of interests, like museum, gardens, malls, and so on. Your colleague who had visited the city earlier has given you a sketch to safely reach the conference venue. The sketch in this case is ‘Information’, where context is how to reach the destination. You also buy the map to guide the taxi driver to reach the destination. In this case, the map of the city is ‘Knowledge’, explicitly expressed and presented in the manner of internationally accepted standards, with the context of describing the town or city. This is knowledge compiled and presented in a code for identifying ‘Where what is and how to reach there’. The map is a repository of explicit knowledge. You engage a taxi and direct the taxi driver to take you to the conference venue in next half the hour. You give the city map to him but he says that he knows the place and would reach the venue in twenty minutes. The taxi driver has a knowledge which enables him to reach faster. The experience of driving the taxi for more than five years has given him deep insight of roads and lanes, a knowledge about how to shorten the distance of the journey at different times of the day. He has already mapped the city roads and lanes to avoid signals, traffic jam possibilities and pedestrian crowd which results in hold ups and delays. The different road map models at different times of the day are tacit knowledge developed by the driver. This knowledge cannot be easily coded to share or transfer to other drivers or visitors. This knowledge of the driver is highly procedural, visualised in mental network of roads and traffic intensity during the day.

Professor of Chemistry vs Scientist in National Research Laboratory (NCL) vs R&D Chief in Heavy Chemicals Ltd The professor of chemistry has vast amount of information and very little knowledge about its application for solving the problems in the real world. His knowledge is based on laboratory experiments designed for teaching the students. Its content is largely information and can be packaged in the text book. But, still, it cannot be termed as knowledge in strict definition of knowledge The scientist in NCL is well informed about chemistry as a subject. He has the information, but he has used the information to conduct research through various research projects. The findings from the projects are published in international journals. They are an explicit knowledge. Being explicit, they can be shared or transferred in the community. The research findings, explicit knowledge, are impersonal and public, as they is coded and published. Beyond the findings, the scientist also got better insight in the properties of chemicals, their interactions in different conditions and their implications in practical terms. This knowledge is bit hazy and difficult to confirm and code, but is of great value for further research. This is a tacit knowledge which is persona to the scientist. The R&D chief uses explicit knowledge and conducts research in the R&D laboratory for industrial application. The knowledge is developed to improve products and processes to create competitive advantage. The additional knowledge of industrial application over and above the publicly known explicit knowledge is partly tacit and largely explicit, and has exclusivity due to its ownership by an individual and an organisation. This knowledge is intellectual property of the R&D chief and of the Heavy Chemicals Ltd. It is a knowledge asset of the organisation. The knowledge, if it is exclusive in terms of ownership and when it has economic value and creates sustainable competitive advantage to the organisation, is termed as knowledge asset. The business impact of data, information, knowledge and BI on business management is shown in Figure 2.6. The business data readily available for use impacts operational efficiency of the people, and of

the organisation. The information supports decision making and has an impact on management effectiveness. Knowledge enables creation of strategy and its application in solving the problems. It enables individuals to be creative and innovative. Business Intelligence Provides Strategic Advantage Gains Competitive Advantage Improves Decision Making

Knowledge Information

Data

Improves Operations Efficiency DPS

Fig. 2.6

IS

KMS

BIS

Business Impact of Data, Information and Knowledge

Knowledge by Application The class of knowledge is determined by its use and the purpose for which it is used. To understand the concept of class of knowledge we must understand the organisation pyramid and the needs of information and knowledge at different levels in the organisation. The organisation model is divided into three parts: loweroperations management, middle-business management, top: strategic management. In each level, the type of knowledge required has a linkage to management focus and decision orientation of the people in that level, as shown in Figure 2.7.

Knowledge Assets, IPs; Strategic Decision Oriented Business Management Knowledge; Business Decision Oriented Work Place Knowledge; Task Decision Oriented

Fig. 2.7

Knowledge Classification by Decision Orientation and Organisation

Work Place Knowledge Workplace knowledge is the ability of the people to understand the work situation and to act effectively. This knowledge is explicit and hence available in coded form, and is easily accessible from portal and intranet. It is represented through check lists, diagrams, drawings, images and manuals. Some of it is available from the Help Desk. An individual or a group supported by workplace knowledge is able to complete the task efficiently and effectively. Workplace knowledge evolves out of practice and experience. It is enriched day-by-day becoming more useful. The owner of workplace knowledge could be an individual or a work group. It is generally task oriented, and is used to make binary kind of decisions, such as Go no Go or Yes or No. There is a fair amount of correlation between task and knowledge. Task, at the core, is same but has a variable components which require workplace knowledge to handle it effectively. The typical workplaces where workplace knowledge is required are reception desks, airlines counters, teller windows, stations on assembly lines and work centres in manufacturing. It is also required when people are working in Network, and together deliver something to the next work centre.

Business Management Knowledge In middle management, knowledge is required to manage the business and processes efficiently and effectively. It is largely business decisions oriented. These decisions affect the performance business. If not taken correctly, and not implemented properly, they affect the targets, budgets and functional goals. The managers in this category are responsible and accountable for Key Result Areas (KRAs). They are responsible to work on Critical Success Factors (CSFs). Their performance is judged by the attainment of Key Performance Indicators (KPI). The knowledge requirement is ‘how to manage every situation effectively and efficiently’ and achieve the goals and targets in KRAs. It is a tough balancing act to carry out successfully using approaches like Tradeoff Analysis, Pay-off Analysis, Resource optimisation, modeling the problem and generating alternative solutions, Sensitivity analysis of the solution, Decision Support Systems, and so on. The need for the knowledge and its specification are influenced by types of decisions and their impact on the performance. The decision impact is short-term, and the nature of the problem is such that its resolution is very important. The decision areas revolve around the tasks of maintaining competitive necessities and sustain competitive advantages. Business management knowledge can be described as a body of knowledge which identifies the problem proactively, suggests solution ideas, enables modeling of the problem and helps to solve it through various approaches of problem solving. The manager must be well versed and competent to use the problem solving and decision making tools. It is important for the manager in this category to have domain knowledge of the business and industry in which the organisation is operating. The proficiency in using tools and techniques of management science knowledgeably is of at most importance.

Intellectual Capital: Comprising Patents, Knowledge Assets and Tacit Knowledge The top management has the difficult task to take the business to new heights, establish leadership in the market and transform or expand the business for growth. In the process, they have to face the challenges of competition. In real sense of the matter, they are risk managers. Their job is to view the business ‘outside–in’ and evolve strategies to meet the challenges of the continuously changing business environment. To handle these responsibilities, top management needs, over and above

business management knowledge, a set of body knowledge which is unique to the organisation. It is perceived as a differentiator. Such knowledge is, in most cases, intellectual property, some of it is patented and the rest is knowledge asset. This knowledge is predominantly used for strategic management of the business. Its application is in the area of strategic thinking; evolving strategies, evaluating them for selection and implementation. Assessing strategy performance by monitoring their implementation and execution measuring strategy performance through predetermined KPIs is the main task of the people at the top of the organisation.

Sources of Knowledge in the Organisation The knowledge in the organisation exists at various locations in different forms. Some of it is easily accessible while some is not. In every organisation, people are the basic source of knowledge. They develop knowledge out of experience which they get through working. The knowledge may be static or explicit but it takes shape in the human mind. Then, as it gets defined and developed, it gets stored in files, databases and project reports of the R&D projects. On the shopfloor, it is recorded in logbooks and folders. The knowledge gathered on the shopfloor is about machine performance, product and process performance, quality control issues and their resolution, effectiveness of tools, and so on. In the executive suite, senior management deliberates on a variety of subjects and issues challenging the business. This management adopts different problem solving approaches, methods and models to solve the problem. This exercise, over a period, provides better insight and confirms efficacy of one solution model over the other. It builds some thumb rules or guidelines to be followed if the problem is of particular type, and so on. A well designed Knowledge Management System (KMS) helps in identification, validation, storage and distribution of the knowledge. This topic will be dealt in the chapter on KMS.

KNOWLEDGE: A DRIVER FOR CREATIVITY AND INNOVATION Creativity and innovation in every aspect of the business are highly beneficial for survival, growth and attainment of superior performance. If the organisation is knowledge driven and people are constantly in the learning mode to add or upgrade their knowledge, the chances are very bright that they come out with new path breaking ideas and are able to translate them innovatively into products, processes, and features. Creativity is the phase in which ideas emerge, and in innovation idea gets converted into practice. Creativity is a result of knowledge application to search an idea which will transform or radically change the present scenario. Knowledge makes innovation faster and better. Idea is a conceptual model of the solution developed out of knowledge. It germinates out of tacit and explicit knowledge. Throughout the process of creativity and innovation, the knowledge continually moves from tacit to explicit and qualitatively improves all the time. Earlier in this chapter, we classified knowledge in three classes using decision orientation as a key. On similar lines we can classify knowledge as a driver for creativity and innovation in the following manner.

Customer Knowledge Customer interfacing systems, like order processing, service management and CRMs capture a lot of data which then moves to data warehouse for intelligent use through data mining applications. DWH and data mining produces a lot of knowledge about customer behaviour, choices and biases, and so on. This knowledge is potentially strong to generate ideas and to develop innovative strategies to enhance the business. Traditionally, organisations rely on market research, different surveys on customer satisfaction and perception. But knowledge gathering through such means is not continuous, and this approach has a limited scope and

specific focus. Customer knowledge here means discovering what is not expressed by the customer, what is not stated by the customer in requirement specifications, and so on. Customer knowledge is about why certain customers are loyal and why some are not. This knowledge is captured during customer interactions, feedback surveys, unsolicited comments on a number of things, comments on what competitors are doing, and so on. This knowledge generates different innovative value propositions the customer is looking for, a booster for creativity and innovation.

Products or Services Knowledge During the course of business transactions, the customer gives valuable feedback through various channels of communication. Knowledge can be captured through analysis of data and information delivered through these communications. Further, knowledge can be searched from the repositories of the systems, namely Feedback Analysis, Service Demand Analysis, Analysis of Complaints and compliments on various offers, Demand Analysis of New Features and Ideas, and so on. Organisations also generate considerable knowledge during product or service design and development cycle. Many problems come up, and solutions are discussed, and one of them is adopted. But this knowledge of problem solving is not digested for future benefit. The process of product & service design and development exposes a number of the facets of the market, applications, customers, and new business opportunities. This knowledge is potentially a source for creativity and innovation. It can be used to develop user guides, procedure manuals, online databases and new product ideas. Some of this knowledge can be embedded into the system or product itself. Its main and major sources are user interviews, prototype results and modifications, application experience, quality audits, customer help desks, noting in service diary during warranty/ guarantee period, test marketing and all such customer focused activities.

Process Knowledge The manufacturing and servicing processes are critical to business success of a business. These processes are designed to serve the customer better. They are audited and improved continually for small gains and reengineered for radical improvements. During the process operations data and information are captured which generate knowledge about process efficiency and effectiveness, a driver for process innovation. The processes are designed with specific goal in mind. The process definition and various stages are designed to operate and perform in a predetermined manner. As the process is used over time, it undergoes a change for meeting new demands. Many times, certain exceptions are handled by making temporary modifications within rules or policies. This continuous modification of the process generates a process knowledge which should be captured and stored for searching creative new ideas. You may study the loan processing system of any bank, designed to handle many interconnected and interdependent processes for deciding about the loan request from the customer. Every proposal, on analysis, would reveal that the bank has to learn a lot.

People Knowledge The people in the organisation are the only live sensitive resource. They possess knowledge mostly tacit, generated out of experience and learning during the course of execution of plans and strategies. The learning cycle has four stages: plan, act, observe, and reflect’. The plan, the first stage, includes thinking, conceptualising, strategising, and devising a set of actions to implement strategies. The act stage stipulates execution of various actions stated in a plan. The third phase is Observe in which people make intelligent observations on the operations, methods and practices evolved over a period. The key observations are the learning, such as dos and don’ts, right and wrong, choices of tools and technology, methods and materials,

and so on. The reflect is the last phase in the learning cycle. In this phase, people reflect upon what they have learned and how it can be used in practice. The people develop formal or informal networks, communities to exchange ideas, solutions and practices developed out of learning and experience in the organisation. Certain individuals, dedicated teams and experts’ in the organisation are the custodians of this knowledge. They should be identified and knowledge management systems be designed to capture the knowledge systematically.

Organisation Knowledge Database The knowledge database is a repository of most important knowledge of the organisation stored for access to all those who need it. The knowledge here is not the one defined, but is the one which, in general parlance, is required by all. The examples are customer histories, best practices, product history, vendor experiences, case histories, problem and solution instances, Yellow pages for the organisation, Blue pages providing access to external contacts, project reviews, and project closure reports, and so on. These repositories are of explicit knowledge. The organisations which operate in very complex customer intensive businesses, like banking, insurance, tourism hospitality, airlines, and similar businesses, develop organisation knowledge domain specific data bases for guidance and for solving the problems of exceptional nature.

Knowledge in Stakeholders Relationship During the course of business execution, the organisation builds relationships with vendors, customers, business partners, and stakeholders. Each relationship begins by engaging them in some business transaction. This relationship then develops into thick relationship because of common business interest. Further, this relationship strengthens as both are always in a win-win situation in their respective business. Due to this relationship both step out and share knowledge, ideas and information. The organisations build a relationship database which explicitly states the nature of relationship, the knowledge about each others’ competencies, the expertise for which the partner is recognised, the partners’ value systems etc. The database in summary describes the partner relationship with the organisation.

Technology and Sciences Technology and sciences are great sources of knowledge generation. Engineering, electrical, and electronic technologies and material sciences are sources of knowledge giving ideas for innovation. In recent past, Internet and chip technology has brought about a revolution in how the business is done. It has affected and our personal and professional lives. Figure 2.8 shows the strategic sources of knowledge leading to generation of knowledge assets and products. Figure 2.9 shows the link between knowledge, creative and innovation cycles. The knowledge cycle is about creation of knowledge. In creative cycle, knowledge in the organisation inspires people to imagine new ideas for transformation, or for solving the problem. Knowledge is also used to translates idea into practice. All the eight knowledge heads discussed here are the sources of creative ideas and innovation for radical improvement in product, processes and service delivery, which the customer is looking for.

KNOWLEDGE: A STRATEGIC RESOURCE Knowledge which is unique to an organisation and is a clear differentiator, and further puts the organisation ahead of its competitors, is knowledge asset. Knowledge assets are created out of intelligent use of existing knowledge over a period of time. They assets change both in terms of content and value. They are recognised

Product Function

Processes

People

Customer

Requirements Expertise

Capability

Capability Knowledge

Relationship

Competency Knowledge Assets, Products

Stakeholders

Fig. 2.8

Organisation's Knowledge

Strategic Sources of Knowledge for Creativity and Innovation Identify

Inspiration

Create

Deploy

Validate Knowledge Cycle: Knowledge Creation

Fig. 2.9

Technology

Define

Imagination

Formulate Creative Cycle: Idea Generation

Think

Visualise

Practice

Design Innovation Cycle: Idea Implementation

Links between Knowledge, Creativity and Innovation

as the capital of tremendous financial value to the organisation. These assets, also known as intellectual asset can be put into three categories, as suggested by Sveiby, Saint Onge and Bontis. • Human Capital Individuals or groups possessing competencies, skills, experience, know how, intelligence and wisdom. It is invaluable and difficult to code and share. • Structural Capital It is embedded in the organisation’s infrastructure, such as critical processes, knowledge products exclusively developed by the organisation, information systems, KMS, LMS and proprietary databases. This knowledge remains in the organisation even though the people who created it leave the organisation. • Brands, Trademarks, Patents These are the capital assets on which business is leveraged. They together are knowledge bodies which are legally protected and are the prize possession of the organisation. All three are largely intangible and are, therefore, difficult to measure and value. Knowledge assets probably the most valuable assets leveraged to develop innovative business strategies. Therefore, knowledge is considered as a knowledge resource.

In today’s competitive business, business strategy needs to be the result of knowledge input developed for achievement of business goals, i.e., for implementation of a successful business strategy and creation of sustainable competitive advantages, a consistent knowledge strategy is necessary. Of all the resources, knowledge is the resource which cannot be easily copied by competitors, be it material processing, design, feature, knowledge products, heuristics, or any ther. The knowledge and know how, by definition are experience and application skills which cannot be easily copied as they are either legally protected or not easy to implement unless people are trained in application. Knowledge, therefore, is a strategic resource of high economic value. Further, ability to identify such knowledge and acquire it after validation is a higher order skill. Some of it may be such that cannot be easily structured and coded for storage and transfered for sharing. Use of such knowledge for building knowledge strategy, to support business strategy, is advantageous. Such knowledge would turn out to be sustainable, and would create sustainable advantage for the organisation. Sustainable advantage is also realised when the organisation knowledge in many spheres is more than that of the competition. And organisation knowledge has clear linkage to business strategy, its development and implementation. The sustainability is ensured for following reasons. • Knowledge may be declared as intellectual property, prohibiting its use in any manner. • Knowledge, being organisation specific, may not easily be used by competition, as it may not be consistent with their business strategy. • The competitors do not get first use advantage of knowledge, and they lag behind in creation of competitive knowledge and knowledge strategy. • The financial implications of knowledge identification and acquiring it by some means may not turn out to be attractive to competition. • The lead organisation which develops competitive advantage based on exhaustive research learns more about it by the learning experience, and improves its quality over time, leaving competitors way behind. • The organisations which spend intelligent HR resources in studies in technology direction, and in disruptive technologies that could substitute their product get the lead time advantage in developing knowledge to build business mapping, classifying, organising into a form which easily usable. The competition would take extra time in this exercise after identification of the knowledge. • The first advantage knowledge organisation also builds an early warning/alert system as a signal to move forward when the current knowledge and its learning experience begins to lose its sustainable advantage. It is an indication that the organisation should take a fresh look at its current knowledge portfolio to avoid some strategic advantages due to new challenges in the industry. • The organisation may have taken a lead in establishing alliances with the business partners whose knowledge and experience are beneficial to the organisation. The competition would not have such advantage over the organisation. • The organisation has a real threat from new entrants who come with altogether new technology products with production processes also based on new technology. One example is that organisation with digital imaging technology have replaced those with analog technology. Calculators have been replaced by laptops. Storage media has changed from disk to pen drive. Entertainment industry is changing at a heart breaking speed, music systems and home theatre are examples of businesses where knowledge of science and computer technology have made a significant impact on business strategy.

In essence, organisations should begin with SWOT analysis, compare organisation’s knowledge with that of competition, and proceed to find the knowledge gap and identify new knowledge needs to meet competition challenges. Knowledge so created would offer sustainable competitive advantage, as the organisation would have lead advantage over competition. Hence, knowledge is a strategic resource useful for building knowledge strategy. When we talk of competition, we must also identify the factors of competition. First competes on price, second on quality, third on service, and so on. It is therefore necessary for the organisation to position itself on competition strategy framework and launch knowledge initiative. For example, in India, oil and petroleum companies are competing with each other under the price regulation authority.

BUSINESS BENEFITS OF KNOWLEDGE Many organisations are using technology to realise the benefits of knowledge. The systematic approach to knowledge initiative and its implementation gives the following benefits. • Mistakes impacting business are largely avoided Knowledge, essentially an experience and learning gathered over a period, makes the decision maker smarter. More of his decisions to be right. The adverse impact of a wrong decision is eliminated. • Faster proactive response to emerging scenario Business environment changes continuously and throws up new problems demanding quick resolution or faster response. Knowledge driven workers, decision makers, empowered by the knowledge, get better insight of the problem and evolve knowledge driven strategies to solve it. The speed of problem solving is faster. • Process improvements Knowledge initiative includes creation of communities of practices. These communities meet very often to share their knowledge about the processes. This process knowledge sharing gives new ideas for process improvements. Hence, the processes become efficient and cost effective. • Strategic management improved In competitive business, strategies play a significant role in taking the business forward. The key to success is how sound the business strategies are. Knowledge and BI give extra support to the top management for strategic thinking and designing of strategies. Essentially, knowledge gives better understanding of threats, risks and their impacts. It also provides ability to formulate strategies which put the business on the right path and in the right direction. Knowledge driven strategies enable the management to maintain competitive necessities and competitive advantages. • Opens door for new business opportunities The knowledge of customer, product and services, and perceived needs built out of knowledge, triggers ideas for new business opportunities. It suggests new initiatives and creative, innovative strategies. The DELL business model, which enables the customer to configure his own computer system, opened the door for new business opportunity over and above selling of the standard configuration of computer systems. The knowledge of internet capabilities and importance of access to information opened the door for new business opportunity, E-Business and E-Commerce. • Enhances customer satisfaction The knowledge about the customer needs which are not articulated in the specification document, if delivered, enhance customer satisfaction. For example, when a refrigerator is sold to a customer, the organisation is fulfilling the customer needs for cooling, preservation, storage convenience, etc. These needs are articulated by the customer and the organisation’s R&D designs and delivers these needs. But, in addition to this, the customer looks for usage comfort and convenience of the refrigerator. When the customer gets answers to FAQs,

procedural guidance to handle sudden stoppage of the cooling system and contact details of nearest service centre, customer satisfaction is enhanced considerably. • Contains business risk at all levels Managing risks in today’s competitive environment, is an absolute necessity. Knowledge about vendors, technology customers and further knowledge about trends in business, economy and technology facilitate identification of risks and the risk exposure the organisation is likely to face. The same knowledge helps in developing risk management strategies and preparing a risk mitigation plan. • Creates flat and lean organisation The knowledge driven organisations are found to be flat in structure and lean in number. Traditional structure is built on the reality that people have knowledge and workers should seek knowledge from their seniors. It is built on the command and control principle of working. Now, in the new era, knowledge is identified and stored in databases and people can access it and use it in the manner they like. With this advancement, people holding positions for exclusive possession of the knowledge have become redundant. Hence, during restructuring and downsizing of the business their exit from the organisation became inevitable. This reduced the layers in the organisation structure, making it flat. With knowledge repositories and ease of access, two things have happened. Knowledge is now embedded in the systems and processes, making them smart and intelligent, that is, they take decisions and act as well. Hence, people at the level of supervisors, line managers and assistants are no longer required. This impact of knowledge in the organisation has affected the numerical strength of the human resource, making it a lean organisation.

TOOLS FOR KNOWLEDGE MANAGEMENT There are a number of tools—web enabled and IT driven traditional tools—which form the backbone of knowledge search and subsequently its management. These are support tools, or enablers, or drivers, to manage knowledge initiative. In this section, we are taking an overview of these tools to appreciate their importance and application in knowledge management. Detailed discussion is held in the chapter on technology. • DBMS Tools In the process of KM, large amount of data needs to be accessed from several sources, which include documents, folders, files, organisation’s databases working for MIS and Enterprise software. The process of identification of the knowledge and data required to build needs access to these sources. On accessing the data, its down loading and processing to create Knowledge requires a variety of tools. These tools are capable of searching, accessing, cleansing, manipulating, structuring and storing in the required format. They are broadly called data management tools and Database creation tools. • Process Management Tools These tools include process modeling and diagramming tools. In the KM initiative phase, are needs to study critical business processes, production and transaction, which are, by themselves, knowledge repositories. These processes are evolved over a period, out of experience in using them. The study of these processes require modeling tools for process abstraction, for benchmarking and for setting the target, diagramming for details, and then for reengineering and process analysis. • Workflow Management Tools Workflow management tools focus on management of documents, content management on the trail of work centres. Different people in the organisation contribute to work flow by sharing their specific expertise for completion of process. These tools are capable of handling the multimedia used in work flow. In KM processes, development and application, work flow management tools are used for design and implementation.

• Enterprise Software (ERP/SCM/CRM) These software packages are tools for managing resources, supply capabilities, and relations with customers and business partners. These packages, in the execution process, develop knowledge which is not systematically recorded or designed to store. The databases, files and folders of these packages have a hidden knowledge. The enterprise software are implemented using best practices of executing a task, which is knowledge for others to use. The knowledge is then extracted by data management tools and process mapping tools. • Agent Tools Agent tools are autonomous programs designed to perform a specific task. Agents can be designed to search information based on supporting input data specification. Intelligent agents will be able to handle context relevant information seeking. These embedded in the system will offload the work put in by knowledge workers to seek information and knowledge from the repositories. • Search Engines Search engines are designed to search information based on search inputs given to the engine. Some search engines are generic and customised to specific domain. • Collaborative Tools Collaborative working for knowledge sharing is a necessity. These tools help in setting up bulletin boards, real time video conferencing and chat sessions are some examples of collaborative tools. The growth theory of Romer is dependent on advance of what is referred to as economically useful knowledge and crucial role of human resources. It is further said that wider diffusion of skills and knowledge would boost productivity, creativity and innovation, impacting growth of the organisation and the nation. Therefore, knowledge is growth.

End Notes • Which is the easiest way to understand Knowledge? Is to know what it is not. We use words like data, information and knowledge without bothering about the precise meaning. Their use is not very precise, they are used interchangeably. • Data represents discrete, objective facts about events. It says nothing about its own importance or relevance. It could be a number, images, words or sounds whose existence has no context. Data does not represent anything, it is a lifeless entity. It does not evoke any mental response, hence cannot be interpreted. It is defined as raw number, images, words or sounds which are derived from observation, or measurement, or processing. • When data is represented with context, it has some meaning. Information is data that is organised in a way that makes it useful for an end-user to make decisions. It represents something. It evokes some mental response. The set ‘6 9 1938’ when mentioned as ‘dd mm yy’ becomes a date. If it is further supplemented as day of birth it becomes a birth date. Information has specifications of some entity. Hence, it represents that entity meaningfully. Information has some intellectual input making it more responsive to the reader or the viewer. • The human learning process is a long one, squarely dependent on individuals and their intrinsic abilities to view the situations from different angles and connect conceptual constructs to resolve the problem situation. When lessons become more valid for application and provide confirmed problem– solution relationship, the body of lessons become knowledge. This may be tacit or explicit, and may belong to any class. • Information, when processed analytically in some context, starts giving a meaning of substantial value. The value could be due to the fact that analysis shows some pattern, trend or cause-effect





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relationship among variables. It helps, with great certainty, to interpret, forecast or predict the events or results in the future. This is then called knowledge. Knowledge in the organisation exists at various locations in different form. Some is easily accessible and some is not. In every organisation, people are the basic source of knowledge. They develop knowledge out of experience which they get during working. Knowledge may be static or explicit but it takes shape in the human mind. Then, as it gets defined and developed, it gets stored in files, databases, project reports of R&D projects. Knowledge is the fact or condition of knowing something with familiarity gained through experience or association. It is a set of information which together provides capability to understand, differentiate and view situations in different perspective, and further enables to anticipate its implications, judges their effects and suggests ways or clues to handle the situations. Knowledge awareness benefits the entire organisation in creating sustainable competitive advantage, higher productivity and added value to the customer. Knowledge, irrespective of its type, kind class and philosophy, provides an opportunity to grow fast, beat the competition and create sustainable competitive advantage. It may enable organisation to become lean and cost effective, and deliver high customer value. Knowledge, therefore, is a mother of creativity and innovation. Knowledge which is unique to the organisation, is a clear differentiator and further puts the organization ahead of its competitors, is the knowledge asset. The knowledge assets are created out of intelligent use of existing knowledge over a period of time. The assets change both in terms of content and value. It is recognized as a capital of tremendous financial value of the organisation. There are two thrust approaches in launching knowledge initiative—knowing what you have and what you know, and searching knowledge which you do not know. In this initiative, you have determined what knowledge the organisation should have. The initiative focuses on KM cycle to identify, search, acquire or create, organise and store to transfer or share in the organisation. Business intelligence is a set of concepts, methods and processes to improve business decisions using information from multiple sources and applying experience and assumptions to develop an accurate understanding of business dynamics. Business intelligence is a combination of methods and processes with tools to extract information from various sources. The power of business intelligence actually relies on the knowledge acquired through the analysis of various reports taken using business intelligence reporting tools. Business Intelligence Reporting Tools, or OLAP Tools, provide different views of data by pivoting or rotating the data across several dimensions. BI tools are capable of displaying data in several formats, like tables, pivots, charts, query results or reports. Knowledge, on creation, can be put in two types, tacit and explicit. Explicit knowledge is objective and context independent, and can be coded for its management. In contrast, tacit knowledge is subjective, context specific and cannot be coded by any means. Tacit is personal while explicit is impersonal. Knowledge, tacit or explicit, builds capability, the understanding that enables to envision different ways of handling situations, anticipate its implications and its impact on the environment. Explicit knowledge can be articulated into formal language text, mathematical expressions, specifications, manuals, etc. Explicit knowledge, in electronic media, can be readily transmitted







• •







to others. Also, it can easily be processed by a computer, transmitted electronically or stored in databases. Tacit knowledge is embedded in individual experience and involves intangible factors, such as personal beliefs, perspective and the value system. Tacit knowledge, unlike explicit knowledge, is hard to articulate with formal language. It contains subjective insights, intuitions and hunches, conceptual models of solutions. In addition, there are two dimensions to tacit knowledge. Explicit or tacit knowledge can be transferred to share, expand, and for enrichment. Transfer of Tacit Knowledge through: • Internal consultants • Personnel transfer • On-line job training • Conferencing, brain storming • Demonstrating Transfer of Explicit Knowledge through: • Rules, procedures and directions • Seminars, workshops and presentations • Manuals, templates • Models, diagrams, drawings, images Workplace knowledge evolves out of practice and experience. Day-by-day, it is enriched, becoming more useful. The owner of workplace knowledge could be an individual or a work group. Work place knowledge is generally, task oriented and is used to make binary decisions, such as ‘go no go’ or yes or no. There is a fair amount of correlation between task and knowledge. The task at the core is same but has a variable component which requires workplace knowledge to handle it effectively. Business management knowledge can be described as a body of knowledge which identifies the problem proactively, suggests solution ideas, enables modeling of the problem and helps to solve it through various approaches of problem solving. Top management’s job is to view the business ‘outside – in’ and evolve strategies to meet the challenges of the continuously changing business environment. To handle these responsibilities, top management needs, over and above the business management knowledge, a set of body knowledge which is unique to the organisation. It is perceived as a differentiator. Such knowledge is, in most cases, an intellectual property, some of it is patented and rest is knowledge asset. This knowledge is predominantly used for strategic management of the business. In knowledge driven organisation, people are constantly in the learning mode to upgrade their knowledge. The chances are very bright that people come out with new path breaking ideas and are able to translate them innovatively into product, process, and feature. Creativity is the phase in which ideas emerge and, in innovation; ideas get converted into practice. Creativity is the result of knowledge application to search an idea which will transform or radically change the present scenario. Knowledge makes innovation faster and better. Idea is a conceptual model of the solution developed out of kowledge. It germinates out of tacit and explicit knowledge. Throughout the process of creativity and innovation, knowledge continually moves from tacit to explicit and qualitatively improves all the time.

• Knowledge which is unique to the organisation, is a clear differentiator and further puts the organisation ahead of its competitors is asset of the organisation. Knowledge assets are created out of intelligent use of existing knowledge over a period of time. The assets change both in terms of content and value. Knowledge assets are intellectual capital tremendous financial value to the organisation. • Knowledge is a self perpetuating asset with two key features: it cannot be divided; it can be parceled but the whole remains intact; it cannot be destroyed; it can become obsolete or irrelevant. • Knowledge generation and exploitation are not uniformly distributed with obvious implications for networking and regional economics. Knowledge propels economic efficiency and, at the same time, creates differences. • Knowledge can only be valued through its application. Exclusive holding of knowledge creates economic and social advantages. Peter F. Drucker wrote a decade ago that center of gravity in HR employment would be moving from manual intelligent workers to knowledgeable smart workers, who resist the conventional ‘Command-andcontrol’ model. And the organisation to remain competitive or even to survive will have to convert into organisation of knowledgeable specialists.

Questions 1. Build two illustrations from your experience which clearly distinguish data, information and knowledge. 2. In your area of work or function responsibility, identify tasks oriented decisions, business decisions and Strategic decisions. List the knowledge requirements in each case. 3. In following business scenarios identify out of eight knowledge areas which knowledge (S) are critical for superior performance. • Retail mega store • Main reception desk at the hospital • Food court with home delivery • Auto manufacturing/assembly line • Airlines check-in-counter • Retail banking: loan servicing • Hospital: OPD • Post graduate institution in management 4. Identify BI components in following organisations • City Police Department • National Chemical Laboratory (R&D) • ICICI Bank • Maruti Udyog Ltd. • Department of HR in an organisation • Idea Cellular

5. Which of the following knowledge sources is your organisation relying upon? • Market research • Prototypes & their outcomes • Quality audits • Customer feedback • Help desks • Test marketing results • Product/ service requirement analysis • Customer interactions 6. How is the knowledge discovered from these sources used and shared? • Embedded in products/services • Developed user guides • Procedure manuals • Created knowledge databases • Embedded in the process • Posted on knowledge portal 7. As an individual in the organisation • Are you a member of an interest group? • Are you a member of a professional association? • Do you make systematic noting and record of knowledge discovered out of interaction with colleagues, customers and/or vendors? • Have you developed knowledge based decision rules, and have they embedded into the system? • Have you built a formal/informal network of your kind of professionals in the organisation? • If yes, what benefits you are getting from this initiative? 8. In your organisation, identify the following: • Knowledge assets • Knowledge, which can be coded into an E-manual • Identify product, process and customer knowledge • Experts, specialists, professionals who possess tacit knowledge • How would you bring them together to discover knowledge? 9. Explain the following terms. • Data driven organisation • Information driven organisation • Knowledge driven organisation • Learning organisation • Knowledge worker • Knowledge assets • Intellectual capital

10. In your profession and in career development, can you recall experiences, cases and events where prior knowledge made a difference and no knowledge made an adverse impact on performance? 11. What type of knowledge is used in each of the activity? • Testing a computer program • Sanctioning a car loan of small amount • Reducing engine noise • Credit rating by a credit rating agency • Credit card agencies sending a SMS or a reminder selectively • Declaring a service delay to a customer in a Pizza Hut restaurant • Security check before entering into the lounge 12. Explain in one sentence the following terms: • Knowledge • Information • Intelligence • Heuristics • Learning by doing • Learning by example • Learning by experience 13. An organisation represents its knowledge in the following ways. • Case study • Model • Semantic representation • Case analysis • Knowledge product Explain the care that should be taken while adopting this knowledge for application. 14. Explain the following terms with examples. • Human learning • Simulation as a learning method • Learning by experience • Declarative knowledge • Intelligence 15. Correct the following statements and explain your correction. • After KMS implementation, users would stop using data and information for decision making. • Knowledge needs no validation and mapping to the problem solution. • There is no need to link knowledge to strategy. • KM initiative need not begin till competition pressure is on. • If the required technology platform is in place KMS will be successful.

16. What type of knowledge would you use in the following situations? • Starting desktop computer system • Investigating frequent machine stoppage • Sudden increase in customer complaints in one product feature 17. Develop a Dimensional Model for the following: • Customer request for enhancement of credit limit • Decision on making the vendor an alliance partner • Investigating absenteeism of certain employee 18. One of the characters of explicit knowledge is that it is compressible. Give an example of each of the following. • Model • Equation(S) • Diagrams: 2D, 3D • Process diagram • Knowledge product 19. Knowledge asset, also known as intellectual asset, can be put into three categories, as suggested by Sveiby, Saint Onge and Bontis • Human capital • Structural capital • Brands, trademarks, patents Identify at least two Indian & International companies in each of the knowledge capital areas marked above. 20. Assume you are a project manager in an IT enabled services company. You are controlling two major accounts, a Bank and a Hospital. Explain how you would use KM function to improve your performance.

3

Chapter

Management (Process, Life cycle, Business case, Models and Networking)

This Chapter Deals with • • • • • • • • • • •

Knowledge Management Why Knowledge Management Now? Knowledge Initiative Knowledge Management Process Knowledge Development and Management Cycle Knowledge Networking Principles behind KM Success Thematic Analysis of Knowledge Management Knowledge Transformation and its Dynamics SECI Model and DKCU System Business Case for Knowledge Management, Alber’s Framework

Learning Outcome You will appreciate the importance of KM in today’s competitive world of business. You will realise that the success of KM depends upon successful implementation of the knowledge initiative and installation of the knowledge networking platform. You will know the principles to be observed and the barriers to be overcome which assure KM’s success. You will also get an insight in to the process of knowledge transformation and its dynamics, modeled into SECI model.

“The present KM focus is not driven by commercial pressures alone. A practical, often implicit, aspect of KM is that effective people behaviour required for success rests on delegating intellectual tasks and authority to knowledgeable and empowered individuals” —Karl M. Wiig

KNOWLEDGE MANAGEMENT There are a number of definitions of knowledge management. In essence, all of them are same. Some have been discussed here. Knowledge management is a system’s approach to identify, validate, capture and process knowledge, and then organise the knowledge elements into knowledge assets for business function operations and decision making. Knowledge management is the process of creating economic value from the organisation’s intangible assets, namely human capital, structure capital, customer capital, business partner capital, to be ahead of the competition. Knowledge management is the process of capturing and making use of the organisation’s collective expertise developed out of experience for improving business operations and performance. Knowledge management is the discipline of capturing expertise, competencies and skills and storing in databases in the form and kind for dissemination and application for resolving issues affecting the business and its position in the market. Knowledge management is the process for developing knowledge and knowledge assets to build knowledge strategy, supporting first to build strategy and then its implementation. Knowledge management involves blending a company’s internal and external information and turning it into actionable knowledge via a technology platform. Knowledge is a fluid mix of framed experience, values, contextual information and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of the knower. Figure 3.1 shows the landscape of knowledge management. The landscape consists of technology, consulting and related activities, content generation systems for users of the organisation and knowledge generation processes and systems. Within each of these four overlapping and interdependent contributors there are supporting aids, tools and processes, which result in the overall and landscape making an impacting on the organisation’s business performance.

KEY TERMS • Knowledge Driven Organisation • Knowledge Networking • KM a Strategic Function • Thematic Analysis of Knowledge Management • Four Kinds of Knowledge Assets • Barriers to Knowledge Management • KM Business Case • SECI Model.

68 Knowledge Management Work Culture, HR Expertise, Competencies and Capabilities, Communities of Practices, R & D Search Engine, E-mails, Portals, Website, Intranet, Extranet, Sotware Platform, Network

Consulting, Researching, Experimenting Technology Infrastructure

Content Generation and Management

Knowledge Generation Process

Content Generation and Management Systems and Tools Ontology, User Profiling

Data Warehousing Text Mining, Data Mining, Identification of Knowledge to its Deployment in Business Processes

Fig. 3.1 Knowledgement Landscape

The importance of KM in recent years has risen due to its ability and proactive preparedness to face the challenges of globalisation, competition and knowledge economy. The organisation recognises it as the key result area, a management function affecting the rest of the business management functions. Knowledge management addresses the following problems of the organisation. • Ageing workforce leading to loss of knowledge due to their exit • Mergers and acquisitions disturbing human resource balance • Urgent need of expertise to be fulfilled which is not planned • Lack of resilience in the organisation to face the competition onslaught • Not able to generate economic value out of investment in human capital and technology For knowledge management to be effective, it cannot function in isolation. Its effectiveness increases when KM is linked to vision and business strategy of the organisation. KM function has no independent identity, it needs to be interfaced to business strategy and its implementation.

WHY KNOWLEDGE MANAGEMENT NOW? Before we proceed to discuss KM further, it is necessary to appreciate why KM is so important now. All these years, we talked about information, information driven organisation, and so on. In this century, technology, in general, and information and web technology, in particular, made a paradigm shift in the way business is done. They have changed style, culture, and structure of business management. New business models have emerged. This radical change has made business highly competitive, demanding focus on developing sustainable competitive advantages. Creating sustainable competitive advantages require efficient management of knowledge assets. Figure 3.2(a) and (b) show the shift from information driven organisation to knowledge driven organisation, and the difference in ‘how they are run.’ We use the process of building a production plan for a month to illustrate the point. In the information driven system, decisions and process checks are based on the information available at that point of processing. The Decision Support System (DSS) processes information one after another in the

Order Book

BOM

WIP on the Floor

Inventory

Process Order Book for the Month’ s Production and for MRP

Check Information: Resources, Order book, Inventory WIP, Bill Value Sales Targets for the Month

Optimum Production Plan for maximum Bill value within the constraints and Conditions

(a) Order Book

Inventory

WIP on the Floor

BOM

Process Order Book for the Month for Production Plan and MRP Knowledge

Use knowledge and Business Rules to Select Orders from Order Book, Cost Effective BOM, Prioritising the Selected Orders for Building Production Plan to Achieve Monthly Sales Target

Customer, Price Cost BOM, BOM Mfg. Process

Business Rules for DSS Customer Choice, Order Choice, BOM Choice, Priority Algorithm for Target Achievement

Optimum Production Plan Achieving Production And Performance Targets: Production, Sales, Inventory (b)

Fig. 3.2 (a) Information Driven Process for Preparing a Production Plan (b) Knowledge Driven Process for Building a Production Plan

given example. It processes ‘first order, then order value, then inventory, then capacity’, and so on, to arrive at the final production plan for the month. The process relies on the information as on date for processing and decision making, for the plan preparation to achieve monthly production and billing targets. This approach achieves the monthly targets of bill value, inventory and order fulfillment. However with all information support, optimum use of resources is feasible but the performance of the organisation may take a beating in factors, such as inventory turnover, customer satisfaction and profitability of the business earned. In the knowledge driven organisation, operations targets like bill value, inventory, etc., are achieved simultaneously with performance targets. In the competitive world of business, knowledge is the key for decision making to achieve operations and performance targets. In the knowledge driven approach, the result would be ‘High bill value and delivery to loyal customers, keeping the Price – Cost-Volume relation balance’, assuring the continuity of the business and customer satisfaction. The decisions are supported by knowledge embedded in business rules, decision models, through knowledge driven applications. Figure 3.2 (b) illustrates the knowledge driven process of building a production plan. Another advantage of KM in a knowledge driven organisation is that it enables to generate innovative strategies for growth and improvement. In the knowledge economy like ours, continuous improvement through TQM (Total Quality Management) gives incremental benefits. What is needed is radical dramatic improvement through creative ideas and innovative implementation. Knowledge is an input that generates innovative strategies. Knowledge organisations work on knowledge network platform. Knowledge network is essentially a network of experts, specialists, experienced persons holding tacit and explicit knowledge about the processes, products and people – employees, customers and stake holders. The computer network that connects them enhances their ability to generate knowledge and share it through the network. Most organisations keep their explicit knowledge and some knowledge assets on the network of databases for users to access and use for building strategies and making innovations. HR on the network is the reservoir of creative ideas and their innovative implementation. The knowledge driven innovation cycle that the HR is engaged in shown in Figure 3.3. Create Ideas

Gather Innovation experience Increase Learning, Improve Knowledge, Be More Creative

Knowledge Knowledge Assets Database

Innovate Evaluate Ideas Select One, Configure, Model, Prototype Design, Test

– Transform Prototype into Method, Process, and Practice. – Change Policy, If Required. Put Innovation in Action

Fig. 3.3

Knowledge Driven Innovation Cycle

The knowledge data base includes customer knowledge, competition knowledge, organisation’s product and process knowledge and few more knowledge assets. Assets are triggers for generation of creative ideas to be innovated into practice by implementation. Today’s business needs competitive strategies and competitive advantages. The knowledge driven innovation cycle ensures its creation and implementation. Last and most important is the need of continuing research and improvement in the Knowledge Development Cycle. KM teams should make continuous efforts to gather experience of knowledge users for revalidation and improvement to keep sustained effort in using knowledge for business gains.

Knowledge Management Perspectives During the course of last five years, two perspectives of KM have emerged. • Technology Centered Knowledge Perspective • People Centered Knowledge Perspective The understanding of these perspectives is important as they decide the focus of knowledge management. In case of technology centered perspective, management of technology is the key enabler of KM. In case of people centered knowledge perspective, management of people, the human resource, termed here as a human capital, is the key enabler. The technology centered perspective pertains to IT and IS professionals. These professionals believe that knowledge is the set of information objects that can be coded, stored and shared by all in the organisation. They believe that technology is an enabler and driver of knowledge and, hence, this perspective is better for understanding and implementation of knowledge management initiative. Technology and knowledge together are termed as Business Intelligence. Also, technology centered perspective’s focus is on technology and not on people of the organisation. This perspective considers that technology is the main mover of knowledge and pays less attention to the human factors that make or break a knowledge management effort. This strong belief is out of the fact that knowledge is relatively easy to identify, create and store to share. But if technology is not a powerful support, KM is difficult. The people centered knowledge perspective focuses on people-experts, specialists, practitioners, entrepreneurs, and leaders of the organisation. This perspective gives less weight to the technology and more to human psychology, human development, cognition, organisational behaviour, group dynamics and sociology i.e., human side of the organisation. The human resource development, focusing on development of intellect, management skills and social skills, is the prime mover of the KM initiative. Both initiatives are right and legitimate but in different business scenarios. The businesses where knowledge is predominantly ‘tacit’ should follow the people centric knowledge perspective. The businesses where knowledge needs are clear and knowledge is predominantly ‘explicit’ to embed in the processing and decision making systems, should take technology centered perspective. Whichever may be the perspective, KM cycle, in its components, is broadly the same, ‘creation, validation, aggregation, organisation, share, use and exploitation and revalidation’. The need to manage knowledge as a management function is very strong. The driving forces behind KM are • Globalisation of business: Bigger markets • International competition: Threat to business • Sophisticated customers: Demanding number of requirements together • Sophisticated competitors: Develops products in innovative way in short cycle • Sophisticated suppliers: Offering higher value but, at the same time, cost effective

72 Knowledge Management

• Bottlenecks in organisation’s delivery systems: Delays in delivery to customer • Increased technology intervention: Fulfilling delivery, response and quality needs • Pressure to improve decision making competence: Control on performance

Knowledge Management Benefits KM benefits are spread across the organisation. The benefits are to individuals in improving personal competence and, for the organisation it demonstrates quick responses to new challenges. It becomes a learning organisation possessing knowledge, know how, sustainable competitive advantage. The Wiig models the KM benefit chain in a structure and layers. The model is adapted as shown in Figure 3.4. Access to Knowledge

Creativity and Innovation

Better Products

Faster Processes and DM

Improved Customer Service

Knowledge Share

Better Use of Resources

Better Cost Control

Knowledge Base

Organisation Learning

Better Financials

KM Efforts

KM Outcome

KM Benefits

Knowledge Transfer

Customer Satisfaction

Sustainable Competitive Advantage

Resilient Organisation

Fig. 3.4 KM Efforts, Outcome and Benefits

To explain the tree of benefits, let us take some points of efforts and illustrate them by examples. Access to the customer segment defined as home owners possessing two wheelers, revealed the knowledge of their next requirement. It gave rise to the innovative idea of producing a car in the price range of Rs.1,00,000. It also triggered the design of manufacturing processes which would keep the cost so low as to make the car Rs.1,00,000. The process knowledge of processing various bank loan proposals is shared through knowledge portal, case histories, etc., making loan financing decision very sound. This results into better use of bank credit and controls the cost of loan financing.

KNOWLEDGE INITIATIVE Knowledge initiative is the first step towards KM in the organisation. There are two thrust approaches in launching the knowledge initiative. • Knowing what you have and what you know In this approach, knowledge management life cycle process is used. Identification of knowledge is a non issue as it is already recognised by users as useful knowledge. It needs to be captured, organised and stored for transfer or sharing. The source of this knowledge could be within the organisation or from outside.

• Searching knowledge which you do not know In this initiative, what knowledge the organisation should have is determined and the initiative focuses on the KM cycle to identify, search, acquire or create, organise and store to transfer or share knowledge in the organisation. Ann Macintosh of the Artificial Intelligence Applications Institute (University of Edinburgh) writes in a Position paper on ‘Knowledge Asset Management’ some specific factors which compel the organisation to go for systematic KM initiative to become the creative and innovative knowledge driven organisation. The factors are: • Market places are increasingly becoming competitive because of globalisation. • Rate of innovation is rising, bringing radical changes and dramatic results in business and environment. • Organisations, being lean, require unorganised knowledge to be converted into explicit knowledge available to all concerned. • The technology application in business processes reduces intelligent work force, compelling the management to take knowledge management initiative to capture the knowledge for common good of the organisation. • Experts and specialists are in great demand, a knowledge management initiative is essential to retain the knowledge in the organisation if specialists leave the organisation. • Global competitive environment demands quick proactive responses from the organisation. This is possible if organisations treat KM as an essential function. The result oriented KM initiative is possible if its design is built on the strength of scisence and technology. The successful KM initiative draws strength from wide range of sciences, tools and technologies. Some of them are • Cognitive Psychology, interdisciplinary study of human intelligence and artificial intelligence • Expert systems, AI systems • Groupware for collaborative working in a network environment • Library and information science assisting in classification, categorisation of information and knowledge • Technical writing enabling effective knowledge communication and presentation • Document management systems for content organisation and knowledge search • DSSs, a part of business processes extensively using management science, Operations Research and Systems engineering methods • Extensive use of relational and object data bases for managing information and knowledge from Creation to Delivery and Exploitation • Computer simulation: A tool for establishing the knowledge and its testing for validity and vitality • HR management science for ensuring the involvement, commitment and motivation of HR in KM initiative • Internet and Web technology, use of knowledge portals • Search engines for quick search and access, and then downloading

KM Initiative Implementation There are three approaches to KM initiative implementation. A lot depends on the three main factors, namely type of knowledge, HR, and the organisation structure, for KM to succeed. Approach

Basis of the Approach

Comments

Technology

More explicit knowledge

Cultural/Behavioural

Organisational Behaviour (OB) and culture

– Easy to implement with right technology – HR is tech savvy – People and OB must change first

Systematic

Application of System Engineering (SE)

– Difficult to implement – Knowledge and KM initiative must have SE development approach – Organisation and culture HR has to be supportive

It should be noted that for any approach, appropriate technology is an essential requirement to implement the KM initiative. The objective of knowledge initiative is to develop knowledge strategy which will translate initiative into an action plan to create knowledge for strategic management of business. Knowledge strategy has direct relevance to business strategy. It focuses on a number of key requirements of business strategy, as shown in Figure 3.5. Application, Enrichment of Knowledge

Develops Core Competencies, Competitive Advantages

Knowledge Strategy Focus

Create Intellectual Capital: Human, Structural, Technology

Organisation Learning through Motivation

Fig. 3.5

Knowledge Strategy Focus

The focus should aim at: • Enriching knowledge continuously so that application of knowledge also improves simultaneously • Developing core competencies enabling the organisation to develop competitive advantages • Promoting organisation learning through motivation, elevating organisation’s competence in delivery to customer and meeting the interests of stake holders • Creating human intellectual capital and raising some of it to intellectual property

KNOWLEDGE MANAGEMENT PROCESS Knowledge management, in practical terms, encompasses identifying and organising knowledge and knowledge assets for sharing with knowledge workers to maintain competitive necessities and competitive advantages. It establishes direct link between knowledge assets and superior business performance. One can see a clear reflection of knowledge into business strategy, policy and practices where KM is a recognised function. Knowledge management is considered as a driver and a critical success factor in change management, implementation of best practices and management of business risk through a risk management and mitigation plan. The term knowledge management is an approach to improving organisational outcomes and organisational learning by introducing into the organisation a range of specific processes and practices for identifying and capturing knowledge, know how, expertise and other intellectual capital, and for making such knowledge assets available for transfer and reuse across the organisation. Knowledge management is the explicit and systematic management of vital knowledge—and its associated processes of identification, validation, creation, aggregation, organisation, share, use and exploitation—in pursuit of business objectives. It is a well designed system. Knowledge development begins in an individual’s mind without him being aware of its development. Some knowledge is retained. Some enriches out of its experienced use. The enrichment is out of learning experience gained in the process of knowledge application. Some knowledge is forgotten or not recalled when required. The reason is that it is rarely used and hence it fades out of memory. Also its validity and vitality are now doubtful. In these processes, emphasis is on achieving explicitness in everything through systematic approach in the management of knowledge. The Knowledge Management Cycle is shown in Figure 3.6. It continuously goes through eight steps. The steps in the management cycle are create, aggregate, store, share, use, validate for vitality, enrich or replace. More broader definition is discussed in Chapter 4 and is expanded in Chapters 5 and 6. Aggregate

Organise

Store

Start

Identify, Create

Knowledge Database

Transfer Share

Continue Replace or Enrich Knowledge

Fig. 3.6

Validate for Continuing Vitality

Use and Learn

Knowledge Management Cycle

This management cycle is applicable to both types of knowledge, tacit and explicit. Tacit is highly person driven, limited by the ability of the person to go through these eight steps. Explicit is largely technology

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Knowledge Management

driven once explicitness is defined. Technology plays a significantly critical role in efficient development of knowledge and its application. The definition of KM has four important components which need further elaboration.

Make Knowledge Explicit Attempt is made to make knowledge explicit through coding different knowledge objects and entities. The management process then can be made more focused on these entities and objects. Explicitness can be achieved by putting knowledge in formula, graphics. It can be coded by standard programming languages and represented by UML or Visio diagrams. The explicitness is achieved by developing business rules, models and algorithms. Further, when knowledge becomes explicit, it is understood well and used effectively by application or embedding in the business process or systems. Lastly, it is then highly amenable to use of technology. The entire KM cycle can be designed as a system. Figure 3.7 shows how knowledge in explicit form can be intelligently used in a loan processing application. Start

Check Basic Primary Eligibility Eligibility

Credit Worthiness

Financial Viability

Check Fixed Assets for Mortgage Knowledge Linked Processing

Knowledge Database Rules, Formula, Models, Forecast, Patterns, Trends, Algorithms, Case History

Check EMI Repayment Ability

Decide

Fig. 3.7

Intelligent Use of Knowledge in ‘Explicit’ Form in a Loan Processing Application

Be Systematic The word systematic means that design of KM cycle ensures use of universally accepted standards of methods, processes, procedures and its consistent use in all stages of the cycle. Systematic also means use of recognised good practices. Systematic means thinking is logical and information flow is logical. Such thinking enforces use of generally accepted standards of system development. The advantage of systematic approach is it facilitates automation and embedding of explicit knowledge into process, product or its application in decision making.

In the loan processing application, the relevant knowledge was first identified, and then processed through a development cycle before it was stored for access to users. This development is systematic, as prescribed in the standard method of system development. Because of systematic approach, rules, models, triggers could be developed objectively and explicitly for integration in the loan processing application.

Ensure Valid and Vital Knowledge Knowledge management focuses on ‘vital’ knowledge. This is possible because of systematic approach to KM. In the business management process, there are many new revelations and experiences. All of them necessarily are not qualified for knowledge as they happen to be incidental, or one odd which does not deserve systematic handling through the KM cycle. Knowledge must be critical, and must have confirmed tested application leading to right conclusion. In execution of KM cycle, every knowledge candidate is tested for its vitality for use before it is taken through knowledge processing cycle and declared valid.

An Efficient Process It is a well laid out process which creates, organises, transfers and shares knowledge with the users. It is a cycle where knowledge continuance is audited and its continuity is managed. The process includes other subprocesses, like mapping, coding, measuring valuing for capitalisation. In the loan processing application, when checking the loan request for eligibility, credit worthiness and economic viability, are needs knowledge which is vital in terms of time and application. For example, normally loan proposal from an ITeS company is considered as eligible, creditworthy and economically viable. However, owing to recession, ITeS business is affected adversely. Hence knowledge based rules and models and guidelines developed for this segment are no more vital and valid. The continuous checking of knowledge vitality and validity is critically essential for successful knowledge application.

KNOWLEDGE MANAGEMENT PROCESSES The processes mentioned from ‘creation to use and exploitation’ are very important to ensure that the knowledge which enters into the knowledge database is after due diligence. Hence, these processes, each one of them, have a unique role in the Knowledge Development Cycle. These processes together ensure quality and vitality of knowledge. They tests knowledge before it is used and, if found deficient, it is put in an archive. The process is given below. • Identification Knowledge is not to be searched in isolation of business, business needs. It has to be identified as the relevant so that it is useful to the organisation in its better management. • Creation Includes identification, formulations and recognition of its source and testing for vitality. • Aggregation Means assembling and clustering knowledge entities into one unified set, easy to code, store, share and use. • Organisation This includes structuring knowledge into different organised formats, such as E-manual, Portal, Database and Folder for access to users. • Store Knowledge so generated and organised is stored in structure and format for easy access to share and use. It could be at different locations on the network for various technical reasons and for user requirements. • Share Share is a process which takes care of dissemination of knowledge to users. It includes dissemination and its security.

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• Use Use of the knowledge is at the initiative or choice of the user. The process keeps track and watch on knowledge, and keeps the log of ‘who, when, where’. Such log, at the time of review, reveals the level and quality of usage. This becomes the key for declaring knowledge as ‘vital and valid’. • Validity of Knowledge Knowledge needs validation regularly at some interval to check its utility for which it is created. Such review may not reject knowledge but enrich it by its experienced usage. The process cycle begins with creation and ends in revitalising the knowledge or archiving it before it is rejected. We use the example of loan processing application to explain the KM Cycle.

E-proposals from All Types and Domains

Loan Proposal Processing Application

Knowledge Management System

Approved/Not Approved Proposals

Application Domain Knowledge

Approved and Sanctioned E-Proposals

Customer Knowledge

Loan Disbursement and Management System

Customer Repayment History

Industry Domain Knowledge

Repayment History Knowledge

Shared by Loan Proposal Processors

Knowledge and BI Database for Loan Management System: Rules, Models, DSSs, Case Models, Structured Guidelines

Fig. 3.8

Knowledge Driven Loan Proposal Processing Application

Figure 3.8 shows a KM system diagram of Knowledge Driven Loan Proposal Processing Application of a Bank. In this processing application, loan proposals are processed using knowledge databases, namely Domain, Customer, and Customer Repayment Performance, Case History and Learning. During the processing of proposals, each knowledge database supports a number of decision making steps. After completing this processing, the proposal is subjected to scrutiny by knowledge database of exclusively developed business rules, models, and guidelines, etc. In this cycle, the KM process continuously creates explicit knowledge through knowledge processing cycle so that the current knowledge in Data Base is vital and loan sanctioning decisions are economically viable with little or no risk of becoming bad debts.

When KM initiative is successfully launched and put into practice, the KM focus changes as per the needs of the organisation. Some focus and on sharing and application as knowledge creation is relatively easy. KM systems focus changes depending on the character of the system. In the KM cycle focus may be more on identification and generation, or on technology or on information processing as it is a demand of the system. Some focus on technology which drives this intivative of generation of knowledge and its distribution to far end corner. Some KM systems focus on inout side of the systems and strengthen information management systems support to KM. Where knowledge is the key and critical driver directly linked to strategy, creativity and innovation, the focus is on utilisation of knowledge for leveraging to produce sustainable competitive advantages. So, the broad definition of KM is the systematic and explicit management of knowledge related activities, practices, programme and policies within the organisation to produce competitive quality of knowledge and its efficient and effective application in business management.

KNOWLEDGE DEVELOPMENT AND MANAGEMENT CYCLE For convenience of understanding, KM cycle is split in two cycles, working closely with each other. Knowledge is developed first, and then it is managed for effective use. Hence, the two cycles are Knowledge Development and Knowledge Management. Knowledge Development (KD) Cycle The KD cycle is about search, identification, validation and creation of knowledge. In this cycle, appropriate required knowledge is determined identified, searched, created and stored for handling, storing and transferring to users for application in decision making. Knowledge Management (KM) Cycle KM cycle moves through four main phases, each having specific activities. The KM cycle deals with the process of capturing and organising knowledge to transfer it to users, sharing and effective use. It measures the knowledge performance and evaluates for its continuity in the organisation. Figure 3.9 gives the process flow details of KD and KM cycles. Capturing Data Entry, Scanning, Voice Recording Interviewing, Brain Storming

Transferring to Users, Alerting the Users, Embedding in Process Transferring, Moving to Users

Fig. 3.9

KD and KM Cycles

KM cycle

Organising Cataloging, Indexing, Filtering, Linking, Codifying

KD Cycle • Search • Identity • Validate • Create • Store

Application Contextualising, Compacting, Productising, Mining Refining, Making Sense

Key challenges in dealing with these two cycles are many. They need to be understood for successful KM initiative in the organisation. Challange 1 Moving people from information driven processes to knowledge driven processes. Most of the decision makers lack trust in the knowledge developed through the KD cycle. The privilege and power which was enjoyed by them using their experience is now in public domain. The concept of knowledge sharing and collaborating with fellow knowledge workers is difficult to digest. Challenge 2 The most difficult challenge is to create trust in tacit knowledge. Tacit knowledge comes from very few in the organisation who have demonstrated skills of using their experienced knowledge in problem solving. All are not ready to accept the supremacy of somebody while using tacit knowledge. People take time to deal with this knowledge. Challenge 3 It takes time and effort to sell KM in the organisation when it is handled by a separate knowledge management function, headed by a Chief Knowledge Officer (CKO). Only time can prove its utility in the organisation. Making a good case for KM is the solution. Challenge 4 Knowledge users believe that KM is a technology, and unless one is a master in the technology success is doubtful. Actually, technology is an enabler and not the soul of KM. Over a period, this misbelief with experience is wiped out. Challenge 5 Sufficient time needs to be given to knowledge workers to develop practice of using stored knowledge, knowledge assets and knowledge products. This challenge can be overcome if knowledge repositories also provide guidance to users in using knowledge. This is actually a confidence building measure. Challenge 6 Another difficult challenge is to prepare the organisation in technology to take up the challenge of paradigm shift from being information driven to being knowledge driven. Four main technology implementations are Intranet, Videoconferencing facility and Groupware technology, for coordination and collaboration, and Knowledge portal. Challenge 7 Changing traditional individual work culture to work group culture is the toughest challenge amongst all stated so far. This can be overcome by training the people first in technology and then in team work for achieving enhanced productivity. Challenge 8 The challenge is convincing people about collaboration as a tool for innovation. The real benefit of Groupware technology is the collaboration it promotes among people leading to higher productivity, process efficiency and innovation. Challenge 9 Changing the mindset of key personnel (experts and specialists) to share their tacit as well as explicit knowledge for organisation’s well being. This challenge can be overcome by introducing appropriate recognition and reward systems in the organisation for wilfully sharing knowledge. The organisation should encourage formation of Community of Practice (COPs) and Common Interest Groups, facilitating the exchange of knowledge and ideas. Challenge 10 The last and the most important challenge is the need of continuing research and improvement in Knowledge Development Cycle. KM teams should make continuous efforts to gather experience of knowledge users for revalidation and improvement, to keep up sustained efforts in using knowledge for business gains.

Knowledge Management (KM) Cycle There is a three steps approach to knowledge management. It moves through three phase cycle before it is integrated into systems and processes of the organisation.

Knowledge Management 81

• Knowledge Definition (Identification, Validation): Recognition of knowledge utility and validating for application. • Knowledge Generation (Creation, Acquisition): Knowledge creation by self and acquiring from other reliable sources external to organisation. • Knowledge Application (Measurement, Archiving): Measuring knowledge for its performance and validating it for continuity, and learning more lessons to enrich the knowledge. Infrequent use of knowledge is taken to archive. A matured knowledge is then attempted to be integrated into systems and processes where it is frequently used. Integration is done through business rules, models and algorithms formulae, and so on.Within the KM cycle, there are four cycles closely linked to each other. The cycles are ‘Data, Information and Knowledge and Application’. Figure 3.10 shows the four cycles. Identify Source

Store Data

Choose Data and Context

Capture Data

Data Cycle

Process, Validate

Process Data

Information Cycle

Store Information

Produce Information

Share and Acquire

Choose Information Use

Application Cycle Enrich, Replace

Fig. 3.10

Knowledge discovery Cycle

Store and Share Knowledge Learn

Process Information for Knowledge Identification

Validate Knowledge

Data, Information, Knowledge, Application Cycles

In the data cycle, data is identified for business relevance along with its Metadata. Then it is processed for correctness, completeness, and is cleansed and organised for data processing application. This processed data is then stored in Database. In the information cycle, data is chosen with context and its purpose in mind, and is processed for contextual relevance and reference. Such processed data represents the context and entities fully. It may also have some surprise element, and it evokes response to think and act. Such information is then stored for application. In the knowledge cycle, the stored information is chosen for processing with some objective. When such information set is processed for discovering insight, trend, pattern, cause and effect relation, the result is ‘knowledge’. In the application cycle, knowledge is put to use directly or through embedded, integrated systems. The application experience enriches knowledge. In some cases, new knowledge is found. New knowledge could be tacit or explicit. All four cycles operate on the Network of the organisation, generally known as knowledge network.

KNOWLEDGE NETWORKING The KM cycle developed for the organisation operates on the network platform. KM network platform has two components, Computer Network and the people from the organisation and outside. In knowledge network, people share information, knowledge and experiences to develop new knowledge and new knowledge assets. Charles Savage, author of Fifth Generation Management, first brought out the term ‘Knowledge Networking’. It is a product of two concepts—knowledge, a strategic resource, and networking, a human act of building relationships. Charles Savage defines knowledge networking as the process of combining and recombining one another’s knowledge, experiences, skills, capabilities and aspirations in ever changing profitable patterns.’ Table 3.1 shows the key characteristics of Knowledge Network. Table 3.1 Characteristics of Knowledge Network

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Network Particulars

Description

Network Components Links Node Pattern Network Character Role of Individual, Team or Group Network Boundary Interaction between Nodes. Strength of Link Use of Links

Nodes and links Channels of Communication Sharing knowledge, Build relationships Individuals, teams or groups Centre of processing activity Network pattern changes depending on nodes in context and knowledge Circular or diffused and hub and spokes Belong to different network and role Central directive or supportive Not fixed, nodes may enter and exit Multiple as well as one to one Depends on usage intensity Knowledge flow

Knowledge networks bring many benefits. The degree of benefits varies with how static or dynamic the network is. Networking allows uninterrupted flow of knowledge and rapid access to its storage place. The knowledge movement through different nodes makes it richer by its experience of application to solve problems. In the process of flow of knowledge, users get creative ideas and innovative solutions to solve the problems. Knowledge network provides a common platform to the users to solve the problems, get better insight, and generate new ideas and strategies. The second best benefit of knowledge network is that it facilitates building relationships between network partners leading to collaborative working on many other issues requiring immediate attention and resolution. Knowledge networks are driven by knowledge workers. The success of knowledge management depends on how good the knowledge workers are. In the knowledge driven organisation, it is virtual working with information and knowledge. The character of a good knowledge worker can be summarised as under. • Proactive and willing to act beyond given role and scope • Motivated to enter into other’s domain to seek additional knowledge • Effective team worker: shares knowledge, collaborates and contributes • Leads to set the goals, achieve consensus among team members • Has broader perspective and wider context. Sees the bigger picture • Finds way through people, policy and politics in the organisation

The knowledge workers with these characteristics are efficient and effective. They work smarter, not harder. Figure 3.11 shows the meaning of efficiency and effectiveness (Source: Dr D.B. Farbey, adapted from the Audit Commission). The knowledge workers focus on the outcome of the efforts they put in. Inputs (Resources)

Outputs (Quality)

Efficiency/Productivity

Fig. 3.11

Outcome (Results, Impact)

Effectiveness/Performance

The Meaning of Efficiency and Effectiveness

PRINCIPLES BEHIND KM SUCCESS KM is a Discipline KM is a discipline because it is a systematic approach to discover knowledge for the development of the organisation’s business strategy and its effective implementation by innovative strategies. The discovery process goes through a well defined cycle starting from creation and then aggregation, organisation, share, use and exploitation. The strict adherence to this cycle is the indication of the discipline. Further, every knowledge or knowledge asset is under surveillance to establish its continuing utility to the organisation. There is a systematic way of archiving the knowledge which is not used for a long time. KM also includes a process which confirms that the knowledge in database is valid even though the environment has changed. The KM process, by default, has a process to upgrade and enrich knowledge by the experience of its usage. It continuously ensures that knowledge in the database is current and useful. All the steps and processes are well defined and fall in line when the cycle begins its execution. In short, it is a disciplined approach; any indiscipline in implementing the approach would result in the poor quality of knowledge affecting the performance of the organisation.

KM Initiative must be Backed by Several Champions Across the Organisation KM project must have several persons behind it. These persons must be the ones who are respected in the organisation and have proved themselves as successful change agents. The reason for several champions is that the initiative is not a ‘project’ which begins and ends as per the project definition. Once the organisation starts KM initiative, it becomes one more management function critical for business success and superior performance. Further, such champions should be from all levels and disciplines of the organisation, lower, middle and the top. This is needed to get involvement and acceptance of the KM project at all levels as knowledge is required by all at all levels of the management.

Accepting Knowledge as a Key Strategic Driver is Cultural Change The people in the organisation do not accept this change easily. This is difficult especially when, historically, people are used to working on the basis of the command and control principle. The use of information and knowledge in decision making, or for solving the problems, or for obtaining better insight in a complex

situation, may not be the practice. KM function empowers people with knowledge support and demands initiative for its systematic use for improved decision making. Note that this is a cultural change, and it is not automatic, or cannot be ensured by authority or directive. Therefore, KM initiative should involve all those who matter in the organisation. These people should be motivated to work on the project. Their involvement and commitment to the project is absolutely essential. KM projects in all organisations create a sense of insecurity in the people who are contributory to them. Top management must ensure that such fears of insecurity are handled effectively to enlist the cooperation of the people. Knowledge is a power and the individuals who possess that power command respect and authority in the organisation. There is fear of losing this respect and authority. Here again, the top management should take into confidence such persons and convince them that their respect and authority in the organisation would grow. This is due to the fact that the KM project is not a one time event, it is a continuous activity and people in the organisation would look at them as a source of knowledge. For these reasons, KM initiative is a cultural change in the organisation, it cannot happen automatically. The principles of change management must be followed for successful implementation of the initiative.

Create a Change Management Plan for KM Initiative In a knowledge driven organisation, people are required to change their style of working. They are empowered by knowledge and are expected to play a responsible role in the organisation. The work culture is more collaborative and technology driven. In order to move from traditional bureaucratic working to knowledge driven working, people have to change considerably. The change is too significant to be digested easily. For smooth transition from the bureaucratic to the knowledge driven style of working, a change management plan is necessary. The change management plan, besides training in technology, must include changes in job descriptions, roles and responsibilities, level of knowledge contribution, performance and appraisal reviews, compensation plans, and so on. The mind set of the people also needs to change from: • Holding information, knowledge to sharing it without reservation • Close door to open door transparent working, seamless exchange • Acting only on directive from command to initiative with responsibility • Information driven to knowledge driven • Reacting to proactive response • Active user to creative knowledge developer The change management plan is to be made in such a way that the KM initiative is accepted by the people. The transition to new way of working is then smooth.

Knowledge Management, a Strategic Initiative The kind of change we are talking about needs to be understood as strategic. It has a long term effect and significant impact on business results. It is not to be viewed as a ‘task’ or a ‘project’, a one time operation ‘plan and finish’. KM initiative is to be planned for implementation and then for maintaining it on line. It is to be treated as mission critical application for discovering the knowledge required to create and maintain competitive necessities and advantages. Knowledge is an asset to the organisation. The creation process focuses on discovery of that knowledge which is critical to the organisation’s success and superior performance. If the organisation’s aim is to become lean, flexible and highly responsive to customer needs then KM initiative is to be treated as ‘strategic’.

Similarly, if the organisation’s aim is to be competitive and be ahead of the competition by leveraging on knowledge and knowledge assets then KM initiative is strategic. KM is a strategic endeavour. Linking knowledge and KM to business strategy is the single most important task of KM teams in the organisation. Figure 3.12 shows the model of such linkage. Business Environment Influences Threats to Business, Competition, New Products, New Technology, Demanding Customers and Suppliers

Impacts

Long Term Strategic Thinking and Strategic Plans

Selection of Competitive Advantages

Fig. 3.12

Choice of Business Strategy

Choice of ICT Infrastructure

Integrated KM Strategy

Linking Business Environment to KM Strategy

To explain this linkage, let us take the case of demanding customers due to globalisation of business. The customers have access to information about the products, their features and where they are available. They continue to put pressure to deliver such products at their price expectations. The organisation which otherwise is a leader in the market may lose on market share as well as on margin if the present competitive advantage of ‘Price – Product’ leadership is not maintained. Such organisation’s strategic thinking is impacted by demanding customer pressure on every account. Naturally, business strategy formulation is influenced by this strategic thinking, forcing the management to build a strategy around this business compulsion. Such strategy can be more right if the customer’s requirement knowledge is captured through KMS. Further, the KMS which can generate such knowledge may demand technology infrastructure which will identify and articulate customer knowledge to build sustainable competitive advantage. The process is detailed below:

1. Begin with Key Knowledge Area The question ‘Where to begin?’ would arise when KM initiative decision is taken. There are seven knowledge areas, like customer knowledge, product knowledge, relationship knowledge, process knowledge, and so on. Which one to choose? The best way to handle this issue is to choose that area which is most useful and beneficial, and has all the ingredients of successful launch. Within that area, start with one of the key segments where knowledge search is relatively easy and the discovered knowledge has a visible use in the organisation. This approach is essential if we accept that change to knowledge driven working is critical to the organisation. Its failure to succeed is not an option with the organisation. Hence, slow and steady is the way to ensure success. This approach also helps the project manager to learn by experience before the entire organisation is taken for KM initiative coverage. KM initiative requires handling of people, technology, and business needs and priorities together. They are complementary to each other. The advantage starting in a small key area segment is that commitment of resources is very limited and its allocation is also easy. This approach is a Prototype and has the advantage of learning, experimentation,

86 Knowledge Management

design and cost effectiveness of delivery. It also brings in precision in cost, time and effort estimation. The organisational issues, like allocation of resources and choice of technology are sorted out. The processes and methods of launching the KM initiative organisation wide are tested and finalised.

2. Focus First on Explicit Knowledge Required by Many We have understood two knowledge types, explicit and tacit. The character of explicit knowledge is most suitable to focus and start KM initiative. Explicit knowledge, compared to tacit, is clear in definition, has a specification, can be coded and stored, and is easy to disseminate. It can also be handled by technology at relative ease and hence is the choice starting the initiative. Other merits of explicit knowledge are that it is easily understood by the users and developers, impacts on the results are quick, and can be measured to assess validity and vitality. And last but not the least, it sends the positive message in the organisation that KM initiative has strength and is successful. It encourages people to come forward to participate with commitment.

3. Set Realistic Expectations on KM The proponents of the knowledge management have to be careful and cautious in setting the expectations on the gains that it would offer. The expectations must be measured ones and duly consider all probable limitations and issues in KM implementation. It is better to be realistic and SMART —Specific, Measurable, Achievable, Realistic, and Time bound. When it comes to setting expectations, one should not forget customer and user expectations. They are not only users but are stakeholders in KM initiative. They should be properly informed about the initiative and the benefits that are likely to occur. It is better to start with lower but realisable expectations and then raise them as KM becomes a reality. In many cases, customer and end user are direct beneficiaries of KM. They interact directly with knowledge databases and seek solutions to problems and answers to queries. If these expectations are not properly assessed and set, then there is a great chance that KM may not fulfill them.

4. Integrate KM into Existing Systems KM systems should not remain standalone systems. They must be an integral part of the larger information system portfolio for better effectiveness. Probably a database of may be a exclusive one but KM systems must be a integral part of CRM, e-mail, remote diagnostics systems, KM systems, DSSs, help desks, and so on.

5. Educate Users; Internal and External All users must be educated in KM systems use. They should be exposed to the total scope of KM systems and its internal. The education and training would help users to benefit from the system and then thus would make them willing participants in the system. They would contribute to its sustained growth. A quote from Gartner, Inc says ‘Those enterprises that include KM processes as part of CRM processes have a higher probability of success than those that don’t’.

THEMATIC ANALYSIS OF KNOWLEDGE MANAGEMENT So far we have discussed the definition, application, critical importance, factors of successful application, Networks which provide the platform for knowledge management, and a new resource, ‘knowledge worker’. In this section, we take up the thematic analysis of knowledge and its management. • Knowledge management is a discipline founded on economics and management science, driven by systems thinking and used for knowledge creation for problem solving and performance improvement. Figure 3.13(a)

Systems Approach, Systems Engineering to Achieve Business Goals

Business Economics, Information Science, Management Science, Cognitive Science

Driven by

Founded on Knowledge Management

Used for

Visible in

Innovative Strategy, Problem Resolution, Creation of Knowledge Assets, IC and IPs

KM Document, Knowledge Portal, KM Practices, Network of Knowledge Workers

Fig. 3.13

(a) Knowledge Management is a Discipline.

• Knowledge Management is driven by internal and external forces. KM initiative is driven by internal forces to remove bottlenecks, improve performance and maintain competitive necessities and external forces, demanding more from the organisation to meet the needs of expanding markets, demanding customers and stake holders. Figure 3.13(b)

Internal Forces: Process Bottlenecks, Maintenance of Competitive Necessities, Advantages, Adverse Impact on Business

Fig. 3.13

Driven by

Knowledge Management

Driven by

External Forces: Globalisation, International Competition, Expanding Markets, Demanding Customers, Vendors, Stake holder

(b) KM is Driven by Internal and external Forces

• Knowledge management is a multi-centric endeavour. Figure 13.13(c)

HR Centric

Technology Centric

IC, IPs Centric

Aimed at Org. Centric Effectiveness

Focuses Simultaneously On Knowledge Management

Fig. 3.13

(c) Knowledge Management is a Multi-centric Endeavour

Knowledge management process is required to focus simultaneously on a number of centres. It is HR centric because HR is the single largest contributor to the endeavour. It becomes automatically technology centric as knowledge needs to be taken to users by transfer and share processes for which technology is an enabler or a driver. While KM process, major effort is to search knowledge which is useful for business benefit, it endeavours to make some part of knowledge body of a high value that is termed as intellectual capital. Further, success of KM process is measured by the increase in organisation’s effectiveness while balancing the efforts in favour of HR, technology and intellecual property. • Knowledge Management makes business impact on efficient and effective transfer and sharing mechanisms in the Knowledge Network. Figure 13.13(d)

Source of Transfer: Chat with Internal Consultants, Experts On the Job Training, Seminars, Workshops, Video Conferencing

Fig. 3.13

Knowledge Management

Shared and Used Through: E-mail, Databases, Groupware E-manuals, Communities of Practices, Interests Rules, Models, Algorithm, Directives

(d) KM Impacts due to Efficient and Effective Transfer and Sharing Mechanisms in the Knowledge Network

The knowledge developed needs to be transferred at user locations and then be shared by those users among themselves for application. The transferring and sharing tools installed on the knowledge network are the backbone of KM. • Knowledge Management rides on basic processes and is enabled by certain drivers. Figure 13.13(e)

Processes: Identify, Define, Create, Validate, Store, Transfer, Share, Use, Integrate, Enrich, Revalidate

Knowledge Management

Enablers: Leadership, Org. Structure, Work Culture, ICT Rewards, Recognition, Compensation, Cognitive Skills, HR Capabilities

(e) KM Processes and their Drivers

Fig. 3.13

While processes are clear enough to understand they are not easy to implement if enablers are not in place, and are not in sync with each other. The critically important enablers are leadership, work culture and management thrust. • Knowledge Management has two stages, development and management Figure 13.13(f).

D E V E L O P E N T

Fig. 3.13

Identifications, Validation Learning, Acquiring, and Accessing External Knowledge

Knowledge Management

Coding, Mapping Transfer, Integration Experiencing Re-validating Knowledge

M A N A G E M E N T

(f) Two Stages of KM: Development an Management

Knowledge management is a discipline and is driven by external and internal forces. It is a multi-focus activity concentrating on HR, IS and IT, IC and IPs, and on achieving organisational effectiveness. KM survives on efficient transfer of knowledge and sharing by needy users without any hindrance. All these details of KM are easy to understand but the last aspect of Knowledge Management Generation and Application-needs elaborate exposition to appreciate its importance in Knowledge management. Let us take a practical example to explain first knowledge generation.

Knowledge Generation: Creation, Acquiring and Accessing, Learning by Doing Creation through experienced analytical observation of events and happenings, and research, design, tests and experiments for discovering the unknown

The knowledge is created by two routes. One is by observation during the process of management of business activity. The people manning various activities develop an experience of handling them efficiently and effectively. They develop thumb rules, build cause and effect relationships, develop models for prediction; learn to get better insight in the competitive scenario, and so on. They develop estimation standards, proven methods out of the experience of conducting the activities a number of times and the lessons thereof. This is mostly tacit knowledge, difficult to formulate or articulate, to store and share. This is shared through human interaction formally and informally. The second route is by conducting research, designing of experiments, conducting sample tests and surveys. The data collected through these initiatives provides valuable knowledge in explicit form to be used for integration in the systems and processes. Some of it could be used to design strategies for change or transformation of business. In the consumer goods industry, market research, test marketing, new product introductions in chosen segments and feedback on their performance, consumer surveys, etc., are the tools to discover consumer behaviour, unarticulated consumer expectations, preferences and desires-valuable knowledge for developing market and product strategies. The organisations extensively using ICT in their business operations develop data warehouse and use data mining and OLAP tools to extract valuable information on trends, patterns and relationships. The mined data is used for developing predictive models, decision support models, business models, and associational relations—different perspectives which are then used by the managers in management of business for decision making, strategy formulations, and for creative innovative ideas for implementation. The creation process described here discovers tacit and explicit knowledge. The process, while creating knowledge, validates it before putting it to use, and it gets richer in content on feedback given by a number of users. Such knowledge, over a period, with its learned usage assumes the status of ‘Knowledge Asset’. Some of it becomes a differentiator to leverage upon. Acquiring and accessing through licensing, training, outsourcing, alliance The third source of obtaining knowledge is to procure it by resorting to licensing, training, outsourcing and getting into alliance with competent R&D, technology, manufacturing business organisations in the chosen field. Organisations sign technical collaboration contracts with the other firms for know how of manufacturing and development of products. They actually get the knowledge, tacit and explicit, through technical documents, drawings, process diagrams, consulting advice, implementation assistance, technical and operations manuals, and so on. Training people is a standard method of acquiring knowledge by engaging experts and specialists in the field. This method is resorted to when a large group of people are to be educated on knowledge driven activity. Organisations use internal resources to train people. Medical representatives, service engineers, on site developers, are trained in new knowledge which drives their main activity. Such training is not only aimed at exposure and understanding of knowledge, but on its efficient and effective application for achieving superior performance. In this process, E-learning tools, such as e-manuals, demonstration and simulation of products and processes through virtualisation, are used for self study. The training sessions are also video taped for online reference and revisit at a later date to refresh knowledge. Outsourcing is the next choice for acquisition of the knowledge. The organisations are so busy in their operations that acquiring knowledge does not become a systematic committed effort. However, organisations identify the knowledge and the area for its discovery (where possibly it can be found). Then, instead of investing in HR and allied infrastructure, they outsource the

knowledge discovery to external competent agencies. Most of these outsourced projects are long-term and are expected to come out with knowledge discovery which would take the business in a new direction, or make a path-breaking turnaround. Many organisations select their alliance partners for their competence knowledge. Such partnerships are win-win situations for both. The alliance partners, by virtue of strong business relation, exchanges knowledge from time to time. Such exchange and sharing is beneficial to both parties. The alliance means both parties are preferred choices in each other’s business. The alliance relation is essentially a knowledge partnership. In all four methods of acquisition and accessing, the most important point is that knowledge is identified and located at some destination. The acquisition and then accessing, it becomes critically important. Learning by doing through, on the job training, hand holding, simulation Some knowledge objects are such that they are best learnt by using them in practical cases. The on the job training is a method which is chosen to learn by doing, acquiring knowledge by working on the job. In health care and diagnostics, knowledge is acquired by seeing a number of patient cases, simple and complex. This experience is a kind of on the job learning. Some jobs are such that an expert hand holds the work along with the main operator. This method is chosen when knowledge is largely tacit. In some areas of knowledge, experts are few and far away. Knowledge, however, can be structured in a knowledge product. This product is used to learn by simulation. Knowledge products are essentially a electronic content made of text and images with extensive use of imaging and animation technology. Organisations produce these products and post them on knowledge portals for access.

Knowledge Treatment Justification Knowledge needs to be identified from the point of its utility to the business. There could be many new revelations qualifying for the knowledge. The issue is, relevant? Can they be considered as competence, as differentiators? The identification of the knowledge recognises its place in knowledge database. Identification is the process which helps to select knowledge objects which are relevant to current business strategy needs. Measurement Knowledge needs to be measured for its effectiveness. It needs to be specified in some form, easy to understand, easy to handle. Archiving Once knowledge is measured and is upto the expectations, it is a case of archiving in the database or folder, as the need be. The archived knowledge is on the network for online access to users. Transfer It also means sharing with users. The knowledge decided for archiving is then transferred to database, folders, portal, website, and so on. Replication Knowledge in one form or model needs to be replicated at different locations for quick and easy access at that location. Replication is mirroring the knowledge as it is. However, this may not be always efficient from user’s point of view at that location. Knowledge undergoes a change in form, format and content, if necessary, before it is replicated for storage. The change in the knowledge is location specific to make it user friendly. The change is mainly in representation and style. Integration Instead of knowledge being stored for use as and when required, attempt is made it to integrate it in the systems and processes for immediate use. The integration is achieved by designing knowledge based business rules, decision models, DSSs, estimation directives. The type of knowledge which is a candidate for integration is the one which does not change time and again with the changing business environment. It is knowledge application integration for expeditious execution of the process and making it person independent.

Experiencing When knowledge is put to use by choice or through integration, users experience its efficiency and effectiveness in application. The experience reinforces the belief in knowledge and its effectiveness. The experience also triggers the process of replacing current knowledge, or enriching the knowledge in scope, content and application. Validating knowledge Knowledge validation is a process which confirms the currency and vitality of knowledge for business application, developed to achieve business performance goals. If knowledge is not valid or has lost its vitality, it becomes a case for archiving in the back office servers. We now summarise the thematic analysis of ‘The Knowledge Development and Application’ in a system model as shown in Figure 13.14.

Identify, Construct Knowledge Objects Helping to Achieve Goals

Assess and Validate the Knowledge Objects

Performance Goals. KRAs, CSFs, KPls

Select Knowledge Components

Integrate, Apply, and Learn, Out of Experience

Create, Acquire Knowledge, and Knowledge Assets

Produces Superior Performance. Achieves the Goals

Enrich, Upgrade, Replace Knowledge Dynamically Knowledge Database

Fig. 3.14

Knowledge and Application System Producing Results

The Knowledge Generation and Application System begins with setting business goals and performance parameters. The Key Result Areas (KRAs), Critical Success Factors (CSFs) and Key Performance Indicators (KPIs) are determined for the business currently in place. The management then identifies knowledge objects which need to be generated as an aid to achieve the business goals and performance targets. An attempt is made to find knowledge internally, and the balance is acquired from external sources. The knowledge objects are validated for their relevance and utility in the management effort of achieving the goals. Knowledge can be represented in the following manner.

Knowledge • Facts or Statement of Facts These could be data or information. But these are indisputable and can be used in any problem solving situation. Example Minimum body temperature, Income Tax Code and its applicability.

• Scientifically established Rule Example Unified modeling language (UML), different software development models, project management processes. • Procedure developed over a period and applied for resolving all kinds of cases where its applicability is very sound. The procedure, by virtue of its applicability, is a matured one, and is safe and flexible to apply to handle a complex situation. Example Loan processing, Insurance claim processing, Package delivery services, Patient care handling, OPD procedures, etc. • Formula Converting procedure or rule into a formula built out of constants and variables applicable in well defined situations with specifications of starting and ending conditions. These formulae can be embedded in a bigger decision making systems. Example Cost models, ROI, ROCE, EMI calculations, Tax calculations in billing systems. • Heuristics is a well defined logically developed procedure, developed over a time, out of experience of solving same or similar kinds of problems. Unlike rule or formula, it does not assure correct decision in all cases. It is based on reasoning by analogy, deductive and inductive reasoning, and case based reasoning. Heuristics is based on certain premises. The result that happens when those premises are true in most cases is the conclusion or decision. Example Choosing a lawyer, chronic unemployment causes social unrest, Diversity could be a virtue or a problem. • Know How is a bundle of knowledge held by experts who use it in varying degrees to solve a problem. These problems are not easily amenable for solution by rule, formula, procedure or Heuristics. Example Solving labour problems, Bidding processes in international contracts, Issues like mergers and acquisitions, Forming teams for international games, Project management. • Knowledge Products are the result of putting different knowledge sets and elements to solve certain requirements. The requirements could be developing bill of material, resource allocation, finding optimum solutions, and so on. Example Software products: ERP, SCM, CRM, PLM, Core banking solutions, Forecasting models, Spread sheet models, etc. • Knowledge Assets are HRs or knowledge products which provide the organisation a competitive edge over competition. They are differentiators and are competitive advantages to the organisation. Example Core banking solutions developed by TCS and Infosys, Payment solutions developed by I-Flex, Dr Govarikar’s rain forecasting model held by IMT lab, Manufacturing knowledge of Boeing and Airbus, Knowledge held by Sony in electronic and entertainment products, and many more. Knowledge, where possible, is integrated into systems and processes for its efficient and effective use in achieving superior process performance. The use of knowledge in solving a number of problems provides experienced learning in its application. The learning experience of managers enhances the quality of knowledge. Some knowledge is replaced for the better and some is archived for use later. The most important element (input) in the KM cycle is the cognitive skills and abilities of the people, namely, • Mapping knowledge with context to problem solving needs • Acquiring it in the desired form • Codifying it for understanding, representation and integration • Storing with conceptual clarity for ease recall • Ability to integrate or disintegrate for transformation to new knowledge

94 Knowledge Management

The essence of thematic analysis is that the organisation must have an eco system to flourish as knowledge driven organisation, achieving business goals and facing competition. The eco system is made of two components, ICT infrastructure and the work culture of sharing knowledge, tacit or explicit. Next to eco system in importance is the process of transformation dynamics. We now discuss these three processes of knowledge creation, transformation and utilization at length in the following section.

SECI MODEL: KNOWLEDGE TRANSFORMATION AND ITS DYNAMICS Three researcher groups prescribed three processes of transformation and dynamics, i.e., knowledge creation and utilization. They are: – Nonakas’s: Socialisation–Externalisation–Combination–Internalisation – Earl’s: Knowledge inventorying–Auditing–Experiencing–Socialising – Hedlund’s: Internalisation–Articulation– Reflection–Dialogue–Expansion All three research groups believed that unless the identified knowledge is transformed in some way it would be useless or be not usable. Knowledge transformations and its dynamics point out to processes which make it possible. But it also relies heavily on technology (human and machine) and knowledge culture of the organisation. The process advocated by Nonaka’s is that of socialisation; Earl’s emphasis is on inventorying and auditing, while Hedlund’s is on participation through internalisation and dialogue. The process, technology and work culture together from the infrastructure of transformations and dynamics of knowledge. The technology majors are data warehousing and mining, document management system, content management systems and Groupware and web based communication. The second component of infrastructure is appropriate knowledge culture for knowledge management. The knowledge culture is seen when people make special efforts in learning out of experience and articulating it in tacit or explicit knowledge. The effort is also seen when knowledge is upgraded or replaced by a new knowledge acquired by its usage in business applications.

The SECI Model of Knowledge Creation According to Professor Ikujiro Nonaka, knowledge creation is a spiraling process of interactions between explicit and tacit knowledge. The interactions between then lead to the creation of new knowledge. The combination of the two categories makes it possible to conceptualise four conversion patterns. The four modes of knowledge conversion interact in the spiral of knowledge creation. The spiral becomes larger in scale as it moves up through organisational levels, and can trigger new spirals of knowledge creation. A more analytical discussion is given in chapter 5. Socialisation: Sharing tacit knowledge through face-to-face communication or shared experience. An example is an apprenticeship. Externalisation: Developing concepts which embed the combined tacit knowledge, and which enable its communication. Combination: Combination of various elements of explicit knowledge. Building a prototype is an example. Internalisation: Closely linked to learning by doing. Explicit knowledge becomes part of the individual’s knowledge base (e.g. mental model) and becomes an asset for the organisation. For effective management of knowledge creation and its exploitation, the organisation has to map its inventory of knowledge assets. Cataloguing is however not enough. Knowledge assets are dynamic; new knowledge assets can be created from the existing ones.

Four categories of Knowledge Assets • Experiential Knowledge Assets: Tacit knowledge with common experience. They are skills and know how of individuals, such as care, love and trust; energy, passion and tension. • Conceptual Knowledge Assets: Explicit knowledge articulated through images, symbols and language texts. They are product concepts, design and brand equity. • Routine Knowledge Assets: Tacit knowledge made a routine and embedded in actions and practices. They are know how in daily operations, such as organisation routines and organisation culture. • Systemic Knowledge Assets: Explicit knowledge packaged into documents, manuals, specifications, databases, patents and licenses. Nonaka and Takeuchi believed that organisations create and use knowledge through the interactions between tacit and explicit knowledge. It begins first with creation of tacit knowledge. Its use in a number of occasions induces and encourages transforming it into explicit knowledge. The process of creation and interaction is continuous. The conversion of tacit to explicit and back to tacit is through human interaction. The conversion process improves knowledge, both in quantity and quality, when the loop is complete. The conversion process has four steps or stages, Socialisation, Externalisation, Combination and Internalisation (SECI), all driven by people in the organisation. Figure 3.8 shows the SECI model of knowledge creation and utilisation through the process of conversion. Let us understand the SECI model through an example of a Pharmaceutical company selling pharmacy products, first through introduction to doctors and then through retail medical shops. The medical representatives (MR) visit doctors and distribute sample medicines for testing. During the discussions, the doctors share a specific health problem, MR explains the new medicine’s strength in handling the problem. This phase is socialization, where MR collects tacit knowledge from various doctors. The experience of each doctor is different, clinical analysis is different, and diagnosis is also different. The information about the new medicine in context of specific ailment collected from all doctors is tacit knowledge. All MRs make a record of tacit knowledge and exchange with each other. The tacit knowledge collected by all MRs is combined systematically by editing and processing in a table form. This table shows the details of the ailment, patient condition, prescription, patient’s feedback, and doctor’s diagnosis. This process externalisation which puts together tacit knowledge elements of all MRs, or their groups, into a format for all to use for sharing with doctors and learning more through interaction. Externalisation is the process of articulating and translating distributed and assorted tacit knowledge elements into an organised format, making it explicit knowledge, easy to read, understand and share. This explicit knowledge, after fair amount of testing and confirmation by doctors, is taken systematically for integration into the development process, manufacturing process, distribution literature or in CD for sharing with doctors. This process is called combination where explicit knowledge takes a form and format for communication, dissemination and for making it part of a system or process. In this stage, group knowledge sets are put together for organisation’s use. The clinical experience of new medicine is again collected by MRs from the doctors on more specific issues of the ailment. In this phase, the experience of explicit knowledge gives rise to new learning, a tacit knowledge. This advanced tacit knowledge is further shared with concerned experts and specialists to take it forward for improvement. The process is termed as internalisation for learning and acquiring new tacit knowledge in practice. The SECI model explains the process of knowledge creation, conversion from tacit to explicit and back to new tacit, and its utilization in practice. The process is repetitive in nature and needs to be executed

through well defined activities, called routines. The organisations must build the reliable Dynamic Systems for Knowledge Creation and Utilization (DKCU), incorporating the creative routines for execution of the SECI model. These systems integrate changing contexts and ensure that new knowledge is created through SECI to put into practice. The SECI model needs DKCU as a support system. (Source: Clippinger, Decoding the Laws of Enterprise).

DKCU as a Support System In application of the DKCU model, knowledge conversion takes place through three processes at three levels. The levels are: • Level 3 Improvising on shared contextual knowledge • Level 2 Articulating tacit knowledge through dialogue • Level 1 Combining explicit knowledge using IT and organisation structure Level 1 is at the top. Level 2 separates explicit knowledge and tacit knowledge. The people involved could be internal as well as external to the organisation. They participate in the SECI process for conversion of knowledge in the capacity of an individual, a group or an organisation. If this conversion has to happen systematically and consciously, formal process routines need to be designed for each of the conversion processes, as shown in Figure 3.15. Develop Creative Routines for Creation and Use of Knowledge Through Dialogue, Formal Interactions, Forming Groups of Interest, Teams to Develop Knowledge Assets Exchange Knowledge, Share and Learn

Fig. 3.15

Explicit Knowledge

DKU: Hard and Soft

Tacit Knowledge

Develop Creative Routines to Internalise the Tacit and Explicit Knowledge into Business Systems and Processes using ICT. Learn New Findings and Develop Tacit Knowledge

DKCU Model of Knowledge Conversion

Let us take an example of an organisation in the business of selling consumer durables, white goods, through dealer distributor network. In the process of selling goods, customer knowledge is very important. Let us see how SECI and DKCU models are helpful in customer knowledge creation and utilisation. The parties involved in the socialisation stage are the salesman at the show room, travelling salesman, support engineers, customer service engineers and marketing manager. Each of these personnel is interacting (socialisation) with the customers. They gather a lot of context sensitive information, knowledge, on price, performance, problems, solutions, choices, preferences, required features, expectations on commercial terms, queries on competition, reasons behind the choice of brand, etc. When these people meet formally or informally, tacit knowledge is exchanged. In summary and review, this tacit knowledge slements are put together in a commonly understandable form (externalisation), making tacit body knowledge ‘explicit’. This explicit knowledge could be from three different areas, namely customer complaints and Resolution, Customer feedback on performance, price and terms, customer feedback on unfulfilled expectations and

unarticulated and not expressed expectations. This explicit knowledge is then analysed and business rules, customer profile, customer segment and preferred models, and so on, are developed (combination). Based on this knowledge support, some of these knowledge assets are used in systems and processes in manufacturing, marketing and sales strategies. The experience of using this knowledge in business processes (Internalisation) gives rise to new tacit knowledge which, in turn, through the process of socialisation and externalisation becomes explicit. The DKCU creative routines for knowledge creation and utilisation could be many. Some are stated below as an illustration. These are technology driven creative routines termed as hard routines. • Meetings, report sharing, weekly • Complaints and solutions report filing, daily • Customer suggestions, observations posting on intranet site, instantaneous • Conversion of prospects into customer, monthly • Repeat customers choosing the same brand, monthly Frequent face-to-face contact at coffee table or lunch table, virtual meetings on internet, informal chat at a function or party, are the soft creative routines for tacit knowledge creation and utilization. These creative routines work on the output of the hard routines stated above. The knowledge gathered out of these creative routines is then used for improving sales performance and increasing customer satisfaction. DKCU systems and routines in it are made out of symbolic language, distributed knowledge, and cross boundary teams working in the organisation. The symbolic language includes models built on scientific reasons, metaphors, analogies and stories. The distributed knowledge is either with people or in electronic records which is assembled into context specific body of knowledge. For example, employees at a call centre have captured customer specific, domain specific and problem specific knowledge over a period of interaction with customers. This distributed knowledge amongst, say, 30 employees is to be gathered for converting into a knowledge asset for use by all. The cross boundary team members or functional team members have tacit and explicit knowledge exclusive of the specific function. This knowledge capture is for specific functional goal achievement. The organisations however have problems which need knowledge support from more than one discipline. In such cases, cross functional teams are formed which develop creative routines for knowledge creation and utilization. For example, the project manager develops cross functional teams as standby for solving complex problems affecting project performance.

Barriers to Knowledge Management KM comprises any process of creating, acquiring, capturing, sharing and using this knowledge, wherever it resides, to enhance the learning and performing in organisations. Probst/Raub/Romhardt provide a straightforward and easy to understand model for the description of the processes of knowledge management. However, while applying this model within various industrial cases, especially in the engineering domain, the aspect of ‘structuring’ knowledge seems to be of high relevance for knowledge management. Thus, the model is adapted to the specific needs of engineering industry and business by adding an additional building block structuring. Along with the processes of knowledge management many barriers exist, making KM a challenging task. A barrier relates to human, organisational and/or technological issues that obstruct the intra- and interorganisational management of knowledge.

Knowledge Goals

Feedback

Knowledge Assessment

Application

Identification

Acquisition

Storing Structuring Distribution/sharing

Generation

Fig. 3.16

Probst, Raub, Romhardt KM Model

Knowledge Goals

Identification

Feedback

Knowledge Assessment

Application

Storing

Acquisition

Structuring

Generation

Fig. 3.17

Distribution/Sharing

Barriers to Knowledge Management (shown in thick black line)

Barriers Related to Technology Legacy systems and incompatibility: Legacy systems are often the cause for compatibility problems, either company internal or company overlapping. The possibility of having different software systems automatically increases with the increase in the number of communication partners. The possibilities to overcome this barrier are either the identification of a system according to the principle of the lowest common denominator, or to invest in a technology that satisfies the needs of all the partners involved.

Barriers Related to Organisation • Lack of awareness of knowledge management strategies and instruments Conscious handling of resource knowledge still seems to be a big issue when talking about barriers to knowledge management. The necessary awareness for the management of knowledge is relatively low among the people. • High investments Building intensive partnerships with customers and suppliers requires significant amount of time and money. Once this has been invested, there is greater reluctance to break up the alliance should the performance of the alliance be insufficient. • Unavailability of individuals It was considered difficult to track people down when wanting to talk to them. This resulted in time delays in searching for the specific individual. A second barrier in point in this context is one does not know who would be the best person to ask in certain cases. • Different working times When dealing with partners from other countries, different problems arise. Dispersed location of time differences often limit communication to a small time frame, and thus to indirect communication means. Videoconferencing, which is considered to be an important communication mean, could therefore fail in usage.

Barriers Related to People • Different languages The language barrier is a problem when dealing with people from other companies, either from the same country or from abroad. When dealing with international companies, it is recognised that misunderstandings can result if people do not speak the same language with a certain level of competence. • Fear of penalty/fear of losing profile The presentation of not clearly defined ideas (soft ideas) is often considered to be a weakness, thus reducing the space for creative thinking and creation of synergies to develop ideas. • Idea robbery This barrier describes the fear that the idea of an individual/employee could be taken by another who would then get the acknowledgement and rewards. It implies the need for the protection of proprietary knowledge among employees. • Fostering established communication channels Communication channels between colleagues across different companies must be maintained and fostered, thus resulting in high efforts. Since the establishment of good relationships is time consuming, means must somehow be provided to support this task.

Justifying the Business Case for Knowledge Management In today’s global business scenario, knowledge management has become an important function for success in the competitive environment of the business. It has been proven beyond doubt that the organisation has to become knowledge driven in its endeavour to beat competition. The organisations accepting this as paradigm shift need to make a business case justifying formal introduction of KM as an important function among many others. It is difficult to prove that ‘knowledge’, tacit or explicit, is directly linked to the positive impact on business outcome, Hence the job of justification of KM is not that simple. KM, by definition, is a systematic approach to create and utilise knowledge for business gains. As stated earlier, organisations look for knowledge which has a context to required business performance, and is an enabler to achieve it. Knowledge creation is not in isolation from the rest of business management. The attempt through KM is not to create knowledge repositories for use ‘just in case’ required. It is an integral part of other business management functions. As traditional business management functions are linked and

planned, keeping in view the business strategies developed for achieving business goals, the KM function has a strong link and relation with business strategy and business goals. To prove this link of KM to the bottomline business performance, a framework is suggested. This framework is made of a series of steps, as prescribed by Albers’ Framework for Implementing Knowledge Management Model (Albers, 2003). The framework would aid knowledge management implementation champions in establishing the business case for KM introduction as an important function. Alber’s Framework has following critical steps, each having a specific goal to achieve in context of KM in the organisation. 1. Business strategy assessment 2. Knowledge assessment and audit to support efforts gaining strategy success 3. Knowledge and business strategy alignment 4. Business opportunity identification 5. Value, business benefits and evaluation 6. Risk reduction techniques

Business Strategy Assessment Every business is unique and, therefore, the KM initiatives that each undertakes are also unique. The organisation needs to determine the business strategy to address the question: Where is the organisation going? The strategic assessment includes establishing/reviewing the vision and mission, analysis of the firm’s competitive environment, analysis of internal strengths and weaknesses, and formulation of strategic actions. Once this has been clarified, it then needs to be determined how knowledge fits into this overall business strategy, objectives and value proposition of the company. The value proposition considers how the company specifically creates value and offers unique goods and services to its customers. Knowledge management can play a pivotal role in both defining what direction to take and implementing strategic actions.

Knowledge Search and Audit Knowledge search identifies what knowledge exists in the organisation and what knowledge is needed to move the organisation in a strategic direction determined in the first step of the framework. Audit identifies the expertise in the organisation, where it can be found, and how this expertise is accessed. It identifies what knowledge is needed to make decisions and what knowledge needs to be discovered. Hence at least a basic knowledge overview needs to be performed to become aware about the current state of KM.

Knowledge and Business Strategy Alignment The third step that needs to be undertaken is to align the firm’s knowledge strategy with its business strategy. The alignment exercise identifies what is needed and what is available, thus revealing the knowledge gap. The knowledge gap is the difference between ‘what the organisation must know’ and ‘what the organisation knows’. The alignment of the knowledge and business strategy should identify what knowledge really matters and how that knowledge is linked to strategy and business performance. The outcome of the exercise is a clear revelation of the strategic knowledge, the Knowledge Requirement Plan (KRP).

Opportunity Identification The alignment exercise has fixed the relation between vision, strategy, knowledge, and the knowledge to be discovered for new vision of the business. The next step is to identify knowledge areas to work upon, to elicit the identified knowledge. While identifying areas for knowledge development, it must always be remembered that some form of baseline, benchmark, or measurement system must also accompany each effort in order to manage and judge its success.

Business Benefits Once knowledge areas have been identified, the business case in support of each knowledge area is to be established. There are effectively only three viable approaches to justify a new KM initiative (Oldham et al, 1997): • Economic (break-even, ROI, IRR, NPV) • Analytic (value analysis, risk assessment, portfolio analysis) • Strategic (business objectives, competitive advantage) All three have obvious benefits linked to business processes. David Skyrme has suggested the utilization of a KM Benefits Tree to highlight the connections and relationships between asset value, benefits potential and cost effectiveness (Skyrme, 2001).

Risk Reduction Techniques for KM Success Having developed a framework to be followed to make the business case for a knowledge management initiative in the organisation, it is worthwhile to mention risk reduction techniques to justify the KM case as well as its successful implementation for achieving the goals and benefits. There are three broad categories of knowledge, the minimum complement that is necessary for every organisation. They are: • General or structured knowledge for sharing This knowledge is required in any case to perform and do business. • Focused competence This knowledge gives the organisation ability to maintain sustainable competitive necessities and keeps the organisation in step with its competitors. This is the survival need of the business. • Strategic competence This knowledge gives the organisation its specific source of competitive advantage and keeps the organisation ahead of the competition. It is recommended that the KM be initiated with one or two relatively straightforward and quick projects to instil confidence and to demonstrate success. The general or structural knowledge is the case in point. This can then be followed up with a more extensive portfolio of projects that would focus on focused knowledge competencies. KM initiatives are more likely to prove beneficial in the long term if they use this framework of implementation. Knowledge management encourages the creation and application of knowledge, tacit, explicit, and embedded in the form of IC. KM leverages on personal understanding developed out of experiential learning, group or community’s capability of dealing with complex problems by using collective knowledge, organisation’s capability built out of experience of maintaining competitive necessities and competitive advantages to remain ahead of the competition. KM justifies its place as top management directed function due to its positive impact on business performance. Figure 3.18 shows KM activities in a Tree model.

End Notes • In this century, technology, in general, and information and web technology, in particular have made a paradigm shift in the way business is done. They have changed style, culture, and structure of business management. New business models have emerged. • This radical change has made business highly competitive, demanding focus on developing sustainable competitive advantages. Creating sustainable competitive advantages requires efficient management of knowledge assets.

Identification Creation Generation

Learning by Doing Acquiring

Knowledge Identification

Transfer, Share, Replicate, Use, Apply

Measuring for Value Application

Revalidation

Archiving

Integration

Fig. 3.18

Search, Validation, Experimentation of Knowledge, Organising, Shaping for Use, Testing Training, Hand Holding, Experimenting, Simulation and Experience

Licensing, Buying Knowledge, Alliances and Storing

Establish ICT, Groupware, Communities, HR Deputation

Benefits, Gains, Impacts, Accounting for IC, Bench marking

Reconfirming the Continuation of Knowledge

Databases, Case Studies, Success Stories, Reports on Events

Business Rules, DSSs, Decision Models, Guidelines

KM activities Tree, Generation and Application

• The knowledge driven organisations work on knowledge network platform. The knowledge network is an essentially a network of experts, specialists, experienced persons holding tacit and explicit knowledge about the processes, products, and people – employees, customers, and stake holders. The computer network which connects them enhances their ability to generate knowledge and share it through network. • There are three approaches to KM initiative implementation, technology, cultural and systemic. A lot depends on the three main factors, namely, type of knowledge, HR, and the organisation structure. • Knowledge management is the explicit and systematic management of vital knowledge and its associated processes of creation, aggregation, organisation, share, use and exploitation in pursuit of business objectives. • The steps in knowledge management cycle are create, aggregate, store, share, use, validate for vitality, enrich or replace. • Knowledge Management focuses on ‘vital’ knowledge. In the business management process, many new revelations and experiences occur. All are not necessarily qualified for knowledge as they happen to be incidental or one odd, which does not deserve systematic handling through the KM cycle. Knowledge must be critical, and must have confirmed tested application leading to the right conclusion. In execution of the KM cycle, every knowledge candidate is tested for its vitality. • This management cycle is applicable to both types of knowledge, tacit and explicit. In case of tacit, it is highly person driven, limited by the ability of the person to go through these eight steps. In case of explicit, it is technology driven, namely, information, network and internet. The technology plays a significantly critical role in efficient development of knowledge and its application. • So the broad definition of KM is the systematic and explicit management of knowledge related activities, practices, programmes and policies within the organisation to produce competitive quality of knowledge and its efficient and effective application in business management.

• Two perspectives of KM have emerged. They are • Technology Centered Knowledge Perspective • People Centered Knowledge Perspective The understanding of these perspectives is important as they decide the focus of KM management. In case of technology centered perspective, management of technology is the focus and the key enabler of KM. In case of the other, management of people, HR, in particular, is the focus. • Both the initiatives are right and legitimate, but in different business scenarios. The businesses where knowledge is predominantly tacit should follow the people centric knowledge perspective. Businesses, where knowledge needs are clear, and knowledge is predominantly “explicit” and needs to be embedded in the processing and decision making systems, should take the technology centered perspective. Whichever may be the perspective, KM cycle in its components is the same, creation, validation, aggregation, organisation, share, use and exploitation and revalidation. • There is a three steps approach to knowledge management. It moves through the three phase cycle before it is integrated into systems and processes of the organisation. – Knowledge Definition (Identification, Validation): – Knowledge Generation (Creation, Acquisition): – Knowledge Application (Measurement of Usage, Archiving) • Charles Savage defines Knowledge Networking as the process of combining and recombining one another’s knowledge, experiences, skills, capabilities and aspirations in ever changing profitable patterns. • Knowledge network provides a common platform to the users to solve the problems, get better insight, and generate new ideas and strategies. The second best benefit of knowledge network is it facilitates building relationships between network partners leading to collaborative working on many other issues requiring immediate attention and resolution. • According to Professor Ikujiro Nonaka, knowledge creation is a spiraling process of interactions between explicit and tacit knowledge. These interactions lead to the creation of new knowledge. The combination of the two categories makes it possible to conceptualize four conversion patterns. • The four modes of knowledge conversion interact in the spiral of knowledge creation. The spiral becomes larger in scale as it moves up through organisational levels, and can trigger new spirals of knowledge creation. It begins first with creation of tacit knowledge. Its use on a number of occasions induces and encourages transforming it into explicit knowledge. • The conversion process improves knowledge both in quantity and quality, when the loop is complete. The conversion process has four steps or stages, ‘Socialisation, Externalisation, Combination and Internalisation (SECI), all driven by people in the organisation. • The organisations must build the reliable Dynamic Systems for Knowledge Creation and Utilisation (DKCU), incorporating the creative routines for execution of SECI model. These systems integrate changing contexts and ensure that new knowledge is created through SECI to put into practice. The SECI model needs DKCU as a support system. (Source: Clippinger, Decoding the Laws of Enterprise). • It is recommended that the KM be initiated with one or two relatively straightforward and quick projects to instil confidence and demonstrate success. The general or structural knowledge is the case in point. This can then be followed up with a more extensive portfolio of projects that would focus on knowledge competencies. KM initiatives are more likely to prove beneficial in the long term if they use the six steps framework of implementation.

Questions 1. Develop information driven and knowledge driven systems on the lines indicated in Figures 3.1(a) and 3.1(b) for following applications. Develop information and knowledge entities for each system • Customer order acceptance • Selecting a raw material or component for a job work • Putting a customer in preferred category 2. Identify the information knowledge and knowledge assets in the following business organisations. • Tata Motors • Idea Cellular • ICICI Bank • Mutual Fund Organisation. 3. Recommend an approach to KM initiative for following business organisations. • University • Indian Oil Corporation • ONGC • National Chemical Laboratory • Maruti Udyog Ltd • Big Bazaar 4. Explain why it is critically important to decide KRAs, CSFs, KPIs linked to business strategy before KM initiative is planned. 5. Develop a model of KMS (Figure 3.5) supporting following business applications. The model should specify the knowledge elements or entities. For example, if customer knowledge is an essential requirement of the KMS, identify and specify them in precise terms. • Medical claim processing • Customer order processing 6. Identify tacit and explicit knowledge in following industry cases where business is highly competitive. • Auto industry: Manufacturing and marketing. • Men apparels • Agro food products • Airlines 7. Explain the data, information and knowledge cycles (Figure 3.6) in the following cases. • Vehicle insurance policy processing: New and renewal. • Call centre for credit card and customer query processing 8. An organisation typically has following knowledge assets. • Experiential knowledge assets • Conceptual knowledge assets • Routine knowledge assets • Systemic knowledge assets

9.

10.

11.

12.

Identify them in the following organisations • Orthopaedic hospital • Deluxe hotel chain • Software testing organisation • Reliance fresh • Car dealer and distributor organisation • Crossword—A book shop chain Explain the following statements with examples. • Organisations ensure the competitiveness by implementing KM systems. • Internalisation is a process to develop tacit knowledge from explicit. • In KMS, it is important to have a knowledge validation and vitality checking system. • One of the prerequisites to successful KM is justifying it by a sound business case. In your organisation, identify the following: • Experts and specialists • Knowledge products • Knowledge assets • Processes which enable knowledge sharing • Customer knowledge • Product knowledge There are three broad categories of knowledge, the minimum complement that is necessary for every organisation. They are: • General or structured knowledge for sharing. This is the knowledge required in any case to perform and do business. • Focused competence: This is the knowledge that gives the organisation the ability to maintain sustainable competitive necessities and keeps it in step with its competitors. This is the survival need of the business. • Strategic competence: This is the knowledge that gives the organisation its specific source of competitive advantage and keeps it ahead of competition. Identify these three broad categories in the following businesses. • General insurance • Disaster management in case of fire in oil installation • Retail mega store • Organisations like Railways and Airlines. Question ‘Where to begin?’ would arise when KM initiative decision is taken. There are seven knowledge areas, like customer knowledge, product knowledge, relationship knowledge, process knowledge, and so on. Which one to choose? The best way to handle this issue is to choose that area which is most useful and beneficial, and has all the ingredients of successful launch. In the following cases, identify at least one area where knowledge initiative and KMS would be successful. • Hospital • Tourism organisation • Credit card business company

13.

14.

15.

16. 17.

18.

19.

• Pharma distributing company • Metro city police department Learning by doing through on the job training, hand holding and simulation is the best way to transform the knowledge to the users far way. Explain these three methods. If users are far away, how would you transform the knowledge? For smooth transition from bureaucratic to knowledge driven style of working, a change management plan is necessary. Explain what is bureaucratic functioning to knowledge driven functioning. Then, to make this change successful, what steps you would take under Change Management Approach? The factors that demand KM initiative are given below. • Market places are increasingly becoming competitive because of globalisation. • Rate of innovation is rising, bringing radical changes and dramatic results in business and environment. • Organisations, being lean, require unorganised knowledge to be converted into explicit knowledge available to all concerned. • The technology application in business processes reduces intelligent work force, compelling the management to take knowledge management initiative to capture the knowledge for common good of the organisation. • Experts and specialists are in great demand, a knowledge management initiative is essential to retain knowledge in the organisation if specialists leave the organisation. • Global competitive environment demands quick proactive responses from the organisation. Examine your organisation and its business to decide how imminent is KM initiative for developing and implementing KMS. Based on your answer to Question 15 above, make a case for KM initiative. Take a view of your organisation, or of the organisation which you know best, and examine the following and identify • Knowledge areas • Explicit knowledge in knowledge areas, existing and which can be coded • Experts and specialists in knowledge areas operating at all levels • Can the explicit knowledge be linked to your business strategy? Is your Business strategy based on knowledge areas identified by you? Sales personnel, service personnel, marketing personnel and occasionally manufacturing engineers and Account managers interact with customers for various reasons in context of their respective business goals. Use SECI model and develop the process of knowledge generation. Which knowledge, tacit and explicit, be created using this model. You may choose any organisation which you know best. Charles Savage, author of Fifth Generation Management, first brought out the term ‘Knowledge Networking’. It is a product of two concepts – knowledge a strategic resource possessed by experts, and net working, a human act of building relationship among experts. Charles Savage defines knowledge networking as the process of combining and recombining one another’s knowledge, experiences, skills, capabilities and aspirations in ever changing profitable patterns.

In your organisation, take a project goal of ‘Knowledge networking’, recognising that knowledge is a strategic resource. Assume that technology platform and LAN, WAN, Internet, Intranet, Extranet are in place. What steps would you take to build knowledge Networking of knowledge workers 20. There are two Knowledge Management Perspectives. • Technology Centered Knowledge Perspective • People Centered Knowledge Perspective Which perspective is more suitable in which kind of organisation? Name the organisations and your justification for the chosen perspective. You may choose following types of organisation. • Research Laboratories • ISRO • Ranbaxy Laboratories • Indian Oil Corporation • ONGC • IDBI • Life Insurance Corporation of India • Call centre for credit card company

4

Chapter

Management System (KM System Design and Architecture)

This Chapter Deals with • • • • • • • • • •

Generic Model of Knowledge Management System Knowledge Management System: Development Phase Knowledge Management System: Application Phase KMS: An Integrated System Challenges in Developing KMS KMS Lifecycle KM System Architecture Knowledge Construction Architecture Implementation of KMS The Learning Concept and Knowledge Management System

Learning Outcome In this chapter you will learn about KMS whose objective is to develop knowledge and apply it for business advantage. You will appreciate the equivalence in SDLC and KMSLC. Here, knowledge is viewed as a need for development and implementation of business strategy. KMS is all about managing interactions and relations between technologies, people and processes.

– —

“An organisation’s KM system delivers a vital feedback loop with customers and is instrumental in establishing customer service metrics; it focuses on creation and application of knowledge, raising its status to intellectual capital.” —Brent Hayward KM World, November–December, 2007

GENERIC MODEL OF KNOWLEDGE MANAGEMENT SYSTEM While discussing KMS, we take a system view which is linked to business strategy of the organisation. The KM system processes here are termed in line with that requirement. Knowledge Management System is defined as the process to manage knowledge in the organisation in steps, beginning with ‘identification, validation, creation, acquisition, codification and transfer, measurement, and creation of intellectual capital and converion of some into intellectual property to meet the business strategy requirements and its implementation (Figure 4.1). The purpose of KMS is to support decision making personnel and stake holders in the organisation with the online ready access to the organisation’s knowledge resources. It has two phases, development and management.

Second KMS Create IC, IP Cycle and Cycles Continue with Changing Dynamics of Business Measure Knowledge Impact

Identification of Knowledge

Business Strategy

Codify and Transfer to Users to Share

Fig. 4.1

Validation of Knowledge Creation of Knowledge

First KMS Cycle

Acquisition of Knowledge

KMSD Cycle and Dynamically Changing Business Environment

The KMS Design has two components: Knowledge Development and Knowledge Management. We call the system dynamic because ‘knowledge’ is not a fixed entity; it continuously changes and improves with application in business. Each phase of change or improvement is termed as a cycle.

KEY TERMS • Knowledge Management • Five Knowledge Areas • Knowledge Development Cycle • Knowledge Application Cycle • Knowledge Management System Lifecycle • Knowledge Drivers • Knowledge Users • Knowledge Developers • KMS Architecture • KMS an Integrated System.

Knowledge Development: Development (Creation and Consolidation) • • • •

Identify the knowledge need supporting business strategy. Validate its relevance, applicability and adaptability to the organisation as a competitive advantage. Create knowledge by extracting, organising and giving some form to it. Acquire knowledge from internal and external sources.

Knowledge Management: Application (Store, Transfer, Share, Apply, Capitalise) • Transfer it through network to users to use, share and enrich. • Measure knowledge in value terms for its utility and performance. • Validate it for its continuity in the organisation’s database and repositories. • Create intellectual capital and convert some into intellectual property. This definition of KMS is extended to include the integration of knowledge in business operations and decision making systems. Integration is done through business rules, models algorithms, formulae, and so on, embedded into the decision making framework. The distinguishing features of KMS are: • Purpose It has a clear purpose to exist and grow. It has a place in the organisation due to its justified business case. • Context The system is required for knowledge creation, its organisation and its application in solving business problems. • Scope The scope of KMS includes the management of knowledge and its enabling IT infrastructure. The scope of KMS is limited to the organisation and its business needs of knowledge. • Processes KMS detail processes are identification, creation, capturing, acquisition, selection, valuation, structuring, formalisation, visualisation, transfer, distribution, retention, maintenance, refinement, revision, evolution, accessing and retrieval. • Participants KMS users are knowledge workers with differing backgrounds and experiences. They play their managerial role by involving as participants in knowledge networks and communities. They are users as well as contributors to knowledge growth. • Use KMS business use is made by communities, virtual organisations and societies to extract and generate knowledge for business application. • Design KMS design is open to change with changing needs of the business. It is flexible and caters to the needs and capabilities of the users of knowledge. • Drivers Business strategy, technology and competitive pressures are the drivers of KMS. Figure 4.2 shows the generic model of Knowledge Management System in an organisation. The generic KMS model considers dynamic business environment as the basis for developing KMS. KMS is a set of processes and tools which give the ability to the organisation to leverage and combine the collective abilities created out of knowledge workers, experience. KMS provides a structured way of capturing knowledge that exists within the organisation; it gives the organisation the ability to improve productivity and knowledge of its employees by means of knowledge sharing. The people organisation and process flow for KMS are shown in Figures 4.3 (a) and (b). It is imperative that the management recognises KM as an important function; it needs a separate organisation for managing the KM lifecycle. The Chief Knowledge Officer (CKO) head this organisation.

Impacts

Dynamic Business Environment

Knowledge Driven Competitive Business Strategy to Manage the Impact

Needs Organisation’s Business Operations and Performance

Needs Support of Knowledge for Development of Strategy, Competitive Advantages, Differentiators

Create IC and IP

Identify Knowledge Validate

Revalidate

Create KMS Acquire

Measure

KMS Process Flow Starting from Identification of Knowledge to Archive

Transfer to Use

Fig. 4.2

Generic Model of Knowledge Management System

CKO

Knowledge Developers, Teams

Knowledge Managers

Knowledge Users

Experienced Knowledge Usage Feedback

Fig. 4.3

(a) People Organisation

CKO supported by knowledge teams, experts and specialists, knowledge processors and knowledge users (Figure 4.3(a)). Knowledge teams are responsible for building knowledge bodies, such as customer knowledge, people knowledge, process knowledge and technology knowledge, and recommend them for knowledge processors to process and manage for ease of use. Some knowledge bodies together may become knowledge assets. Knowledge teams include Communities of Practices (CoP).

Recommends for Use Identify Create, Validate Acquire Exchange

Teams

Creates Usable Knowledge Assets

Processor, Managers

Knowledge Assets Use Knowledge

Teams

Organise, Maintain

Users

Exp. Knowledge Usage Feedback for Improvement or Revalidation

Fig. 4.3

(b) KM Process Flow

Knowledge users are the actual beneficiaries of KMS. Their intelligent use of knowledge and knowledge assets creates live experience about its effectiveness in practice, directly or through being embedded in DSSs. This experience is regularly fed back to knowledge teams for improvement, or for revalidation of the knowledge assets in the changed business environment. In competitive business, sustainable knowledge advantage is not for long. A process in KMS must exist to validate and revalidate knowledge in the context of competition as well as changing business dynamics. In the organisations, where knowledge is being evaluated continuously for its currency, knowledge database is under constant updation and is current. Figure 4.3(b) models the KM process flow from identification to store to share with the users. Knowledge teams, that interface with the external world and track and monitor internal business management, issues, challenges and search for knowledge based solutions, manage the KM cycle. They justify and certify knowledge for use and recommend it to knowledge processors and managers who put it in proper shape and store it in the knowledge database for users to access. The users use knowledge in its given from or use it to build knowledge products and assets. After experienced usage of knowledge, users sense whether it is still effective or requires rejustification for use. At this stage, knowledge teams take over and resolve the issue about its continuance in the knowledge database. The knowledge organisation, in the integrated manner has three components, namely: • People organisation CKO, knowledge teams, knowledge users • Process Identify, validate, create, organise, store, measure, revalidate or improve • Drivers Competition, business strategy, technology, work culture, threats to business The most important drivers are the threats to business and competition, that put pressure on the management to develop competitive business strategies to maintain business leadership and to introduce new competitive advantages. And this needs to be achieved in the changing business environment. Another significant critical change in the business management process is a paradigm shift from achieving financial results to achieving performance excellence. If this approach has to be cultivated systematically organisations must recognise KM as the key critical function and formally establish a well designed Knowledge Management System (KMS). The concept is modeled in Figure 4.1. Let us now elaborate the processes to understand the KMS model.

KNOWLEDGE MANAGEMENT SYSTEM: DEVELOPMENT CYCLE Identify Knowledge This is the first step in the system. It examines the present knowledge base to see if it is adequate or new knowledge is to be searched to take the new strategy approach. The search for new knowledge becomes imminent because the world around is changing or has changed. The change in environment may call for a new set of competitive advantages to make it an undisputable differentiator from competition. The knowledge body is never static in business, and for the people in the organisation. The current knowledge may no longer be relevant to face the competitive challenges. The five knowledge areas may call for a re-look from the business strategy view point, to confirm its effectiveness. It is not just to confirm the adequacy and deffectiveness of the existing knowledge portfolio, of the last it is to search for new knowledge as additional weaponry to design the new strategy. A quick review of the last five years of changes in the five knowledge areas will justify the step of knowledge identification in KMS. The management focuses on five knowledge areas for developing business strategy creating a competitive advantage. • Customer knowledge • Product and service knowledge • Process knowledge • People knowledge • Technology knowledge The organisations continuously research in these areas of knowledge to assess whether the current business strategy needs reassessment and a new design to keep business on growth path. It examines whether present competitive necessities are effective and whether new set of competitive advantages need to be worked upon to maintain the leadership in the business. Customer Knowledge The customer knowledge is all about different segments carved out of customer population based on different socio-economic conditions. The customers in each of these segments may have different considerations while demanding products and services. Hence customer behaviour in each of the segments would differ. Customer knowledge about choices, and preferences, therefore, needs to be continuously searched to ensure that the communication strategy and associated supportive strategies are built on a strong footing of current requirements and expectations. Product and Service Knowledge The customers demanding value for money. They want faster delivery cycles. The offerings (products and services) should not only meet in functional needs, but should also have smart features to make them efficient and effective. The customer choices are changing fast because of online access to the world market information. The demands are becoming more precise and focused on key functions. Customers want more automated products and services. They prefer products and services which require less maintenance, less power and much less service; that are user/customer friendly. Process Knowledge Process technology is undergoing rapid change. The process, for that matter, any process, should be lean and flexible. Process productivity should continuously rise so that the cost is reduced. Process knowledge means having knowledge of latest technology which drives the process. The knowledge also includes the bench mark which the process designer should aim at to achieve. Process knowledge means the current measures in terms of cost, cycle time and quality of the process versus the bench mark.

People Knowledge The people here mean people in the organisation who are driving and executing the business and its processes. People knowledge means their capability and capacity to face the challenges, and their ability to manage the change effectively. This knowledge portfolio includes subject, function knowledge, and social and technology skills. They should be creative and innovative to develop new strategies to meet the challenges of the changing business environment. People knowledge is all about who is who and what knowledge they have.

Technology Knowledge Modern business is driven by technology. It is an enabler to make systems and processes efficient and effective. It helps to solve number of issues, like better use of resources, quick communication, prompt deliveries to customer, monitoring and tracking of events, and so on. The organisation must have up-to-date knowledge of current technology, and also of the emerging technologies, so that they can be deployed for leveraging the benefits. In the process of identification of knowledge what is being achieved is the search for knowledge which could be useful in the identification of problems due to the changing business environment, and the probable knowledge driven strategies which could overcome these problems on implementation. It is expected that the knowledge search would help to develop the winning strategy. The winning strategy uses ICT to transform the organisation into the result oriented process organisation. Figure 4.4 shows how winning strategy encompasses the organisation, ICT, and Business Processes. ICT Driven Processes Organisation

ICT

Computers Networks Winning Business Strategy Driven by Knowledge and ICT

Internet Intranet Servers Desk Tops, Cell Phones

Knowledge Database

Fig. 4.4

Enterprise Software, Knowledge Databases

Winning Business Strategy Formulation and Implementation

Winning Strategy Formulation Winning business strategy in competitive business is the one which is evolved by considering the five knowledge areas and supporting knowledge strategy. The most important two factors for business strategy to succeed are the Information and Communication Technology (ICT) platform and the ICT enabled processes supporting business strategy implementation. ICT driven processes should be such that

• They are intelligent, i.e., decision making in the process is knowledge triggered. • They are lean and reengineered using ICT. • The process network is productive as processes are linked or connected satisfying the start conditions, end conditions and constraints.

Validation of Knowledge Validation of knowledge is the next step in KMS. The objective of this step is to confirm the relevance, utility and application of knowledge to current problems of the business. In the first phase, we have identified the different knowledge areas, entities to focused upon. This is an important step to justify the business case for designing KMS and KMS initiative. Suppose the area of search is customer knowledge which includes such things as different segments, their purchasing power, customer density in each segment, decision makers (individual, family, group, or one specific family member), choices, preferences and priorities, factors developed by Maslow—basic survival needs to self esteem and so on. Though all this is relevant and useful one should focus on validation of the ‘knowledge’ which is a doubtful case of inclusion in the knowledge base. It is economically unviable and a wasteful exercise to collect the knowledge which prima facie looks useful and relevant. In the validation phase, identified knowledge cross checked with current problems, probable solutions, future trends and the likely strategy approach required to move ahead. This cross check shortlists the knowledge which KMS should pursue to gain and consolidate. It is difficult to establish a close correlation between ‘problems and knowledge-strategies. A broad view is necessary to begin with to be confirmed later on with some experience. Also, it should be noted that some knowledge is absolutely necessary and some could be of questionable utility.

Create Knowledge Creation of chosen knowledge is the next step. Identification and validation of knowledge. Creation includes number of strategies. They are: • If knowledge already exists outside the organisation, it needs procurement. It can be done by purchasing from research bodies, paying consulting organisations to provide knowledge by capturing through systematic methods, such as surveys, test exercises, simulation models and so on, building alliances with the partners who possess it and are willing to share, and so on. • If knowledge already exists within the organisation, it needs processing to gather, capture. The organisation possesses knowledge and is also aware where it is stored in the information systems, files and folders. A system is needed to process these sources of knowledge to produce it in the required form, to store and share. For example, an organisation has a data driven or transaction driven CRM system. Customer knowledge is hidden in various records, files, folders and databases of this system. Having identified it, an information system is required to process the data to create customer knowledge. • Knowledge does not exist, it needs a design of experiment to build. There is a possibility that the identified knowledge does not exist in the organisation or not available from external sources. The only alternative is to design an experiment around the subject of concern and conduct for a large sample size, or for a reasonable time period, to generate input-output data. This data, on analysis, would provide a new insight in to the problem and, may throw up some guidelines on resolving the problem. Hence, new knowledge is created.

Market research, test marketing of products, strategy, and customer feed back gathering, experiments in Agro business for testing the properties of chemicals and fertilizers on various soil conditions, test runs of plant and equipment are few illustrations of experiments to gather information and knowledge. • The Approach of collection and formulation is necessary when knowledge is not available directly, as seen on designing of experiment or processing of existing data to reveal knowledge. In this process, existing knowledge is sourced from various sources and assembled to construct a programme, an algorithm, a formula or a model. Most of such knowledge results turn out to be an asset for the organisation, are tools for intelligent business processing. Typically most organisations have built Excel Spreadsheet Models for data analysis, decision support, forecasting and so on. These models import data from back-end systems and servers. Hence, data is current, and the model gives knowledge driven results to implement. The organisations have built Operations Research Models, Financial Analysis Models, Resource Allocation Models, Project Management Models and so on. The competent, knowledgeable experts and specialists have extensively used modeling as a tool for developing such products. • The approach of collection and presentation is taken when knowledge elements already exist but are distributed in different files and folders and are not accessible to the users. As a result they have lost their knowledge value. ICT provides intelligent processing support to assemble these knowledge elements in a knowledge product. They are also presented using multi-media tools to make them interesting. These products use audio-video clippings, animation and gaming techniques, image processing and so on, to make knowledge products effective tools of knowledge processing and dissemination. E-learning products, knowledge portals online maintenance manuals are examples of such knowledge products. These products are created and posted on the portal or are available on the intranet. Figure 4.5 models the creation process in detail. File and Folders

Book

Experts Organisation

Data Bases and Repositories

Fig. 4.5

Creation Processing: Acquiring, Fetching Data and Information, Grouping, Analysing, Assembling, Formulating, Experimenting, Presenting

KNOWLEDGE MANAGEMENT SYSTEM: APPLICATION CYCLE Knowledge transfer is the step taken when knowledge, knowledge objects are finalised for delivery to users. The transfer takes knowledge to the user and stays with him for use by choice. Sharing is a step where

knowledge is at one location and access is given to authorised users for use as they like. Knowledge transfer is done in a number of ways. Some prominent ways and mechanisms of knowledge transfer are: • Working together Internal consultants, personnel transfer, on-the-job training, hand holding, informal visits and chats, mentoring. • Communicating through formal channels E-mail, fax, telephone, video conferencing, E-manuals, posting on knowledge portal. • Creation of socialising opportunities Form communities of practice and interest, conduct workshops and seminars, get togethers. • Codifying knowledge for ease of transfer Make Rules, Policies, Build protocol, procedures, models, programmes etc. • Use data management technologies Develop knowledge bases, data warehouses, knowledge repositories. Knowledge, when created, goes to knowledge repositories and then is handled through transfer process. In some cases, it is transferred from individual to teams. In case of tacit knowledge, the transfer is a daily routine, though not systematic in the formal sense. Most of such transfers are at will and by choice of the user and the person who possesses it. Knowledge also present in databases, warehouses, books, programmes and so on, is also transferred to users. One of the prerequisites to knowledge transfer is codification of knowledge which makes management of knowledge efficient and effective. The code is of two types, the first identifies of the knowledge and the other signifies its type, kind, domain and format. For example, if knowledge relates to customer requirements and is explicitly expressed in relation matrix then relevant identifications keys are put into the code. Three entities are involved in the transfer of knowledge. They are source of knowledge repository and the media holding it, methods of transfer and recipient, a user or knowledge worker. Figure 4.6 shows the flow of knowledge transfer. Source of Knowledge Expert, Specialist, Domain Expert, E-Books, E-Manuals, Databases, Knowledge Bases Functional Repositories, Digital Media

Fig. 4.6

Transfer and Sharing Methods

Recipients

Download, Transfer on Demand, Automatic Transfer, Group Meetings, Individual Interactions, Working Together, Mentoring.

Authorised User, Decision Maker, Knowledge Worker, Database, File, Folder, Data Warehouse

Flow of Knowledge Transfer

Sharing is the process of transfer where experts share knowledge on demand by the user. This may happen if the expert has no issue in sharing it, or he welcomes the sharing in the interest of the organisation. The transfer or sharing operation takes place on the network, supported by internet, intranet and web portal. The transferred knowledge, or shared knowledge, may or may not be used by the recipient. The application or adoption in any manner is not automatic; it is at the will of the recipient.

Measuring knowledge adoption is the next step in the second phase of KM. Since the use of knowledge is at will, it is necessary to have periodic review meetings Formal-informal interactions, seeking feedback on the benefits, auditing the incidence of use are some methods. Another reason to measure knowledge adoption is to check whether knowledge is contributing any economic value or not. If not, it is better to declare it as obsolete and delete it from KMS. If it is contributing high in value terms then it has become an asset to the organisation. Some assets in this category could be intellectual capital giving competitive advantage to the organisation. Some may be contributing to the building of brand image of the organisation, thus raising its market value. Measuring knowledge also reveals whether knowledge is being put to use for generation of creative, innovative ideas. In other words, this step revalidates knowledge for continued use by value criteria. The step also selects the knowledge asset that is to be protected by the trademark, licensing mechanism, and finally by declaring that knowledge as intellectual property of the organisation. The third step in the second phase of the cycle involves converting selective knowledge assets into intellectual capital and further declaring some as intellectual property of the organisation with trade mark declared, patent registered, and so on. This is necessary as this knowledge asset provides competitive advantage to the organisation.

Knowledge Management System: People, Process and Technology Interaction Knowledge management system is all about managing interaction of people, processes and technology. All the three are drivers of each other. Figure 4.7 shows the interaction of People, Processes and Technology which results in knowledge. KMS manages this interaction where the three have a close association, relation and dependence. People Interaction Processes

Fig. 4.7

KMS

Technology

Generates

Knowledge

People, Process and Technology Interaction

In people process interaction, process operators identify the bottlenecks holding the process, process inefficiency causing delays and quality problems and knowledge gaps in operators which require training and guidance. This exercise of solving process problems adds to the knowledge of process designers, which emerges out of experience of applying existing knowledge. In people technology interaction, people learn the capability of the technology and its effectiveness in delivering the outcome in an efficient manner. This knowledge is captured and used in other process reengineering projects. The interaction also creates knowledge about limitations of technology in solving problems. It also throws light on economic viability and feasibility of technology implementation. Process

technology interaction develops the norms and standards of application and the results it offers. Knowledge also is gathered about choice of technology versus process in question. In all interactions, people who are managing the knowledge and people who are manning the process learn a lot, initially at the time of selection of technology, then by application experience of technology. It is by now established that technology drives the process efficiently and effectively. The process results and its performance throw light on a number of issues, teach something new, develop insight, and so on i.e., people acquire knowledge from interaction. For example, technology driven CRM process generates a lot of results and acquire information on key performance indicators (KPI) while delivering the service to the customer. The people managing CRM function capture these results and KPIs, analyse them to research meaning of ‘customer behaviour’. In other words, this interaction generates customer knowledge about choices, preferences and unarticulated requirements. The physical view of KMS model is given in Figure 4.8. The business systems driven by technology generate data and information. KMS processes this data and information to measure the operations results and business performance, and compares with targets and KPIs. When this outcome is analysed, applying theory and principles, functional knowledge and experiential wisdom, knowledge components are produced.

Capture Data and Information Apply Principles, Theory, Functional Knowledge Use Experiential Knowledge

Process Data for Performance Information and Assess the Knowledge

Generates

Knowledge Components

Process Knowledge Components Produces

Knowledge Assets, Knowledge Products, Actionable Knowledge

Fig. 4.8

Physical View of KMS

These knowledge components are processed further to build knowledge products and knowledge assets. For example, technology driven CRM applications generate knowledge components, namely customer knowledge, product knowledge and unarticulated requirements expressed a number of interactions. These knowledge components are processed further to find new product features. Such features are the new revelations, actionable knowledge for product redesign.

CHALLENGES IN DEVELOPING KMS We have said that knowledge is the creation of interaction between people, processes, and technology. While technology is an enabler, people and processes are the drivers. Their interaction is not natural and straight. There are a number of challenges. The first challenge is organisation culture which has emerged over time. People are accustomed to working in a particular fashion, more information driven and less dependent on technology driven DSSs. The organisation culture is unable to keep pace with the changing dynamics of business. The realisation of knowledge as a power to face competition is not immediate. Changing the mindset of key people who are accustomed to hoarding knowledge is a difficult task. However, this is not impossible to achieve if proper and adequate incentives are offered to people. The fear of challenge to their position and power needs to be handled effectively by the recognition and reward system. The second challenge is creating faith in the paradigm shift from information to knowledge driven processes. The lack of faith in knowledge as a power poses serious problems which are tougher when knowledge is embedded in management processes and systems. This creates a power vacuum and people start showing lack of faith in the knowledge and knowledge driven systems. They challenge knowledge itself. The solution to this problem lies in creating a strong justification in knowledge which is generated out of business case. This is more a implementation issue of tackling the organisation culture, people mindset and lack of confidence in technology. The third challenge is ease of access to knowledge and its usage. This challenge is about how KMS manages key processes, namely, store, share, transfer and access to knowledge. The decision makers, knowledge workers, tend to move away from KMS if access to key information and knowledge is time consuming. Further, KMS is silent on how knowledge should be used. The factor of faith discussed here becomes dominating. It is important KMS design and architecture that address these issues effectively. KMS must ultimately demonstrate the relation between Knowledge – Problem – Usage – Experience. Revitalization of knowledge is a core area of KMS. This is a continuous process as shown in Figure 4.9. Revalidate Knowledge

Current Knowledge Database Usage

Experience and Confidence in Knowledge Usage

Problems

Redefine the Problems

Fig. 4.9

Knowledge and Problem Relation Revalidation

Evaluation of Knowledge Effectiveness

The continuous revalidation of knowledge and redefining the problems keeps the users’ confidence in KMS. The process also helps in enlarging the scope and content of the system. The fourth challenge is KMS implementation. Its implementation without the top management recognising it as key function like finance or manufacturing, is destined to fail. Secondly, the contributors to knowledge enrichment must be committed to KMS. Further, implementation without solving people issues is bound to face tremendous problems. KMS today is a technology enabled system but essentially it is a people driven system. Successful implementation begins winning people’s mandate and results in awareness and expertise in technology.

KMS LIFECYCLE KMS lifecycle (KMSLC) is similar to Software Development Lifecycle (SDLC). KMS lifecycle deals with identifying the requirements of knowledge and making a business case for such system. It essentially finds the problems, challenges, issues in business and the knowledge required to solve them. It also addresses the justification of KMS by identifying the benefits of such system. Then, it looks into the organisation required to build such system. KMS lifecycle focuses on strategic planning and justification for KMS development and the processes for building it. SDLC contains the following steps—‘Need for the system, Requirement study, Feasibility study, Building RDD and SRS, High levellogical design and architecture, Coding, Testing, User training, Implementation, and Maintenance. KMSLC runs on similar lines as shown in Figure 4.10.

Identify the need of knowledge for superior business performance

Fig. 4.10

Make a business case for justification of KMS

Obtain management approval

Form a KMS development group

Identify broad knowledge areas and consult users and knowledge workers for their opinion

Establish its need versus business strategy. Confirm the linkage between strategy and knowledge

Identify sources of knowledge and capturing strategy

Develop a plan of KM Development and its budget for approval

Revisit the justification of business case for KMS versus the budget

Decide on technology, process design and development strategy

Develop KMS engaging KM development group

Implement and test KMS in live mode. Revise modify/change

Make modification, corrections and freeze KMS

KMSLC Model

Let us discuss these steps in detail.

Identify the Needs of KM System In this step, we confirm that competitive pressures in business are demanding more systematic handling using knowledge, and not just information. It is assumed that the organisation has a formal MIS supporting business decisions. But now, business performance issues are more prominent than business operations management. Elaborate analysis of this aspect and immediate business performance management needs would identify the needs and the KM system required to be developed.

Make a Business Case for KMS A business case for KM initiative means confirming economic justification for investing in KMS. Further confirming that (Return on Investment) ROI is very attractive because of the huge benefits owing to moving from information driven to knowledge driven strategic decision making. The benefits are due to improved control on business performance while achieving better management of operations of the business. Knowledge and business strategy are closely linked.

Obtain Management Approval Obtaining management approval means management support to KM initiative in the organisation. Such approval from management saves additional efforts of budget allocation to this project. Such approval by the management sends clear message in the organisation that paradigm shift from information to knowledge driven is a certainty. The organisation should accept this change and participate in KM development.

Form a KMS Development Group Forming a KMS development group is a stage where a team of experts and specialists from all disciplines are brought together to take up the knowledge initiative further. These personnel are selected from all levels and from all departments of the business. This is essential as, so far specific knowledge need has not been fixed. This team is responsible identifying for specific knowledge areas which make business sense from the strategy view point. Once the knowledge areas are decided, this team undergoes a critical change in content, scope and expertise.

Identify Broad Knowledge Areas—Consult Users Once the knowledge areas are identified, they need to be opined by the users of knowledge. The key users and knowledge workers debate search of knowledge to be developed through KMS. Users confirm and validate the knowledge specifics and areas. They also confirm its consistency with business strategy plan of the management.

Establish Knowledge Needs versus Business Strategy—Confirm Linkage Between the Two KMS is successful if business strategy, identified knowledge and business benefits, in terms of performance and operations, are clearly seen as linked in the KMS, and are consistent and supportive to each other.

Identify Sources of Knowledge and Capturing Strategy Having confirmed the knowledge needs for achieving business excellence, the next step is to identify the sources of this knowledge, to capture then to process for further applications. Knowledge may have a source internal to organisation or to be procured from external sources. KM development cycle handles this critical requirement of fetching, processing, validating, and converting knowledge into knowledge elements, knowledge products and eventually knowledge assets.

Develop a Plan of Development and its Budget By now, most of the specifics about taking the KM initiative forward are ready. The development group can estimate the cost of development, resource needs and total budget for the development.

Revisit the Justification of Business Case for KMS The development team leader then makes the presentation to the management, seeking budget approval and support to the development team to launch the KM and its development project. The presentation revisits the business case for KMDS justification to obtain the approval from the management.

Decide on Technology, Process Design and Development Strategy Once the budget is approved and top management support is ensured, the team gets into the exercise of specifying technology tools and networks, and so on. These details are worked out in precise terms. In this step, details of KM processes are worked out on the chosen technology platform. A thought on development strategy is also made to ensure that KMS initiative begins with a success note. Broad decisions on technology are already taken while estimating the development budget.

Develop the KMS KMS development is undertaken in a planned manner on the basis of development strategy.

Implement and Test KMS in Live Mode KMS is then implemented. A review of all basic premises is made to confirm that what is being developed meets the business objectives, i.e., strategy linkage to knowledge is appropriate.

Make Modifications, Corrections and Freeze KMS In this review, some modifications to KMS are expected. KMS design is then frozen for a planned period of four to five years. In this discussion, we have made reference to two individuals, knowledge user and knowledge worker. There is a critical difference between the two, but both are participants and users of the system. We can outline the difference in the following table. Attributes • Contribution to KMS • KMS user

Knowledge Worker Kowledge and experience Not always

Knowledge User Information on usage Always

• Participation • Knowledge • Ambiguity

In initial stage Contributor Can tolerate

Throughout User Cannot tolerate

• Role

Verification, validation

Usage with feedback

In KMSLC, system justification,which makes a business case for knowledge management, is an important step, taken quite early in the process. KM system’s purpose is to impact business strategy, and improve productivity and effectiveness of the people in the organisation. The system justification has two dimensions, financial and its utility to the organisation. Financial dimension is relatively easy to study and understand to prove that the system need is imminent, and would provide substantial gains if right KMS is developed. The second dimension utility to the organisation, is established by linking vision and business strategy to performance of the organisation and then identifying the knowledge, which would support the strategic decision making in key result areas of the business. If this chained linkage between the three is positive, the KMS is justified in the organisation.

126 Knowledge Management

In this regard the role of strategic planning is important. Once the business strategy is decided and approved by the management, the next step is to prove link with KM. For example, if your business strategy focuses on customer satisfaction and evolves different strategic actions to improve it by improving quality of the product, faster service and delivery, continuous upgradation of value addition, the knowledge which you would identify will be in the area of R & D, customer expectations, process knowledge affecting and impacting customer and so on. Many organisations conduct ‘gap’ analysis in this chain and develop a suitable KM system for the organisation.

KMS Feasibility It is essential to confirm that KMS is feasible to develop and would ensure business benefits. The feasibility has six dimensions, namely • Is it doable to achieve the business goal? • Is it affordable? Is ROI attractive? • Is it appropriate for the goals to be achieved? • Is it practicable in the organisation? • Is the organisation ready to move to KMS? • Is the ICT infrastructure required to run the KMS available, or can it be installed?

User and Stake Holders Support The users and stake holders are the main beneficiaries of the KMS. So to begin with, this group must feel the need of KMS to improve their performance and also of business performance. The best way to sell the KMS idea is to build a case for its need. This approach can be built by convincing the users that the business management approach in the globalised world has changed. The business has become more risk prone and needs knowledge based solutions. It should be explained link between business goals, business strategy and KMS is critical, and is a key success driver. This approach would succeed in getting users support in KMS development.

Forming a KM Team This team, when formed properly, is an asset for KMS. Team members are to be drawn from various sources within the organisation. They possess business knowledge and have experience in solving the problems. They are aware of the individuals who possess tacit or explicit knowledge. The composition of such team would have following personnel, namely, intelligent users, experts and specialists—strategy managers, technology experts, and so on. Team size cannot be recommended as it emerges out of the necessity of KMS. In this team a couple of individuals play the role of the knowledge developers. Knowledge developers are central to KMS development. They give shape to knowledge, as discussed earlier. See Figure 4.11.

KM SYSTEM ARCHITECTURE The KMS architecture is factored into three main modules, identification, creation and delivery and service. The knowledge workers responsible for these modules are experts in business management for identification of knowledge, manager technocrats for creation, and handling of knowledge and experienced knowledge workers for enrichment, service and maintenance of knowledge. We now look at KMS architecture given in Figure 4.12.

Provides Knowledge Knowledge Providers

Shares Experience

Top Management

Consults

Acquires Knowledge Developer

Provides Feedback

User and Stake holders

Feedback

Knowledge Database: Assets and Products

Fig. 4.11

Role of Knowledge Developer in KMS KMS

Identification

Definition Search and Locate

Validate and Structure

Fig. 4.12

Create Knowledge Elements

Deliver to Network System and Communicate to Knowledge Workers

Process Elements To generate Usable Knowledge, Knowledge Products and Assets

Create Access Control for Usage and Ownership Rights for Revalidation, Enrichment

Move to Knowledge Database (KDB)

Design Applications for Posting on Knowledge Portals

KMS Architecture (Process view)

From the user point of view KMS infrastructure has seven layers.

User Interface or Web Browser Layer Web browser is installed on each PC, and on other hand held devices. This is the first layer between the user and the KMS. The user is not exposed beyond this layer. While designing user interface, the features which make UI operationally efficient should be included. The first one is consistency in screen design, that is menus, icons, buttons, colour scheme and, captions. The layout should be of same design throughout the system. While finalising these features, future expansion and enhancements should be also considered.

UI design should be such that all relevant information is displayed on use. This helps the user to customise or personalise it. Next feature is responsive clarity of screen display. This is actually part of screen layout design. It should be ensured that display is total and is accommodated in one screen. Scrolling should be avoided. Pull down menus should be there by default. Proper use of colour, margins, lines and shades brings clarity while viewing the screen. It is universally known that not more than 8 seconds should be taken by the user to read the screen display. The navigation through web pages should be smooth and easy. The navigation process should not require the user to go forward and backward time and again. And, finally, usability which encompasses many more things should be to user’s expectations and liking. It is an acid test of efficient UI design.

Security Layer This contains authentication, non-repudiation, firewalls, proxy servers, user identifications, their rights and privileges to access, read, write, edit, etc. Fire walls are installed to ensure security by checking and verifying each entry and exit of files, data, or any other document. Passwords, administrative security rights, and such as access to read, write, edit, etc., classified information and knowledge are given to designated users. It is an authorised access layer for accessing knowledge stored in repositories through organisation’s Intranet. The Extranet is an extension of intranet through firewall, whereby authorised suppliers, vendors, stake holders have access to information and knowledge stored in databases and repositories. Firewalls are hardware and software to define, control, limit access to networks and computers. Most users know conventional security measures which are also used in web enabled KMS. A firewall is a hardware software tool which is installed between KMS and other enterprise software to prevent some ‘marked’ information going out and being accessed by unauthorised users. They also block the entry of viruses, intruders which would affect information and knowledge files. They not only protect, they create a report for the system administrator to take action where necessary. Use of biometrics, that is, voice and finger prints for authentication and identification is gaining popularity. It is assumed here that the organisation has bigger and wider security umbrella, which protects from events like thefts, fire earthquakes and physical access to servers, etc., by appropriate security strategies.

Dissemination Layer It contains tools and technology to filter and segregate into news, mails, warnings, alerts and official notifications. It does the job of providing personalised information and knowledge. Intelligent Agent, special software, does the job of quick searches in databases and repositories to send the information and knowledge to the user in the form requested. This layer’s main role is to reduce search time for the task the user has requested. Intelligent Agent is an active software object capable of perceiving and reasoning the user’s request and make searches to produce most satisfying information or knowledge for the user. Suppose the list of employees is requested by both the workshop manager and the HR manager. Intelligent agent for workshop manager would display the list with employee technology skills and it would display the list of employees with grade, and date of joining to the HR manager. The key components of this layer are: 1. Search engine to find the information, such as subject, words or information on query. 2. Membership creation by specific user services, such as news group, community group by practice, on site service schedules of different mandatory actions, customer support services, and so on.

3. Directory of tailored information based on user’s operational and professional behaviour. For example, such directory would have information of employees by skills against the user, works manager and list of employees by grades against the HR manager, with supportive relevant information.

Application Layer It contains Video conferencing, Groupware applications, synchronous and asynchronous, Yellow pages, Decision support tools, and Knowledge bases imaging tools. This application layer enables the user to do the job in a better way. For example, at a project site, a problem needs immediate solution. The parties involved are the Site Engineer, Materials Manager, located at the site, and Project Manager and Manager Engineering are at different locations. They can use video conferencing application to discuss the problem and resolve it with no more delay. Knowledge database, material database and engineering drawing database is available to all. Repositories about case history are also available to verify what was done in similar cases.

Information Exchange Layer This contains TCP & IP, E-mail and Document exchange, and it manages the network of the organisation. It manages the transmission of information and knowledge flow between computers on the network. This layer is made of LANs, WANs, intranet, extranet and internet. The layer is suitably equipped to manage network traffic flow using existing bandwidth, connectivity tools and URLs.

Middleware Layer It contains specialised software for network management and network security. This is important when the user wants information and knowledge from legacy systems developed on different platforms. This layer interfaces with legacy system’s databases and records which may be in a different format.

Repositories Layer It contains legacy applications, enterprise software and their files and folders, databases, data warehouse holding knowledge and rules, procedures, algorithms, models and case histories. This layer is responsible for data transmission on request by the user or client. Once the repositories are formed, they are linked to form about a integrated repository. For example, if query is customer problem, its solution might be in customer knowledge repository, but if it requires process knowledge, integrated repository displays both these knowledge sets in the format the user has asked.

KNOWLEDGE CONSTRUCTION ARCHITECTURE Every organisation has knowledge concealed in files and folders, and also with the people who have been with the organisation for long. People individually enrich their knowledge as their experience of knowledge application increases over time. Knowledge is resident in many sources within the organisation. Some knowledge is to be procured or acquired from outside the organisation. Knowledge could be the creation of an individual. It could be within the team repeatedly engaged in some activity. This knowledge is out of systematic collaborative activity of the team. The organisations engaged in project activity have knowledge distributed in the team. The organisations, like L&T, ONGC, real estate developing companies, ISRO, hotel chains and so on, are examples of organisations possessing collective knowledge—held by individuals as tacit knowledge and in files and folders, servers and databases as explicit knowledge. Knowledge held by the organisation needs to be created systematically through KMS. Figure 4.13 shows the model of knowledge creation cycle through KMS.

Initial Knowledge

Gathers Knowledge Application Experience

Knowledge Application, Problem Solving

Knowledge Terms Update Initial Knowledge

Fig. 4.13

KMS

Knowledge in Documents

Knowledge in Data Files

Extracts

Knowledge Creation Cycle

Implicit in this KMS cycle is an assumption that the knowledge team would transfer and share the renewed experience as knowledge for common good of the organisation. This may not happen in a routine fashion through KMDS. Like KMS, knowledge also has architecture. It is a prerequisite to the knowledge creation process. Earlier we have said that the knowledge is an outcome of interaction of people, process and technology, as expressed in Figure 4.14. People

Process

Technology

Fig. 4.14

Knowledge Creators and Drivers

People are the creators and owners of knowledge. The experienced interaction of these three components creates knowledge and further improves it. Their experience adds value to knowledge. Technology is an enabler and driver of knowledge management. People include all types—managers, officers, workers and staff members. All gather knowledge in their fields of operation through work experience and interaction with fellow employees and their counterparts in other organisations. Knowledge architecture is built out of three components—knowledge areas, knowledge centres, and knowledge owners. KMS is built on this architecture. Knowledge areas are the ones which the organisation has identified as the need of business for superior business performance and also for building business strategies to achieve such performance. Knowledge centres are the physical locations where knowledge is resident. The centres include people, files, folders, documents, servers databases and repositories. Knowledge owners are the people at all levels who know ‘Where is what’ of knowledge. They are experts by experience. Let us take an example of the process knowledge which the management has identified as the need of the business to achieve superior performance through better quality product, less customer complaints, faster delivery, reduced cost due to lean and flexible processes. Process design knowledge is present in process diagrams, specifications, required tools and technology, process input-output data and benchmark. Process operations records contain process operations and performance knowledge. Process personnel, along with other team members who include CRM manager and

Knowledge Area

Knowledge Centres

Interaction Knowledge Owners

Process Design Knowledge: Process Diagrams, Process Specifications, Tools and Technology, Process Quality results Process Strategy, Process Goals Process Efficiency Process Cycle time Process Bench mark

Process Operations Records and Customer Responses: Work Shop, Delivery Systems, Customer Feedback, Customer needs Articulated and Not Articulated Competition

Process Personnel Process Planner, Process Designer, Proces Operators, QA Personnel Process Community

Knowledge Created By

Process Knowledge Team

Knowledge Repository

Process Performance Knowledge: Tacit and Explicit

Fig. 4.15

Example of Creation of Process Knowledge

QA chief, extract knowledge, tacit as well as explicit, and store it in knowledge repositories. When customer demands something new, or complains about product performance, process personnel refer to knowledge repository and try to fulfill customer demand promptly. Failing to do so, they go back to process knowledge team to resolve new demand. Figure 4.16 shows inhibitions to knowledge sharing. HR Inner Thinking: • Compensation • Recognition • Ability to Articulate • Job Security • No Challenge to Power • Proper Support Structure • Conductive Work Culture

Fig. 4.16

Impacts

Inhibitions to Knowledge Sharing

Knowledge Sharing Attitude

Impacts

Organisation Culture

Knowledge sharing is most difficult to achieve. HR department and top management should make extra efforts to convince people that knowledge creation and sharing are good for company performance and eventually for their performance. This requirement is better fulfilled by creating knowledge in a particular manner, and presenting it uniformly in similar manner. Figure 4.17 shows knowledge content model.

Fig. 4.17

Knowledge Domain

Name Code

Mkt

Mkt 33

Knowledge Area

Application

Customer Service Feedback Complaints Suggestions Queries New Requirements

Storing and Solving Problems Action Taken Acted Upon Answered Noted For Modification

Knowledge Content Model

While putting knowledge in the knowledge database the following points should be taken care of to realise Business benefits and higher productivity. • Focus on real application oriented actionable knowledge give all references of owner, expert, contributor for communication in case of difficulty or doubt. • Classify knowledge in broad areas and mention name code of group member to attend, guide, develop, etc.

Network Through Internet Users on Extranet

F I R E W A L L

ERP SCM

KMS

PLM

CRM Legacy Systems

Users on Intranet

Fig. 4.18

KMS, an Integrated System

IMPLEMENTATION OF KMS Implementation phase is the last stage in KMS. At this stage, knowledge needs are identified and validated by the knowledge team and management has agreed to go ahead as business case is justified. The knowledge then is captured and coded and stored in the knowledge base resident on one server. Implementation phase contains three main tasks—KMS deployment, review of KMS while in use and maintenance.

On deployment of KMS, the system KMS team trains users in the system. User training covers presenting the system, explaining the details about design and architecture, and why KMS is important to them and business. Next step is putting users in the driving seat and hand holding when they are using the system. In this mode, users’ questions have to be resolved. Their suggestions and modifications are noted for consideration and implementation at an appropriate time with formal change management system. A well written user manual would be of great help to both the users and the KMS team. KMS training has two goals; the first is training on the system to use it effectively, and the second is training the user to become knowledge worker and knowledge contributor. They must appreciate the paradigm shift in business operations supported by KMS. They must accept the new work culture which is technology driven and knowledge driven. The business processes have shrunk, and work today demands collaboration and coordination across the departmental and functional boundaries. It takes time for usess to accept tools like video conferencing and Groupware technology. The experience of working with knowledge embedded system is new to them. Sufficient time should be given to create their comfort level. The change from information driven to knowledge driven is three dimensional cultural, operational and decision making. In knowledge driven operations, user empowerment is highest due to access to knowledge. They become solely responsible for decision making. All users may not be equipped to accept this change. The operations of business are now process driven, running across the organisation. Users must learn to accept process view and their role in the process. The appreciation of this role is important to make the process efficient. They must learn to work with Groupware technology, where process demands synchronous and asynchronous intervention by the users. This is a work culture change, both in style and operations. Unlike other software system implementation, the KMS needs to address some people related issues to ensure that users participate in the system willfully, and they make KMS rich and efficient. This resistance to change is very difficult to handle. It is never spoken but is expressed in different ways. First, approach and attitudes towards peers is non-cooperative and often hostile. Second, those who resist show indifference and tend to withdraw from any involvement. Third is taking an aggressive stand against the system and finding fault with what is being achieved. Fourth is use of personal power to divide the development team and slow down the process of development. The resistance to switch over to KMS comes from four quarters, experts and specialists, users in powerful positions, regular employees fearing they becoming redundant, and trouble makers.

Experts and Specialists They are domain experts. They have anxiety of sharing the knowledge, and also being responsible for right use by others. The empowerment which they enjoy is diluted but they have to continue to create knowledge based on the changes in business environment and the experience they gather from used knowledge by them and others. KMS project manager and HR head have to come together to handle this sensitive issue so that experts and specialists are motivated to participate in the system in different roles.

Regular Employees The role of regular employees changes considerably. The processes have become shorter and transparent to all process users. They are automated and only decision making is left with the usess. They fear becoming redundant eventually and loosing their jobs. This fear needs to be removed that their job is not at stake as their role would now be expanded with additional responsibility. Some would be elevated and some would be rewarded.

Users in Powerful Positions These users have assumed power by their experience, holding key positions in key functions in the organisation, and showing leadership qualities. KMS poses challenge to their status of and they thun create problems while implementing the system.

Trouble Makers Trouble makers are the ones who are left out of this shift. They suddenly become conscious about their positions, and take a stand by finding fault with the system. These employees are just users of KMS with no contribution to its development. It is necessary that the management take them in to confidence to explain the changes and assure them comfort in using KMS. These employees may not be covered by the reward and recognition system. Management must convey that their active use of KMS would improve business and financial performance and they would naturally benefit from the radical change. The solution to these problems requires the following; • Proper change management system to move to KMS • Strong case for justifying KM initiative and development of KMS • Involving personnel of the type discussed in the beginning to win over their whole hearted cooperation and participation • Evolving and declaring reward and recognition system simultaneously • Convincing key personnel that their professional growth would not be hampered, if they performed well they had high chances of growth • Convincing people in the organisation that the business compulsion to be ahead of the competition demanded systems like KMS

Test the System Step, the system is tested in live mode, when users are actually using it. Two actions are taken, verification and validation of the system from all angles. Verification confirms that the system is as planned in the system specifications, and needs no correction. The verification step includes confirmation of problem/solution association, and then, when called for the system displays it the format user has chosen. Though the system development is right, the validation step confirms that does the right job of application, producing the desired results. It meets the user and knowledge worker’s expectations. The validation checks confirm reliability of the KMS. Besides this, knowledge stored needs to be tested for the following aspects. • Reasoning Error Since knowledge is used for problem solving, it is necessary that the user does not make a mistake in ‘inductive or deductive’ reasoning. For example, ‘consumption of tobacco causes cancer’ is inductive reasoning. The error here is that this induction may lead to wrong action by the user, because causes of cancer are many, it is risky to use in KMS. In deductive reasoning, the deduction is scientific and logically deduced from confirmed set of knowledge. Here we use current knowledge to develop new knowledge. For example, all senior citizens get railway ticket concession from Indian railways (Knowledge 1). All persons beyond age 60 are senior citizens (Knowledge 2). Hence, Harish Salve of age 63 is eligible for railway ticket concession. • Incompleteness Knowledge presentation should be complete in all aspects, leaving no chance for the user to misunderstand and take wrong action. For example, product knowledge can be said to be complete if it displays quality specifications, user guidance, process of manufacturing and details of other inputs. Knowledge is incomplete if it is ambiguous. For example, process is faulty and hence

redesign it. The word faulty is ambiguous as it does not give specification of where the process is faulty. • Ambiguity No statement in Knowledge Base should have more than one meaning. If it is so, then there is risk of misunderstanding causing a wrong action. An example is statement like ‘If inventory is high then take action to reduce it.’ Here ‘high’ is not defined in specific terms in rupees or quantity. Hence, the statement is ambiguous. • Erroneous Representation Erroneous representation could arise in coding knowledge for subsequent processing activities. It may mislead the decision maker and wrong decision or action may be taken.

Post Implementation Review It is standard practice to review any system after it is implemented and user has some experience about it. It is also true for KMS. Knowledge team leader should make a very systematic review of the impact of KMS on the organisation. Following guiding questions would help asses the impact of KMS. • Is KMS delivering identified and validated knowledge? • How often and by whom this has been called for usage? • Are various repositories properly linked to each other, saving time of knowledge processing? • Is knowledge continuously being validated for currency? • Is knowledge getting richer out of its experience by the users? • Have users accepted new ways of collaborative working to save time and cost of processing? • Is knowledge being shared without any inhibitions? • To what extent has technology made an impact on users’ working? Are they satisfied with present technology driving KMS? • Have users formed COPs and interest groups formally or informally? • Is resistance to KMS receding owing to confidence it has created in the users as a useful tool for decision making? • Is KMS being maintained properly? Is it backed by a proper competent organisation of experts and specialists in key knowledge areas? • Is the management of the organisation actively looking into the system, and rewarding and recognising the users and contributors to the system?

KMS: An Integrated System KMS is integrated in overall enterprise software. Integration helps to create knowledge out of experience of users in using Enterprise software and legacy systems. Firewall takes care of security aspects and needs of Enterprise software, and of KMS as well. The KMS team is continuously monitors the knowledge development cycle by keeping track of knowledge usage, its frequency, the experience of its efficacy, and so on. Knowledge continues to exist for application, or finds its way out to make space for better knowledge or new knowledge all together. Intelligent managers always fall back on knowledge support from KMS to make better decisions and use of resources. Their eye is on improving the organisation’s business performance to beat competition. Let us elaborate the point of integrative relation of KMS and other Enterprise Software and legacy systems. Let us take CRM Enterprise software working along with other software. CRM software is of

two types, data driven and process driven. Both contribute for knowledge generation about customers, their requirement on products and services. KMS is put to use by design to extract the knowledge and then it is stored in appropriate repositories. Different customer knowledge sets regarding performance, features, new demands, etc., from different servers and databases are integrated and put into one repository built as customer knowledge. Experts and specialists are identified for tacit knowledge, and explicit knowledge is stored in coded form to use directly. Integration is of two types knowledge integration from several sources into one repository and integrating knowledge into the process as a process feature to resolve some problems. For example, a customer always wants a particular accessory in duplicate. This has been learnt by experience over time while servicing order requirement and has been confirmed subsequently. This is a ‘Product × Customer’ requirement knowledge. This knowledge will be used by default when the customer places an order for the product. Integrated KMS with extensive use of ICT provides a knowledge lever to managers to make better decisions. Following table illustrates this point. Customer

Knowledge

Application

Impact

Credit card Holder

Usage pattern; Amount spent, Kind of use

KMS watches the pattern and triggers a SMS or a call to check

Better service to Customer through alert

On site Engineers at Oil Drilling Site

Repository of drilling problems, advise and solutions

Site engineers get the benefit of knowledge in solving the drilling breakdown problems

Drilling begins with no inordinate delay

Erection Engineer at Project Site

Access to engineering drawings, data information of similar projects

Benefit of experienced knowledge of erection of similar projects

Erection of equipment is faster without any fault. Faster billing to customer

Airlines

Data warehouse Flight and occupancy data processed for traffic pattern and trend

Pattern and trend used for developing pricing strategy

Strategy benefits in rise in revenue

Service and Support Engineers

Knowledge Portal on Intranet of problems and solutions Manuals and drawings

E-learning of domain, problems and solutions

Early return from employee on the job. faster service

KMS has a number of processes which when operated in an integrated manner result into knowledge and its usage by the people in the organisation. Basically, after identification and validation of knowledge required by the organisation, it goes through five basic processes with the help of technology. The processes are: • Acquisition/Capturing/Procuring • Organising/Classifying/Indexing/Codifying • Refining/Contextualizing/Expert referencing/Best use guidance • Distributing/Transferring/Sharing to users • Archiving the knowledge before it is deleted Knowledge awareness benefits knowledge workers and knowledge users, producing better results in operations and performance of business. If knowledge has links with vision and business strategy, the impact

is high and sustains longer. If knowledge is applied to manage competitive necessities and competitive advantages, the organisation maintains its lead in the business. KMS provides knowledge support to the organisation. A good KMS design sustains if it is supported by HR. The benefits are larger if people quickly change over to knowledge driven culture of work and decision making. Further, if the organisation and HR head take care of Reward and Recognition system for supporters of KM initiative and the business benefits are very high, supporting the business case originally established for developing Knowledge Management System in the organisation.

THE LEARNING CONCEPT AND KNOWLEDGE MANAGEMENT SYSTEM Learning is the process of bridging the gap between what are knows and what are should know. It is the knowledge or skill acquired by studying theory or instructions. Learning enhances when knowledge learnt is applied in operations and problem solving. The gap may be filled by additional data, more contextual information and improved knowledge due to additional experience of using the knowledge in different applications. Learning means finding new ideas, improved insight, discovering new patterns, verification of hypothesis with additional knowledge and predicting future trends and behaviour. It may be developed out of experience, by experiment of knowledge in problem resolution, and by discovery while working on something. In KM application of collaborative working knowledge and intelligence are very important. The learning tools and technologies required for knowledge driven collaborative working are: • Artificial intelligence • Expert systems • Data warehousing and mining • Case based reasoning • Intelligent agents • Association rules • Neural networks In all these tools and technologies, data is a primary input. Learning takes place when the data is processed through these tools and technologies and using of data models. In order to use data directly, visualisation of data is absolutely essential. Data visualisation brings clarity in data structure, relationships and meaning. For example, retail trade business, monthly sales data of a product can be structured by customer segments, by locations, by models, and so on. Each structuring throws more light on sales and customer behaviour. The same sales data can be processed with a closely associated product, like cheese or butter to bread. The associate relationship is learnt to reveal the correlation between sale of bread vs sale of cheese or butter. These relations reveal a new meaning which may probably have not been found earlier. We will discuss these tools and technologies in detail in the chapter on technology. We can summarise the KM function delivery through KMS in a KM function delivery model as shown in Figure 4.19. The model specifies six enablers driving KMS, in which leadership drives the remaining drivers. The results at KMS produces are five knowledge entities which, over a period gather high economic value culminating into human, structural capital and Intellectual property. The organisation truly becomes a learning organisation whose brand equity increases, highly impacting the market value of the organisation.

Enablers

Results Knowledge

Knowledge Champions

Leadership

Fig. 4.18

Access and share tools Technology and Network Culture: Knowledge, Learning, and Sharing

• Bases • Assets KMS

• Products • Repositories • Intelligent Systems

Human Capital Structural Capital Intellectual Capital Intellectual Property

KM Function Delivery Model

End Notes • People are the creators and owners of knowledge. Their experience adds value to knowledge. Technology is an enabler and driver of knowledge management. People include all types-managers, officers, workers and staff members. All gather knowledge in their fields of operation through work experience and interaction with fellow employees and their counterparts in other organisation. • The Knowledge Management System is defined as a system to manage knowledge in steps, beginning with ‘identification, validation, creation, acquisition, transfer measurement, and capitalising into IC & IP. The purpose of KMS is to support decision making personnel in the organisation and stake holders with online ready access to the organisation’s sources of information and know how. • This definition of KMS is extended to include the integration of knowledge in business operations and decision making systems. Integration is done through business rules, models, algorithms, formulae, and so on. • The generic KMS model considers dynamic business environment as a basis of developing KMS. KMS is a set of processes and tools which give the ability to leverage and combine the collective abilities of the knowledge workers. • KMS provides a structured way of capturing knowledge that exists within the organisation; it gives organisation the ability to improve the productivity and knowledge of its employees by means of knowledge sharing. • The management focuses on five key knowledge areas, customer knowledge product and service knowledge, process knowledge, people knowledge and technology knowledge. • It is imperative that the management recognise KM as an important function; it needs a separate organisation for managing KM life cycle. Chief Knowledge Officer (CKO) would head this organisation. CKO would be supported by knowledge teams, experts and specialists, knowledge processors, and knowledge users. • The knowledge organisation can be viewed in an integrated manner. It has three components, namely People Organisation CKO, knowledge teams, knowledge users Process Identify, validate, create, organise, store, measure, revalidate Drivers Competition, business strategy, technology, work culture, threats to business

• The organisations continuously research in these areas of knowledge to assess whether the current business strategy needs reassessment and a new design to keep business on the growth path. It examines whether present competitive necessities are effective, and whether a new set of competitive advantages needs to be worked upon to maintain the leadership. • Knowledge management is all about managing interaction of people, processes and technology. KMS manages this interaction where the three have a close association, relation and dependence. • The KMS processes this data and information to measure the operation’s results and business performance, and compares with targets and KPIs. When this outcome is analysed, applying theory and principles, functional knowledge and experiential wisdom, knowledge components are produced. • The KMS system architecture is factored into three main modules, identification, creation and delivery and service. The knowledge workers responsible for these modules are experts in business management for identification, manager technocrats for creation, and experienced knowledge workers for delivery, service and maintenance. • Another view of KMS architecture is in layers, namely, user interface or web browser layer security layer, dissemination layer, information exchange layer, middleware layer, repositories layer. • KMS training has two goals, training on the system to use it effectively and training the user to become knowledge worker and knowledge contributor. They must appreciate the paradigm shift in business operations supported by KMS. They must accept new work culture which is technology driven and knowledge driven. The business processes have shrunk and work demands collaboration and coordination across the departmental and functional boundaries. • The appreciation of this role is important to make the process efficient. They must learn to work with Groupware technology, where process demands synchronous and asynchronous intervention by the users. This is a work culture change, both in style and operations. • Unlike other software system implementation, KMS needs to address some people related issues to ensure that the users participate in the system wilfully, and they make KMS rich and efficient. This resistance to change is very difficult to handle. It is never spoken but is expressed in different ways. • The resistance to switchover to KMS comes from four quarters, experts and specialists, users in powerful positions, regular employees fearing they would become redundant, and trouble makers. • The solution to these problems is to have the following in the organisation. – Proper change management system. to move to KMS – Strong case for justifying KM initiative and Development of KMS – Involving personnel of the type discussed in the beginning to win over their whole hearted cooperation and participation – Evolving and declaring reward and recognition system simultaneously – Convincing key personnel that their professional growth would not be hampered, if they did well, chances of their growth were very high – Convincing people in the organisation that it was a business compulsion to be ahead of the competition, which demanded systems like KMS • KMS is tested when users are actually using it. Two actions are taken, verification and validation of the system from all angles. Verification confirms that the system is as planned in system specifications and needs no correction. The verification step includes confirmation of problem/solution association, and then, when called for, displaying it the format user has chosen.

• Though the system development is right, the validation step confirms it does the right job of application, producing the desired results. It meets the user and knowledge worker’s expectations. The validation checks confirm reliability of the KMS. Besides this, knowledge stored needs to be tested for the several aspects. • It is standard practice to review any system after it is implemented and the user has some experience about it. It is also true for KMS. Knowledge team leader should make a systematic review of the impact of KMS on the organisation. • Every organisation has knowledge concealed in files and folders, and also with the people who have been with the organisation for long. People individually enrich their knowledge as their experience of knowledge application increases over time. Knowledge is resident in many sources within the organisation. Some knowledge is to be procured or acquired from outside the organisation. • Implicit in this KMS cycle is an assumption that knowledge team would transfer and share the renewed experience as knowledge for common good of the organisation. This may not happen in a routine fashion through KMDS. • Like KMS, knowledge also has architecture. It is a prerequisite to knowledge creation process. Earlier we had said that knowledge is an outcome of interaction of people, experience and technology. • Knowledge sharing is most difficult to achieve. HR department and top management should make extra efforts to convince people that knowledge creation and sharing are good for company performance, and eventually for their performance. • While putting knowledge in knowledge database, following points should be taken care of to realise business benefits and higher productivity. – Focus on real application oriented ‘actionable knowledge’ – Give all references of owner, expert, contributor for communication in case of difficulty or doubt – Classify knowledge in broad areas and mention name code of group member to attend, guide, develop, etc. – KMS is integrated in overall Enterprise software. Integration helps to create knowledge out of experience of users in using Enterprise software and legacy systems. Firewall takes care of security aspects and needs of Enterprise software and of KMS. • Implementation phase is the last stage in KMS. At this stage knowledge needs are identified and validated by the knowledge team and management has agreed to go ahead as business case is justified. Knowledge then is captured and coded and stored in knowledge base resident on one server. Implementation phase contains three main tasks, KMS deployment, review of KMS while in use and maintenance. • Integration is of two types, knowledge integration from several sources into one repository and integrating knowledge into the process as a process feature to resolve some problems. For example, a customer always wants a particular accessory in duplicate, which has been learnt over time and confirmed subsequently. This is a Product × Customer knowledge. This will be used by default when the customer places an order for the product. • Following are the key knowledge areas a KM team should identify: • Knowledge required to build strategy and its implementation • Knowledge processes contributing to creation of value and competitive advantage • Characteristics of identified knowledge

• Mechanisms to transfer and share knowledge • Conducive organisation structure • Incentives, reward and recognition systems

Questions 1. Explain the importance of knowledge identification in KMS. What would happen if this step is dropped from KMS? 2. Explain how you would identify knowledge in the following organisations. • State Transport Organisation: A PSU • Organisations producing white goods, such as LG, Godrej, Bajaj. • Airlines • Mobile phone service providers 3. Explain the difference between competitive necessity, competitive advantage and business differentiators. How would you use them in launching KM initiative? 4. How would you select and develop a knowledge development team in the organisation? Identify their role and contribution in developing a sustainable KMS in the organisation. 5. Why is it important to make a business case to justify the investment in KMS? 6. Give an example of knowledge from your organisation, or from your experience, which is a • Fact • Rule • Procedure • Formula • Heuristics • Model • Declarative • Semantic 7. Explain why technology is a driver in KMS. 8. Why do you think that Knowledge needs to be validated and periodically revalidated for its continuing use in the business operations? Identify the knowledge types which need not be validated. 9. Explain your understanding of tacit knowledge and explicit knowledge. In the following pair of persons, explain who possesses more tacit knowledge and explicit knowledge? Why? • General practitioner vs Consulting physician • Programmer vs Programmer analyst • Line manager in machine shop vs Manager maintenance • Line manager vs Process planner 10. Most organisations focus on the following knowledge depending upon their need. • Customer knowledge • Product and service knowledge • Process knowledge

11.

12. 13.

14. 15.

16. 17.

• People knowledge • Technology knowledge Is it necessary that every organisation should focus on all of them? In the following organisations, which knowledge is a must for the organisation to focus upon and use in strategic management of business? • Service organisation • Oil and gas supplying companies • IIT and IIM • Pharmaceutical companies • Passenger car manufacturers • Companies manufacturing consumer durables In following situations, identify the knowledge which can be embedded in the system to make it more intelligent. • Traffic jams and delay problem due to signal system at five road junction • System of controlling H1N1 Swine Flu incidences and remedy for that • A particular refrigerator model of the company has more customer complaints than other models of the company • In a Room air conditioner, a particular control system is failing too early. The system is purchased from the alliance partner who is manufacturing as per the company supplied design Explain the linkage between knowledge and business strategy. In the following innovation cases, explain which knowledge has led to this innovation. • Mortin Mosquito Repellant coil • Advertising and promoting ‘Tea’ as an anti-oxidant • Automatic car locking and alarm system • Mobile vehicles advertising the products or using them for demos • Use of satches in products like shampoo, oil, etc. Draw a model showing the relation between knowledge and innovation. Identify from your professional experience, or as observed by you in public or social life, examples of data driven system, Information driven system and knowledge driven system. Distinguish between the following • Knowledge worker and Other worker • Knowledge and Business intelligence • Knowledge development and Knowledge management • Rule and Procedure • Program and Heuristics • Work culture and Knowledge driven work culture Explain why KM system should be tested before it is implemented on a large scale. Develop five questions you would like to ask yourself after, say, six months whose answers would help you to comment on the success of KMS in the organisation.

18. Following errors need to be controlled while designing knowledge database. • Inductive or deductive reasoning errors • Ambiguity in a guiding statement • Incompleteness in knowledge • False positive or negative representation • Give an example of each error 19. KMS is a system which does not function in standalone mode. It must be integrated in larger integrated Enterprise software system. Explain. 20. Explain the importance of ‘Security layer’ in KMS architecture.

5

Development

Chapter

(Identification, Valiadation, Creation, Acquisition)

This Chapter Deals with • • • • • • • • •

Introduction to KM Developing Business Strategy and Knowledge Link Framework for Mapping Knowledge A Knowledge Strategy Framework Validation of Knowledge through Knowledge Models Creation of Knowledge Triology Model of Knowledge Creation Acquisition of Knowledge Knowledge Acquisition Techniques (KAT)

Learning Outcome In this chapter you will get an indepth understanding and insight into the steps involved in knowledge development. Further, you will realise the importance of linking knowledge strategy to business strategy. There are several techniques of knowledge acquisition which are use for knowledge acquisition. Your understanding will result in confidence.

“When markets shift, technologies proliferate, competitors multiply, and products become obsolete almost overnight, successful organisations are those that consistently create new knowledge, disseminate it widely throughout the organisation and quickly embody it into new process technologies and products.” —Ikujiro Nonaka, The Knowledge Creating Company

INTRODUCTION TO KM Knowledge management (KM) comprises of a range of practices used in an organisation to identify, create, represent, distribute and enable adoption of insights and experiences gathered during the course of business management. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organisational processes or practices. KM is all about creating knowledge based employee competencies. The Hay/McBer Iceberg Model gives us insight into this.

Skill Knowledge

Social Role Self-Image Trust Motive

Fig. 5.1

The Hay/Mcber Iceberg Model

Hay/McBer, a leading UK management consultancy firm and inventors of competency management, define managerial competency as an underlying characteristic of a person that enables him to deliver superior performance in a given job, role or situation. Their iceberg model of managerial competencies places knowledge and skills at the tip, with the underlying yet conscious elements being social role and self-image;

KEY TERMS • Knowledge Validation • Knowledge Based SWOT Analysis • Knowledge Conversion Model • SECI Model • Knowledge Acquisition by Interaction • Knowledge Acquisition by Type • Integrated Knowledge Development Model • Knowledge Strategy vs Business Strategy.

traits and motives are at the subconscious level. The social role reflects values which sees as important while self-image reflects identity—whether one sees oneself as an expert. The traits are the habitual behaviours that we recognise in each other, while the motives are the thoughts and preferences that drive behaviour and satisfaction. Many large companies and non-profit organisations have resources dedicated to internal KM efforts, often as part of their business strategy, information technology, or human resource management. Several business consulting companies provide strategy and advice regarding KM to these organisations. KM efforts typically focus on organisational objectives, such as improved performance, sustaining competitive advantage, creativity and innovation, sharing of lessons learned out of experience and continuous improvement of the organisation. KM efforts focus on the management of knowledge as a strategic asset. They also focus on encouraging the sharing of knowledge to build IC & IP. KM efforts can help individuals and groups to: • Share valuable organisational insights • Reduce redundant work • Avoid reinventing the wheel per se • Reduce training time for new employees • Retain intellectual capital The process steps in KM run dynamically, revolving around a vision and mission of improving knowledge to higher value. Some of it would then be IC & IP of the organisation, a competitive advantage. Knowledge management process cycle is made of seven steps, as given below: • Identify knowledge • Validate knowledge • Create knowledge • Acquire knowledge • Transfer and share knowledge • Measure value of knowledge • Create intellectual capital and intellectual property These steps are executed in cyclical order keeping the knowledge need of the organisation fully supported through KMS. In Chapter 4 we introduced the Generic Model of KMS as shown in Figure 5.1. The KM cycle is implemented through KM strategy evolved suitably for the organisation. Create IC, IP Measure Knowledge Impact

Identify Knowledge Validate Knowledge Vision, Business Strategy

Codify and Transfer to Users to Share

Fig. 5.1

Dynamically Changing KMS Cycle

Create Knowledge

First KMS Cycle

Acquire Knowledge Second KMS Cycle and Cycles continue with Changing Dynamics of Business

Knowledge Management: Development 149

In this chapter, we discuss the first four steps of this cycle-identification, validation, creation and acquisition. The remaining three steps—transfer, measure and create IC &IP—will be dealt with in Chapter 6.

Knowledge Identification Business organisations of the day have realised the importance of information and knowledge as a cutting edge strategic resource for competitive business management. After successful implementation of various IT solutions and applications, they are now focusing on exploiting IT investment for knowledge generation. Knowledge is now recognised as the most valuable asset of the organisation to face the challenges of competition. It is considered as distinguishing capability of high economic value for the organisation, recognised both by customers and competition. Knowledge, as an entity, has no separate independent existence in the business of the organisation. Its requirement and existence depend on the business status at the point of time, management style, business model and people in the organisation. That is, knowledge management team responsible for knowledge development and management has the task of searching the knowledge which has a direct bearing on business operations and performance. The knowledge which needs to be identified is the one whose usage brings excellence in business operations and results in superior business performance. By this logic, in the same industry and business, knowledge needs of two different organisations would be different. Also these two organisations may not be competing with each other. For example, knowledge needs and its identification in a private bank and a PSU bank would be different, as their business goals, business models, organisation structure and management style are different. Knowledge driven organisations use knowledge extensively in their business processes, and in strategic and operations decisions. So identification of knowledge areas becomes the critical first step to ensure that knowledge areas and, from them, the specific knowledge elements are correctly chosen to support business management for excellence and superior performance. The process of knowledge area identification is shown in Figure 5.2. In this chapter, we are taking a broader view of ‘knowledge’. We include in its scope that ‘knowledge’ which the organisation needs but is not known. Such knowledge may be hard facts, rules, programmes, best practices, heuristics, models, knowledge products, and so on. We are not restricting ourselves to the classical definition of knowledge, learning out of experience, and developed through SECI Model. Hence, when business strategy alternatives are developed, knowledge areas, known and unknown, are chosen and analyse in such a way that the business strategy choice is also the result of sourcing knowledge from all knowledge areas. They also support business strategy implementation.

Process of Knowledge Identification Develop a Business Strategy Strengths, Weakness, Opportunities, Threats (SWOT) analysis is the most popular and recognised tool to understand the present business status which forms the basis for designing business strategy for the next few years. The strategy then builds measures and actions to strengthen the organisation strength (Internal capabilities), further to offset the weakness and ensure that their impact on business operations and performance is reduced.

Study and Analyse Business Environment

Analyse Competition

Fig. 5.2

Forecast Business Projection for Organisation

Assess Threats to Business

Identify Current Strengths and Opportunities

Develop Strategy Alternatives and Select One

Determine Knowledge which Areas Would Create and Support Business Strategy and its Implementation

The Process of Knowledge Areas Identification

The second part of the strategy leverages on the strength to exploit the business opportunities to business advantage for growth and superior performance. The third strategy option deals with preparing to meet the threats to business (Should it occur?). But all this strategic working is done by the top management in a closed room. The secret operations are known to few. SWOT analysis is further dominated by Michel Porter’s Model on Five Forces of Business Threats. It largely takes SWOT analysis in external domain of the business, towards industry at large. Some strategists argue that this holds good up to a stage, but is not fully useful when talking of an organisation and its business. They argue that SWOT should focus on internal view of the organisation. It further argues that each organisation is unique in the industry and would react to challenges in a different manner, resulting in different performances, measured in quantitative and qualitative terms. Hence, needs an approach which is organisation specific, but does not wholly ignore SWOT analysis. It recommends focus on internal capabilities and building additional ones to meet the strategic challenges to the organisation. Resource based approach argues that focusing on market/products/customers is wrong as products may go and new may come, or markets may shift to new areas of substitute. It says that the organisation should focus on resources, capabilities and skills, and ensure that they change with time to meet the new challenges to business. It argues that leveraging on resources and capabilities offers more competitive bandwidth than focusing on products and markets, and on the lines of Porter’s five forces of threats. It recommends a new perspective of looking at knowledge, as driver to build business strategy. This perspective emphasises that knowledge (five knowledge areas) which matters in the particular case is the most important key input to design business strategy. This perspective is known as Resource Based Perspective where knowledge is the first key resource of high economic value. (Source: J.B. Barney, The Resource Based Theory of the Firm, ‘Organisation Science’ Vol. 7 and DJ.Collis & C. A. Montgomery, Competing on Resources Strategy, HBR, July-August 1995, and others) Developing business strategy and its successful implementation is a challenge in the world of global business and global competition. The challenge can be met if strategy is developed by a group consisting of a strategist and people who are responsible for delivering customer requirements. This group should also include people from the frontline who are interfacing, supporting and servicing customer needs. The group members are knowledgeable and may hold any rank in the organisation.

This challenge is tougher when strategic thinking is done by top management with the help of Manager, Corporate strategy. This process does not involve other key personnel who are closer to the market, customer and technology. Due to such distance approach, strategy does not reflect what the market and customer want. The implementation of such strategy fails, not because of bad implementation, but because of lack of knowledge about market, customer needs and priorities, technology needs of manufacturing and delivery and support services. In essence, strategy lacks various knowledge inputs just stated here. The important thing missing is the process of building strategy based on knowledge of a number of aspects of business. Hence, we do not look at knowledge or business strategy independently, in isolation, but together to make it a success. Organisations are investing in Enterprise software, hardware and networks to leverage on technology. Integrated systems have given some business benefits because of automation of transaction processing, DSSs, just-in-time information and MIS. But these returns are not large enough to be happy about. The management still experiences strategy failure because something is wrong, or there is failure in implementation because strategy is a misfit at the ground level. What is missing is that both, business strategy and knowledge strategy, are not linked by knowledge. That is, business strategy and knowledge strategy are not developed in integrated manner to support each other. Business strategies of the day must be backed by knowledge. Some points to be noted for the exercise of knowledge identification are listed here: • Business strategies to deal with threats to business • Since best practice of knowledge identification at organisation level is to take internal view of resources and the level of existing knowledge to build more knowledge. • The competition may not have similar internal resource scenario and would, therefore, find it difficult to develop, imitate or find substitute knowledge to catch up with the organisation. • Further, developing new knowledge by competition is possible but unless it is integrated in the rest of its IS and KMS infrastructure, its use would be very limited and would often not be very effective. The competitor therefore would lag behind the organisation. • Unlike physical resource, knowledge resource generates increasing returns with its use over time. Hence, even if competition catches up, its returns on time scale would be less than that of the organisation. • Knowledge is systematically built after identification through a process of knowledge identification. For example, in India, oil and petroleum companies are competing with each other under the price regulation authority. Though their domain is oil and petroleum, their competing strategy and necessary knowledge and knowledge strategy may differ, making difference in the business strategy mix.

Conduct Knowledge Based SWOT Analysis The importance of link between business strategy and knowledge, required to make business strategy successful, has been established. We also mentioned earlier that successful business strategy needs proper SWOT analysis of internal organisation’s strengths and weaknesses first, before opportunities and weaknesses are discussed vis-a-vis competition. In order to have sustainable competitive advantage through knowledge driven strategy, SWOT analysis, focus should change to analysis of knowledge strengths and weaknesses, and then opportunities and threats should also be investigated based on knowledge, where in entire analysis cycle competition one or more are in the picture.

In other words, SWOT analysis considers knowledge intensive business of the organisation, and that of the competition. In this approach, SWOT analysis maps organisation’s knowledge resources (tacit and explicit, knowledge products, assets, and so on) against opportunities and threats foreseen by the organisation. This enables the SWOT analyst to understand better the advantages and weaknesses of the knowledge mapped, and the probable business strategy options. It also helps to analyse the gap between the available and the proposed, or the required. Knowledge strategy, then, can be thought of as balancing the knowledge based resources and capabilities of the organisation to the knowledge required to compete with superior knowledge of the competitors. (Figure 5.3). Further, identifying knowledge based resources and capabilities which are unique and inimitable, and how these resources and capabilities support the organisation’s product and market positions, is an essential prerequisite of building the knowledge strategy. Knowledge Balancing Exercise through SWOT Analysis Knowledge Based SWOT Analysis Organisation

Fig. 5.3

Knowledge Based SWOT Analysis Knowledge Strategy for Business Strategy

Competition

Knowledge Based SWOT Analysis

To strengthen the linkage between knowledge strategy and business strategy, it is necessary that the top management of the organisation firm up its vision and strategy for the next few years, validated by SWOT analysis of internal and external business environment. Unless business vision and strategy direction is firmed up, balancing exercise is wasteful. Further, it should analyse existing organisation knowledge and required knowledge to take to vision forward, and ascertain the gap between the two. This would lead to an exercise of acquiring new knowledge, as knowledge gap is already identified. With full knowledge support to vision and strategy, the knowledge linkage would then be complete and precise. To establish the link between business strategy and knowledge • An organisation must articulate its strategic intent to all in the organisation • Identify the knowledge required to execute its intended strategy • Compare the strategy and its knowledge need to its actual knowledge, revealing its strategic knowledge gaps • Take steps to bridge knowledge gaps

Linking Both Ways Knowledge to Strategy Every organisation in the business has different approach to strategy building because of its internal work culture and competition scenario. Each has developed strategy building systems based on some technology platform the corporate strategy process. Every strategy mix has a link to some intellectual resources and capabilities, and application skills of the people in the organisation.

The strategic choices that organisations make regarding technologies, products, services, markets and processes have a profound influence on knowledge, skills and core competencies required to compete and lead in the industry. This linkage is obvious and automatic. Issue is whether current knowledge and skill is appropriate to link to strategy, or the strategy considered is rightly the result of current knowledge. What needs to be secured is correct identification of the competition, their intellectual resources in any category, and then identification of right mix of the knowledge to be acquired, to deal with the competition. Linking knowledge to strategy is a must for successful strategy implementation. The exercise of linking knowledge and strategy requires time and money, and engagement of the organisation’s intellectual resources, and the knowledge developed and resident in files, folders, databases and servers. It must therefore take a systematic approach to knowledge building and designing strategy, built on the knowledge portfolio. As a prerequisite to this, the organisation must decide, based on identified knowledge, whether it would compete on price, cost, market, product, process and technology, or a mix of a couple of them. For example, ICICI Bank competes on technology and a range of services in the young twenty million people market segment. The bank’s processes are technology driven; most of the services are online and customer driven. The core banking and service banking are integrated. The range of services has a wide span, current account to saving account to home and insurance for individuals and family. The knowledge identification is focusing around these areas. As you have noticed, the bank has identified its competition, and its strength in intellectual resources. It has balanced its knowledge identification and development systems with that of competition. ICICI competes with HDFC, HSFC, Corporate Bank and other international banks, but much less with nationalised PSU banks.

Map Knowledge and Analyse the Gap The first and foremost requirement is identifying and mapping current knowledge in the organisation by its type, category, kind, economic value, etc. It begins with cataloging knowledge by type, category. First knowledge can be categorised as tacit and explicit, and then whether it is a fact, rule, procedure, heuristics, model, and knowledge product. Further, the category of knowledge is with an individual or is collective in a group of people. The mapping of knowledge in this manner helps in linking with strategy, and also managing knowledge with KMS. Core knowledge is essential, advanced knowledge makes business viable and gives lead and breather to the organisation, and innovative knowledge provides sustainable competitive advantage. Figure 5.4). The mapping of the knowledge in this manner is not easy because, knowledge, as a candidate for categorisation, is competitive or not is difficult to decide. Each organisation’s competitive strength may be different. So, competitive knowledge in one organisation is necessarily a strength, but is not in an other organisation, though it recognizes it as knowledge. Such knowledge in that organisation would be a competitive necessity and may not have axis, link to business strategy. Knowledge is strength and can be used to build knowledge driven strategy if it has the following features: • Unique, no parallel elsewhere • Core, advanced or innovative in its category, not found elsewhere • Competition would take long time to build • It has a future and is enrichable with experience

Determining Its Type, Category, Source, Economic Value, Core or Advanced Innovative, Strength of its Context to Strategy Intent

Gap Analysis Current Knowledge Inventory and its Application Experience

Current Knowledge Mappings

Fig. 5.4

Take Knowledge Initiative to Bridge the Knowledge Gap

Identified Knowledge to Implement Strategy

Strategy Intent and Some Specifications, Models. Implementation Strategy

Identify Required Knowledge

The Model of Knowledge Strategy Mapping and Gap Analysis

• It can be linked to strategy to reap advantages • Over a period, it has the capability to become differentiating competitive advantage After mapping current knowledge, the next step is to identify the knowledge which is required to implement the new strategy intent with its specifications. Once the required knowledge is identified for successful implementation of the proposed intended strategy, it is mapped in the same manner with current knowledge. You now have knowledge of what is current and what is required new. At this stage gap analysis is carried out by the management through knowledge initiative to fill the gap of knowledge. Figure 5.4 shows the model of knowledge strategy mapping and gap analysis.

ESTABLISH A KNOWLEDGE STRATEGY FRAMEWORK A knowledge strategy framework describes the overall approach an organisation takes to align its knowledge resources and capabilities to intellectual knowledge requirements of its proposed new business strategy. The organisation needs to describe and evaluate its current and desired knowledge strategy. The evaluation should centre on the area where knowledge needs to be enhanced and the degree of benefits it offers to the organisation. If the current knowledge level needs enhancement, knowledge initiative gets into the exploration of new knowledge to close the knowledge gap. If current knowledge is adequate and higher than what is sought, it aggressively exploits its application for new strategy implementation. If the competition in the industry operates at a much higher level of knowledge, the external knowledge gap needs to be aggressively dealt with to bridge the gap. At the conclusion, knowledge strategy framework specifies knowledge in terms of type and kind, rules, programme, procedures, models and Heuristics, and its application.

Take Knowledge Initiative The organisation, in this game of closing the knowledge gap, plays the role of explorer, creator and acquirer of knowledge to maintain its competitive advantage. If the knowledge resources and capabilities significantly

exceed the requirements of a competitive position, then it offers the opportunity to rationalise the knowledge platform, possibly within or across other competitive niches. For example, Dow Chemicals screened its portfolio of 29,000 patents (IPs) to see which should be exploited, which could be licensed, and which should be abandoned. The exercise generated $125 million in licensing income and $40 million in savings over 10 years. (Source: Developing a Knowledge Strategy, Michael H. Zack California Management Review, Vol. 41, No. 3, Spring, 1999, pp. 125–145) The roles mentioned here are not mutually exclusive. In the exercise of building knowledge strategy, the organisation’s knowledge initiative may be in the area where exploration is necessary, in an other case role it could be of the acquirer, and, in some other area, initiative would focus on creation, as the required knowledge is already identified. The knowledge initiative, through the role of explorer, creator, and acquirer, would be handled by different people or teams as these are specialised areas of knowledge, whose source could be internal or external. Balancing these efforts to become congruent to support the new business strategy is very difficult. To make this happen, the organisation must have in place a system of rewarding motivators and competence. It is one of the strategic core capabilities the organisation should build to ensure that knowledge gaps are closed at the earliest. The organisation’s knowledge team must plan and programme various activities of knowledge initiative using technology to expedite the process of closing the knowledge gap. Use of ICT for developing e-learning programmes, conferencing techniques for knowledge transfer to user centre, advancing training programme for new knowledge initiative, building robust network of knowledge workers and communities are same of the solutions to overcome the difficulties of knowledge search, closing of the gap, and so on. To get the command on this knowledge initiative, following guidelines are very useful. • Focus first on the internal source of knowledge as it is known, most of it is already articulated and in use (but not known publicly), some of it is already stored in files, folders, databases, and so on. Being internal, it could be very valuable and unique, and may have high economic value and strategic content. • Form user groups, communities of practices, participate in seminars and conferences to catch the most recent knowledge. • Focus on external sources which are published in journals, magazines, publications of professional bodies. This knowledge is available to competitors and so may not have special advantage, but it can be used to judge its impact value on knowledge and business strategy. • Enter into alliances with resourceful vendors, institutions, federations who are following KMS in their business strategy formulation and implementation. Integration of all three sources may provide a new insight in to the knowledge strategy and formulation of business strategy. Business strategies are built on leveraging knowledge. Competing successfully on knowledge requires alignment of strategy to what the organisation knows, and developing knowledge and capabilities needed to support the desired strategy. The business strategy implementation, backed by the right knowledge spectrum, is successful if it is implemented on the right mix of ICT infrastructure. In other words, technology, knowledge and strategy must shake hands to make the whole system a success. Taking a strategic view of knowledge as a resource of economic value, and hence considering it for building business strategies, is critically important in competitive global business of the day.

We are emphasising here that knowledge, existing or to be acquired, needs to be identified first. The process of identification is for searching known or unknown knowledge in the organisation and in the world external to the organisation. Then, knowledge initiative is taken to explore, create and acquire. So, we consider identification of knowledge as the first step before its acquisition.

VALIDATION OF KNOWLEDGE Validation is the process which confirms the rightness and appropriateness of the identified knowledge for framing business strategy and its implementation. If there are errors in knowledge, there will usually be errors in performance of its application system. There are several reasons for knowledge to be incorrect or improper, calling for its systematic validation. • The expert(s) provide incomplete or incorrect knowledge. • The knowledge team fails to correctly understand or code the expert’s knowledge. • The knowledge team may fail to capture all instances of the underlying conditions. There are two kinds of validation required on an identified knowledge: logical and semantic. Logical validation checks how the rules and objects work together to reach logical conclusions, that all the conclusions of the knowledge can be true at the same time. Logical validation also in the process checks for completeness of knowledge. Logical completeness and consistency are necessary for knowledge to be valid. However, logical completeness and consistency are not sufficient for knowledge validity. For example, knowledge about a vendor is logically incomplete if we know only the manufacturing process capability of the vendor and have no knowledge about his delivery system. The consistency of knowledge confirms that all inputs, rules, models, facts, programmes and heuristics are complete, and are consistent to each other with little or no chance of going wrong in its application. If selection of vendor is a problem, then knowledge body about the vendor includes: • Process capability, Credit expectations, Quality rating, ability to supply on time, image in the market, and expertise for which the vendor is being considered • A programme to compute vendor rating based on these knowledge elements Further, knowledge can be logically consistent but not semantically consistent for its intended target application. Semantic consistency occurs when all facts, rules and conclusions of knowledge are true for the intended knowledge application. To illustrate the difference between logical and semantic consistency, consider ordinary Euclidean and spherical geometry, both are logically consistent mathematical systems from which knowledge can be built. However, for everyday life, Euclidean geometry is consistent to its application requirement but spherical geometry is inconsistent. While for long distance navigation, spherical geometry is more appropriate and consistent to the required knowledge application. The basic method for validating a knowledge item or element is: • Ask a panel of experts, who created it, whether knowledge is true or false. • Tally the true/false answers with all experts involved. • Analyse these results statistically and conclude on the degree of confidence on the knowledge before its application. There are several ways to validate knowledge. Check whether: • Knowledge is sourced from a standards document in the domain. For example, IEEE standards. The assumption in this case is that standards are based on valid knowledge.

• Identified knowledge areas and knowledge elements within are obtained from genuine experts and specialists, and the knowledge workers recognize them so. • Knowledge is validated with most recognised current expert and is reviewed with other experts. • Develop knowledge Models and test them to validate. It validates model as well as knowledge elements within the model. The following steps detail the validation process of knowledge. • Present the knowledge model to outside experts. • Collect all questions, comments and objections to knowledge and the model. • Make corrections, where necessary. • Verify the knowledge, whether it is complete and correct for the intended purpose. • Give the test of knowledge to the outside expert to validate and to determine the extent of agreement on each of the Knowledge elements. • Check whether knowledge application and source are consistent to each other.

VALIDATION OF KNOWLEDGE THROUGH KNOWLEDGE MODELS Knowledge models are used as proof of correction of knowledge. Therefore, it is important to validate knowledge models with domain experts. A knowledge model represents the total knowledge identified and coded in the model for further processing. The ability and competence to construct a knowledge model would decide its validation capability. For example, as a part of profit maximisation strategy, an organisation would develop multivariate product mix strategy. The knowledge elements required for building knowledge strategy are ready. To convert this knowledge body into a knowledge solution model and to validate it is difficult and challenging. Hence, the organisation would build a linear programming model to find the product mix to test and confirm whether the strategy of product maximisation would be effective to make a decision on its validity. The model is used to improve strategy through different options of operations and business management strategic options, and this would call upon the knowledge team to identify new knowledge, develop new strategies and improve the solution and business performance. This Linear Programming (LP) model building exercise requires the knowledge team to collect only those elements of data, information and knowledge which are relevant. The experts, internal as well as external, have confirmed that LP model would confirm the validation of knowledge and the model confirming the business strategy of that product mix which maximises the profit goal of the organisation. The LP model, in its final form, is a knowledge product of the organisation. There are several ways to ensure that the LP knowledge model is valid as a testing model. • LP model, a knowledge model, is a standard approach to solve this kind of problem. The model becomes more efficient if there is precision in all its inputs and all inputs, are considered in building the LP model. • Create a LP knowledge model through joint development and consensus of a knowledge team of recognised experts in the organisation and business domain. The knowledge model created in this way contains the best available expertise. • The participation of multiple experts increases the chances that one of them will catch any error that creeps into their discussions in the process of knowledge collection for constructing LP Knowledge Model. A graphical representation of the LP model is shown in Figure 5.5. • On creation of this model, have it reviewed from other outside experts.

Labour Constraint

Material Constraint Knowledge of Number of Feasible Solutions

Fig. 5.5

Mfg. Capacity Constraint

Graphical LP Model for Product Mix: Knowledge Model

Before the knowledge model is accepted as a solution platform for profit maximisation, it should be validated from different angles. In this process of validation, are validates knowledge elements, constraints, relation among the variables and product output, and finally the LP model itself. The following steps detail the validation process of the knowledge model: • Present the knowledge model to outside experts. • Ensure that professional courtesy does not interfere with making critical comments on the knowledge model. • Collect all questions, comments and objections to knowledge models, or parts thereof. • Sort and organise these comments into questions about parts of the knowledge model. • Give the test to the outside expert, to determine the extent of agreement on each of the items. • If some of the items are not validated, perform additional knowledge acquisition and modification of the model to resolve the problems pointed to by the invalidated items. This may include additional discussions, bringing in more experts, literature searches, or redoing parts of the model. • Conduct sensitivity analysis on a number of inputs to judge its effect on the model and its efficiency as a knowledge testing tool. In validating the knowledge model and related knowledge validation activities, it is important to ensure that the experts are from the domain of the expert system. Most technical fields today are too big and complex to be mastered in their entirety by a single expert, or even a few experts. Therefore, in critical applications, it is important to validate every part of the knowledge base with experts in that particular specialty. After performing these validation steps it is important to assess the performance of the domain expert, if the current domain expert differs from a consensus of other domain experts. In that case, there are two possible courses of action: replace the domain expert with one who represents a consensus of current domain knowledge and continue the expert system with the disputed knowledge model, with the realisation that the system will not reflect a consensus of expert knowledge. In this case, it is unlikely that the system will perform in a way that matches a consensus of domain experts. Continuing development is a legitimate course in experimental or non-critical systems but is not advisable in critical expert systems. A knowledge model containing knowledge which has not been validated should be used only for applications where there is no serious consequence of an error by the expert system. Even if expert knowledge has been properly encoded into the knowledge model, it will probably produce errors if the underlying expert knowledge is wrong. Therefore, it is important to validate expert knowledge before expertise is used in building the knowledge model. This is particularly important because there are a

number of ways in which errors can creep into the knowledge model on which strategy is built. Some of these errors are: • The expert is wrong, or the knowledge is not current. • The knowledge was correct when collected, but it has changed now. • The knowledge engineer misunderstood the expert presentation and recommendation. • Errors in knowledge were introduced in maintenance and review of the model.

Creating a True/False Test for Knowledge • In asking the experts to decide if the knowledge element is true or false, it is important not to bias them. • Start with a collection of True/False questions with no specific proportion. How many true and how many false is the demand of the knowledge being tested. • Scatter True/False statements in random order. • Adjust the test if necessary so that True and False have approximately equal probabilities of being right. Although this guidance is adequate, more detailed information about constructing unbiased tests can be found in the literature on survey and test design.

Giving the Test and Deciding on Validation • Knowledge validation through testing is a consensus approach; there are some issues that must be handled to become test efficient and effective. • First of all, the knowledge engineer/tester must explain to the experts that it is not they, but the knowledge and its intended application, that are being tested. • The items on the test represent assertions expressed by experts on which the knowledge is based, and these are being validated by experts. • The reason for using multiple experts is not a lack of confidence in any one expert, but a desire to validate assumptions made in knowledge to a statistically significant confidence level. • It is important to explain this to all experts used in knowledge validation to ensure that no hostility toward the knowledge engineer or the project develops. • The experts used for validation should be carefully instructed to call knowledge element false if it is not always true. • Design a test for multiple options such as ‘True, False, Sometimes True and Sometime a False’, with conditions specified. • The test must be given to a good number of experts of varying competencies so that the correctness of each knowledge element on test results can be distinguished from chance test results. • A knowledge base item is statistically validated: A majority of experts answer that the knowledge element is true or false. • The number of experts participating in the test is so large that if the experts’ conclusion is either true or false, it could have a chance of being wrong (true is wrong or false is wrong) below the threshold, say less than 5%. In a nutshell, validation is the process which confirms the rightness and appropriateness of identified knowledge for framing business strategy and its implementation. If there are errors in knowledge, there will

usually be errors in performance of its application system. In this case, it would be an inefficient strategy and its implementation. There are two kinds of validations that must occur on an identified knowledge: logical and semantic. Logical validation checks how the rules and the objects where rules are applied, work together to reach logical conclusions, that all the conclusions of knowledge can be true at the same time. Logical validation also checks for completeness of knowledge. Logical completeness and consistency are necessary for knowledge to be valid. However, logical completeness and consistency are not sufficient for knowledge validity. Further, knowledge can be logically consistent but not semantically consistent for its intended target application. Semantic consistency occurs when all facts, rules, and conclusions of the knowledge are true for the intended knowledge application. The basic method for validating a knowledge item or an element is: • Ask a panel of experts who created it whether knowledge is true or false. • Consult outside experts in the same domain and get opinion on knowledge. • Tally the True/Fase answers with all experts involved. • Analyse these results statistically and conclude on the degree of confidence on knowledge before its application. Knowledge models are also used as proof of correction of knowledge. Therefore, it is important to validate knowledge models with domain experts. Knowledge model represents the total knowledge identified and coded for further processing. The ability and competence to construct a knowledge model will decide its validation capability. In validating the knowledge model and related knowledge validation activities, it is important to ensure that the experts used in validation cover the intended domain of the expert system. Most technical fields today are too big and complex to be mastered in their entirety by a single expert, or even a few experts. Therefore, in critical applications, it is important to validate every part of the knowledge base with experts in that particular specialty. A knowledge model containing knowledge which has not been validated should be used only for applications where there is no serious consequence of an error by the expert system. Even if the expert knowledge has been properly encoded into in a knowledge model, it will probably produce errors if the underlying expert knowledge is wrong. Therefore, it is important to validate expert knowledge before expertise is used in building the knowledge model. This is particularly important because there are a number of ways in which errors can creep into the knowledge model on which strategy is built. Therefore, knowledge, knowledge product and its application should be tested before it is declared valid for use. Figure 5.6 gives the knowledge validation process model.

KNOWLEDGE CREATION Knowledge Creation Model In the Knowledge Creating Company, there is a theory put forward as to how knowledge is created. The basic idea is that knowledge takes one of two forms, tacit knowledge (in peoples’ heads) and explicit knowledge (in documents, web pages, etc). A single piece of knowledge would move between these two forms and create ‘new’ knowledge on the way. Generally, knowledge moves in a circle from tacit to tacit, tacit to explicit, explicit to explicit and explicit to tacit. Socialisation Tacit knowledge can be shared in a process known as socialisation where knowledge is learned directly from another person, through working with him in some way.

Knowledge Validation

Documents in Business and Processing Systems

? Ask Experts ally True or False Answers

External Sources Data, Information, Knowledge

? Analyse Results Statistically Knowledge Identification

Experts, Specialists, Communities, Groups of Common Interest

? Cross Check Standards

Validated Knowledge Database, Repositories

? Cross Check with Other Experts ? Review the Knowledge with Knowledge User

Servers and Data Bases of the Organisation

Fig. 5.6

Knowledge Validation Process Model

Externalisation The knowledge which the engineer has termed tacit knowledge. This knowledge is then externalised when put into words or in some other form. It is now explicit knowledge. Combination There are cases where explicit knowledge undergoes a combination process that creates new explicit knowledge, for example, joining databases or search engines that link data together, hyperlinked documents, etc. Internalisation Explicit knowledge is converted to tacit knowledge when someone learns from that knowledge. This is known as internalisation and suffers from the format that explicit knowledge is in. For example, the learner may not have access to the documents or referenced documents, or the diagrams may not be clear, or the writing style may be awkward to the learner. Nonaka and Takeuchi believe that there are a number of enabling conditions that work to put the process into the real world context. The more apparent these conditions are, the better the creation of knowledge would be. These conditions are elaborated below. Intention This relates to an organisation’s level of aspirations and commitments to its goals. The more focused a company is better are its chances of achieving its goals. Autonomy As far as circumstances permit, all members of an organisation should be allowed and encouraged to act autonomously. This may increase the chance of introducing unexpected opportunities, and also the possibility that individuals may motivate themselves to create new knowledge.

Nonaka’s Theory of Organisational Knowledge Creation, centering on the SECI model, is probably the most widely cited theory in knowledge management. Figure 5.7 is the SECI Model: The ‘Engine’ of Knowledge Creation.

Tacit Knowledge

Tacit Knowledge to Explicit Knowledge

Socialisation Meetings: Formal and Informal, Discussions, Seminars, Workshops. Tacit to Tacit Transfer

Externalisation Articulation through Dialog, Brain Storming, Documenting, Modeling, Diagramming, Programming. Tacit to Explicit Transfer

Internalisation Learning more by Using Knowledze, New Experience Producing More Tacit knowledge Explicit to Tacit Transfer

Combination Using Technology to Convert Explicit Knowledge Elements to Knowledge Assets: Product, Processes, Heuristics, Models Explicit to Explicit Transfer

Explicit Knowledge

from

Fig. 5.7

SECI Model: ‘Engine’ of Knowledge Creation

The Case Study Evidence* Nonaka and his colleagues also provided illustrative case study evidence for each of the SECI processes. This material is illustrative, in the sense of having been selected to exemplify a point, and, as has already been indicated, much, if not all, the data came from previous studies of information creation. The SECI model claims that knowledge conversion begins with the tacit acquisition of tacit knowledge by people who do not have it, from people who do a process that Nonaka and his colleagues named socialisation. They give three examples of this process, of which the best documented study concerns the development of the automatic breadmaking machine showing that technical skill was socialised. An early prototype machine failed to produce tasty bread, the problem focused on in the second phase of the project. The team felt that the secret lay in the kneading process. Since a master chef could not ‘tell’ them what they needed to know, a software engineer apprenticed herself to him to learn the appropriate tacit skills. We are told that one day she “noticed the baker was not only stretching but also ‘twisting’ the dough”, and for reasons not reported the team decided to try to replicate this action. Since the new prototype was successful they concluded that they had found ‘the secret for making tasty bread.’ This appears to provide a convincing and unusual case of tacit-to-tacit knowledge transfer, or socialisation, learned from the master baker by working with him. There are, however, some critical technical difficulties with this account of observing. *

Source Extract from The SECI model of Knowledge Creation: Some Empirical shortcomings, Stephen Gourlay Kingston Business School, Kingston Hill, Kingston upon Thames, KT2 7LB UK. [email protected]

Externalisation, the next step in the knowledge conversion process, involves converting tacit into explicit knowledge, and holds the key to knowledge creation as new concepts are formed here. Several cases of new product development are offered as examples of this process. The best documented case describes how managers set up a young team charged with producing a new car that was inexpensive but not cheap. When novelty proved difficult to achieve a team leader stimulated their creativity with his idea of ‘Automobile Evolution’. Using this and other similarly incongruous phrases, ideas about what a new car might look like were generated and subsequently developed into a formal proposal for a new car. It seems to be an interesting example of the application of standard creativity techniques. Had Nonaka and his colleagues claimed that the team leader had ‘foreknowledge’, in the Polanyian sense, of the new product, then, despite the obvious difficulties of this notion, the product development cases could be read as examples of tacit-to-explicit knowledge conversion. The bread-making case seems to provide a more convincing example. Thus, we are told that one of the design team ‘was able to transfer her knowledge (of making bread) to the engineers by using the phrase ‘twisting stretch’ to provide a rough image of kneading’. The team was able to use this metaphor to think about how to replicate the motion in a machine. Externalisation is also exemplified here in that the team was able to put their newly acquired tacit knowledge into a form of words, and ultimately machine specifications, that enabled them to produce the desired effects. This appears very like the processes Collins described – people who could do something but were not able to fully describe how they could do it worked hard at developing a description when it, became necessary, and when it was apparent that they could not describe what they did in such a way as to enable someone else to do the same thing. Externalisation does appear to be an important process, albeit one that is more complex than Nonaka’s accounts would suggest. The next step in the SECI model is combination, the process of ‘systematising concepts into a knowledge system’, which happens when people synthesise different sources of explicit knowledge into, for example, a report or ‘through ... meetings and telephone conversations’, and exchange of documents. Combination also involves the embodiment’ of knowledge into products. Combination thus apparently consists of three (or four) kinds of activities: using language (talking, listening, reading, writing) to produce a synthesis, some unspecified aspect of computer functioning, and the ‘embodiment of knowledge into material goods. In so far as formal education involves language activities, it can be subsumed under the first category, but it could also be separated out as learning/teaching, and thus constitute a fourth category of’ combination activities. It is impossible to take seriously their claim that higher education simply, or even largely, involves ‘exchange’ of explicit knowledge. The final cell of the matrix is labeled internalisation, described as ‘a process of embodying explicit knowledge into tacit knowledge’. It is ‘closely related’ to ‘the traditional notion of learning’, and to learning by doing. Individuals can also internalise experiences by creating and reading documents. ‘Documentation helps individuals internalise what they experienced ... documents [help] ... people ... experience the experiences of others indirectly’. Documentation is an ambiguous word that can mean writing or reading. Books by business leaders, for example, are seen as a useful way of sharing mental models. Finally, internalisation also involves, or is achieved through, the dissemination of explicit knowledge throughout an organisation. Their description of internalisation is thus a little confusing since so many activities appear to be involved in this process. Moreover, we are not given any indication as to what they understand by, for example, ‘embodying’ of explicit knowledge, or ‘the traditional notion of learning’. It appears, however, that they envisage it to involve three distinct routes or processes: learning by doing, through reading, and through writing. Learning by doing is exemplified by team members who enriched their tacit knowledge through the experience of creating a new product and workers who learned what working reduced annual hours ‘meant’ by working at the new annual rate for a month. The annual hours example indicates that the workers ‘felt’ what the shorter working hours ‘meant’, suggesting internalisation is about acquiring a subjective sense of meaning. In so far as tacit knowledge is subjective and personal, this would appear to illustrate the acquisition of such knowledge. But it is difficult to see what explicit knowledge of how many hours were to be worked as distinct from the experience of actually working shorter hours contributed to internalization.

No examples of internalisation from or through reading or writing are given, and the difficulty regarding reading simply as a transmission channel has already been discussed. While those comments concerned explicit knowledge I see no reason why they should not also apply to tacit knowledge. If, as Nonaka and his colleagues claim, language and texts ‘contain’ mental models then, on the assumptions of the ‘communication model’, they would be transmitted simply by reading. But if reading is an interpretive process, such transmission is unlikely, unless the reader is already attuned in some way to the writer’s tacit ‘message’. Like combination, internalisation has not been clearly described.

Though, SECI model has some short comings, it is the best available model to launch the knowledge creation initiative in the organisation.

Introduction to Triology Model* Not much is understood about how knowledge is created in organisations, or how the knowledge creation process can be managed (Tsoukas and Mylonopoulos, 2004). However, some tend to believe that a single model devised to work on knowledge creation is enough to work in all situations, similar to the theorems developed in mathematics. The perception is not only deeply flawed, but is also a disconnect in understanding and respect on the fluidity and dynamism of human learning. Knowledge is regarded as important for creating organisational value and enhancing organisational competitiveness, especially in an unpredictable environment (Nonaka, 1994).Same is very true for learning organisations. In this day and age, knowledge is the key to success of the individual, the organisation and even the nation as a whole. Thus, it is imperative that learning organisations must not only have a deep understanding of knowledge construction but must also spearhead its understanding, adapted for the changing times. Today, in the age of knowledge economy, the academia is left behind by the globalised industries and military organisation that are deeply dependent on the efficiency of logistics, innovativeness of processes, products and services and technology in spearheading understanding on the newest school of thought, which is knowledge management. As always, the role of the academe is to pick on the success of these organisations, and analyse and adapt it to academic practices such that future workers will be able to continue and improve on what had been developed in the past. The focus here is to understand three models of Knowledge Management developed from three different sectors of society at different times. The OODA Loop (for Observe, Orient, Decide and Act), a concept applied to the combat operations process, often at tactical, operational tactical and grand strategic level in the military, is also adapted today by commercial operations. It was created by military strategist and US Air Force colonel, john boyd, in the 1960s. The SECI Model (Socialisation, Externalisation, Combination and Internalisation), was developed in 1991 by Professor Ikujiro Nonaka of Japan Institute of Science and Technology, and the Organisational Knowledge Creation and Management Framework was proposed in 2004 by Harri Oinas-Kukkonen of the University of Oulu, Finland and Stanford University, USA.

Understanding the Models OODA Loop Model John Boyd emphasised that learning is a product of decision making process within the mind of the person. Thus, understanding this process and creating a shorter and better way to create learning must be the main * Trilogy Model of the Knowledge Creation Process, Methusael B. Cebrian College of Education, Capitol University.

focus, in order for the organisation to ensure that learners will be able to demonstrate their learning at the fastest rate possible and gain advantage against the enemy. In our case the enemy is time. According to John Boyd, this decision making process within the person’s mind can be classified into a Process Loop. This means that a human being can learn and come up with his best decision using a single Process Loop. He called this as OODA Loop, which is derived from, Observe, Orient, Decide and Act (OODA) Process Loop. • Observe John Boyd Theory contends that the very first step to this process is for the person to observe the variables around him. These variables can be events and information that the person notices around him. He notes it in order to the preposition his thinking to the next phase of the process, which is orientation. • Orient After noticing the various informations around him, the learner now positions himself by taking into account his own previous knowledge, culture and traditions, and new information. The learner then analyses the new information versus his own previous knowledge, and connects them through synthesis. This is the phase where the learner understands what is going on around him. At this point, the learner has not created new knowledge, but readies himself for the next phase of the process, which is to decide. • Decide At this point, the learner has gained significant level of understanding regarding the new information around him, he now understands what is going on and prepares himself to adapt towards the new situation. So, the next step is to decide, based on his new experience, if he is going to make the new experience a part of his new knowledge. Should the learner decide to neglect the new experience, his next process is to go back into the observation phase and restart the process. If the learner accepts the new experience as part of his new knowledge, he is now prepared to demonstrate his new learning to his environment. • Act After deciding the best course of action to the given situation, the learner quickly moves into putting that decision into action. This is the time that the learner demonstrates his understanding of the given situation to the best of his ability and knowledge confirmed so far. However, the action may depend on how the learner has oriented to the variables or information fed to him through interaction. Therefore, he may act, depending on the level of his understanding, to the new knowledge constructed within his mind.

Commentary of Methusael Cebrian on the SECI Model According to Professor Ikujiro Nonaka, knowledge creation is a spiraling process of interactions between explicit and tacit knowledge. The interactions between the explicit and tacit knowledge lead to the creation of new knowledge. The combination of the two categories makes it possible to conceptualise four conversion patterns. Nonaka also suggests a different approach which facilitates the knowledge conversion for his SECI Knowledge Creation Model. • Socialisation This mode enables the conversion of tacit knowledge through interaction between individuals. One important point to note here is that an individual can acquire tacit knowledge without language. Apprentices work with their mentors and learn craftsmanship, not through language but by

observation, imitation and practice. In a business setting, on-the-job training uses the same principle. The key to acquiring tacit knowledge is experience. Without some form of shared experience, it is extremely difficult for people to share each other’s thinking process. Tacit knowledge is exchanged through joint activities, such as being together, spending time, and living in the same environment, rather than through written or verbal instructions. In practice, socialisation involves capturing knowledge through physical proximity. The process of acquiring knowledge is largely supported through direct interaction with people. • Externalisation Externalisation requires the expression of tacit knowledge and its translation into comprehensible forms that can be understood by others. In philosophical terms, the individual transcends the inner and outer boundaries of the self. During the externalisation stage of the knowledge creation process, individual commits to the group, and thus becomes one with the group. The sum of the individual’s intentions and ideas fuse and become integrated with the group’s mental world. In practice, externalisation is supported by two key factors. First, the articulation of tacit knowledge, that is, the conversion of tacit into explicit knowledge, involves techniques that help to express one’s ideas or images as words, concepts, Figureurative language (such as metaphors, analogies or narratives) and visuals. Dialogues, listening and contributing to the benefit of all participants, strongly support externalisation. The second factor involves translating tacit knowledge of people into readily understandable forms. This may require deductive/inductive reasoning or creative inference (abduction). • Combination Combination involves the conversion of explicit knowledge into more complex sets of explicit knowledge. In this stage, the key issues are communication and diffusion processes and the systemisation of knowledge. Here, new knowledge generated in the externalisation stage transcends the ground in analogues or digital signals. In practice, the combination phase relies on three processes. Capturing and integrating new explicit knowledge is essential. This might involve collecting externalised knowledge (e.g. public data) from inside or outside the organisation and the combining such data. Second, dissemination of explicit knowledge is based on the process of transfering this form of knowledge directly by using presentations or meetings. Here, new knowledge is spread among the organisational members. Third, editing or processing of explicit knowledge makes it more usable (e.g. documents, such as plans, reports, market data). In the combination process, justification – the basis for agreement – takes place and allows the organisation to take practical concrete steps. Knowledge conversion involves the process of social processes to combine different bodies of explicit knowledge held by individuals. The reconfigureuring of existing information through sorting, adding, re-categorising and re-contextualizing of explicit knowledge can lead to new knowledge. This process of creating explicit knowledge from explicit knowledge is referred to as combination. • Internalisation Internalisation of newly created knowledge is the conversion of explicit knowledge into the organisation’s tacit knowledge. This requires the individual to identify the knowledge relevant for one’s self within the organisational knowledge. That again requires finding one’s self in a larger











entity. Learning by doing, training and exercises allows the individual to access the knowledge realm of the group and the entire organisation. In practice, internalisation relies on two dimensions: First, explicit knowledge has to be embodied in action and practice. Thus, the process of internalising explicit knowledge actualises concepts or methods about strategy, tactics, innovation or improvement. For example, training programmes in larger organisations help the trainees to understand the organisation and themselves in the whole. Second, there is a process of embodying explicit knowledge by using simulations or experiments to trigger learning by doing processes. New concepts or methods can thus be learned in virtual situation. Oinas-Kukkonen Model According to Harri Oinas-Kukkonen, there are four phases or sub-processes in the knowledge creation process. Comprehension The author contends that learning begins with comprehension. He defines it as a process of surveying and interacting with the external environment, integrating the resulting intelligence with other project knowledge on an ongoing basis in order to identify problems, needs and opportunities; embodying explicit knowledge in tacit knowledge, learning by doing, re-experiencing. At this stage, the learner surveys the environment around him and interacts with it internally. Communication The Oinas-Kukkonen Model says that, communication is a process of sharing experiences between people and thereby creating tacit knowledge in the form of mental models and technical skills. It produces dialog records, which emphasise the needs and opportunities, integrating the dialog along with resulting decisions with other project knowledge on an ongoing basis. At this stage, the learner gains new information through communication with other people, this results in creation of tacit knowledge that is shared by the people around the learner. Conceptualisation According to the Oinas-Kukkonen Model, conceptualisation is a collective reflection process articulating tacit knowledge to form explicit concepts and systemising the concepts into a knowledge system. It produces knowledge products of a project team, which form a more or less comprehensive picture of the project in hand, and are iteratively and collaboratively developed; may include proposals, specifications, descriptions, work breakdown structures, milestones, timelines, staffing, facility requirements, budgets, etc.; rarely a one-shot effort. Collaboration With new explicit knowledge, the learners are now ready to work together into putting their conceptualised information together, using teamwork, and demonstrate the new knowledge they have successfully created. All of this revolves around, and is a product of, collective intelligence of the learners involved. In other words, the learners now create their own product, thereby converting their developed tacit knowledge into explicit knowledge. The learners can effectively concretise their understanding in a piece of paper or project. Educational model has been derived from the integration of the OODA Loop Model, SECI Model and Oinas-Kukkonen Model

Integration of Three Models Based on the integration of the three models on knowledge creation process, a conceptual knowledge creation model is proposed that is tailored for classroom instructional application. My view is that the knowledge creation process can be simplified into three phases. These phases are derived from the integration of the models discussed earlier. Thus, the new model would be able to simplify the concepts and processes specifically designed for classroom learning. In the workplace environment, people have the mindset to perform their jobs and earn a living. They expect to work and not learn the way they did in school. That is why they don’t carry textbooks, notebooks, calculators and other learning paraphernalia, and they don not expect professors or teachers to lecture them on a certain subject. Workers are oriented to work. That is why, in order to make the workplace environment a learning organisation, orientation or externalisation was included in the knowledge creation process. This is what differentiates the new model to the SECI. model that is popular in the business organisations and the academic world today. The new Trilogy Model of Knowledge Creation Process is composed of three processes the learner must undergo before he can develop and demonstrate his new knowledge. These are the observation and orientation, adaptation and absorption, and manifestation and substantiation*.

ACQUISITION OF KNOWLEDGE Knowledge acquisition is the process of extracting, structuring and organising knowledge from one source, usually human experts, files, folders and databases of the integrated enterprise system. Some authors on this subject also call knowledge acquisition as knowledge elicitation. There are three main topic areas central to knowledge acquisition that require consideration. They are: • First, the business domain and problem domain within must be evaluated to determine if the type of knowledge is suitable for developing into knowledge components to build knowledge strategy for supporting the desired business strategy. • Second, the source of expertise must be identified and evaluated to ensure that the specific level of knowledge required by the organisation to build its competitive knowledge structure is present. • Third, if the major source of expertise is a person, and/or various storage media, the specific knowledge acquisition techniques and participants need to be identified to involve into knowledge initiative. Knowledge based systems attempt to replicate reasoning/pattern recognition of human experts derived by them through particular knowledge and specialised expertise for direct use in DSSs. The assumption here is that DSS is heuristic and readily distinguishable from algorithmic programmes and databases distributed in the organisation. Further, DSS heavily uses expert knowledge intelligence and is not based on just competent or skillful behaviour of the experts. For knowledge acquisition, domain features are important as the problem lies in that particular domain, or the decision making scenario is domain specific. The features are: • First, the domain should be narrow and well defined, and solutions within the domain require intelligent handling. They must not require just common sense. • Second, bona fide experts, generally acknowledged experts in the organisation domain, must exist. *

DJ. Collis and C.A Montgomery, Competing on Resources strategy, HBR, July-August 1995. and others .

• Third, there must be general consensus among experts about the problem definition and accuracy of its solution in the domain. • Fourth, experts in the domain must be able to communicate the details of their problem solving methods to others, i.e., users. Although knowledge base can be developed from a range of sources, such as textbooks, in-house manuals, journals and publications and models and heuristics developed from time to time, the knowledge at the core of all these comes from experts in the organisation and their alliance partners. The reliance on the expertise of the experts is so much that it is required they agree with the goals of the KMS project. Second, the expert should be cooperative and easy to work with and believe in collaborative methods of knowledge exchange and sharing.

KNOWLEDGE ACQUISITION TECHNIQUES (KAT) Knowledge Acquisition Techniques (KAT) can be classified in many ways. One common way is by the manner (direct/indirect) the knowledge team obtain knowledge from the domain experts. Direct methods involve direct interaction through questioning with domain experts on how they do their job. The domain experts have to be reasonably articulate and willing to share information and knowledge to with the knowledge team. The knowledge is difficult to express for the experts as, over a period, the problem resolution or task execution becomes automatic. Indirect methods/techniques are used in order to obtain knowledge that cannot be easily expressed directly. Two ways of classifying KATs are discussed here. One classifies by how knowledge team interacts with the domain expert. Another classifies them by what type of knowledge is obtained from experts. Other factors that influence the choice of KAT are the amount of domain knowledge required by the knowledge engineer, and the effort required to analyse the data, information and knowledge given by the expert. There are several knowledge acquisition techniques each is unique and has a useful role to play in the exercise of knowledge acquisition. The techniques are classified on two parameters, techniques which require direct or indirect human interaction and the second parameter is type of knowledge being obtained from the expert. These techniques are classified in the following manner.

KAT by Human Interaction Knowledge Team made of Knowledge engineers can choose any one of the KATs mentioned below. But the interaction with experts may be direct or indirect based on the choice of KAT made by the team. Interviewing, Case Study, Understanding Protocols, Critiquing, Role Playing, Simulation, Prototyping, Teach Back, Observation, Goal Related, List Related, Knowledge Construct Elicitation, Sorting and Laddering, Document Analysis.

KAT by Knowledge Type Besides being grouped into direct and indirect categories, KAT methods can also be grouped by the type of knowledge obtained. The knowledge types are Procedures, Problem Solving Strategy, Goals/Sub goals, Classification, Dependencies/Relationships, and Evaluation. We will first deal with human experts in particular area and particular domain of organisation’s interest. At the heart of the process is the interview of these experts. The experts have an agreement on the domain model. For example, experts in mobile computing and communication systems agree on the industry domain model, its complexity, general working procedures and practices, and so on.

The process of knowledge acquisition from experts is listed below. • Identify the experts for interview/ interaction from the group of experts satisfying the basic qualification, and from the group of persons solving real problems. • Identify the kind of data, knowledge and procedures followed by them to solve different types of problems. • Build the model scenarios that can be associated with different problem types and their solutions to form class or categories of problems and their solution models. • Discuss the approach taken by them to solve different problems. Identify whether any rationale exists behind these approaches and solutions evolved. • Attempt to develop rules, procedures, and heuristics on the basis of what has been grasped by your knowledge team made of knowledge engineers. Develop rules based on the interviews and solve the problems with them. • Obtain the validity to your knowledge developed in terms of rules, procedures, models, etc., from the experts chosen by you. Have the experts review the rules and the general problem solving procedures. • Put these developments to test as prototype to knowledge users to confirm and get suggestions to improve upon them. What we have discussed so far are the knowledge acquisition techniques to be used on experts, specialists and other human intelligent resources from and within the organisations supported by published knowledge sources to acquire knowledge. We now discuss other supporting methods required for knowledge acquisition.

Set up Operational Goals After an evaluation of the problem domain and the knowledge required, solving the problem by a feasible solution requires, in clear terms, the operational goals to formulate the problem and a framework to solve the problem with feasible solution within the framework of operational goals. The operational goals for finding a feasible solution are: • What is the level of knowledge required to be delivered to the user? • Who are the target knowledge users and what is their level of competence to accept the proposed knowledge? • Is training or learning, required by the knowledge users, in problem domain or knowledge domain? The knowledge team should set these operational goals.

Train Knowledge Engineers It is advised to train the knowledge engineers in the problem domain, if required. If a knowledge engineer has limited knowledge of the problem domain, then training in the domain is very important and can significantly boost the early development of knowledge. The knowledge team made of knowledge engineers should take stock of the situation and make the decision on training.

Create Knowledge Document Once the knowledge development begins, the process should be well documented. While documenting, structured format of the document should be used. The language should be superior so that the intended communication is clear and complete. The writer of the document should have technical writing skills. The

purpose of knowledge document is to the record entire process of acquisition and its intended use in the problem domain.

Develop Scenarios A very common practice of knowledge acquisition is interviewing the knowledge experts. This interviewing practice is more efficient if expert develops well defined scenarios where the required knowledge is used to solve the problem. The scenario describes the process of going through a procedure to arrive at the solution. Familiarity with several such realistic scenarios shout quick understanding of the expert about the knowledge required in solving such problems. In the interview process, acquisition of this knowledge is very systematic and complete. It also helps in structuring the interview process to get better response from the experts.

KAT by Human Interaction Develop Case Study In the case study method, different examples of problems/tasks within a problem domain are considered for knowledge development. The problems consist of specific cases that can be typical, difficult or are model ones. These cases are used as a context within which directed questions are asked in the interview. If a problem scenario can be presented in the case study format, it is the best option for the knowledge engineers team. The case describes the scenario, problem and procedure of solving it. In this case, interviewing is less complicated as all requirements of knowledge acquisition are already documented in a systematic manner in the case format. The case study may describe a critical incident and how it was handled through knowledge application. It could be a simulation of an expected scenario and the problem solution handling, or it could be based on a critical decision to be taken and method the followed to resolve it. The success of case study approach to knowledge acquisition depends upon the critical analysis of the domain and the problems in those scenarios. Most readers must be knowing that there is a methodology in case writing, development and presentation.

Critiquing In this method, the knowledge engineer, or the team, focuses on critical analysis and evaluation of the problem solving model developed, alternatives generated and outcomes obtained. It is critical analysis of problem solving strategy. It is an evaluation of problem solving strategy compared to alternatives. The team then lists the knowledge used in the problem solving process.

Role Playing Role playing is used when the expert is forced to solve a problem. In this process, knowledge engineer team makes critical observation of difficulties felt by the role player in solving the problem and the knowledge used to overcome them. The team makes objective noting of difficulties faced during role playing and knowledge used to overcome those difficulties.

Protocol to Observe Protocols are developed over a period by the organisation to conduct events, execute certain procedures, and interact with each other, keeping in view the status of the parties involved. If protocol is not followed, it is considered wrong or insulting or highly objectionable. In business, one comes across a number of such scenarios, such as receiving a trade delegation, conducting trade negotiations, opening up some internals to

the guest, security measures, and other such scenarios where knowledge practiced over a period at a number of places is termed as protocol.

Prototyping Prototyping technique is used when experts and knowledge team have no prior exposure or experience to solve the problem or deal with the situation. In such cases, knowledge acquisition is attempted by creating a prototype of the problem model and a prototype of its solution. A number of such protocols are tried and evaluated before one of them is accepted as knowledge for development and application.

Observation of the Process This technique is used when experts do not always follow a standard approach, procedure or policy for solving the problem. The primary reason for this is that experts become more knowledgeable and like to attempt a more effective solution. This could be an improvement over the previous one, or a rejection of all previous solutions, and trying a new one. Then the knowledge engineers team prefers to observe the process of solving and makes its systematic documentation.

Goal Related or Oriented Capture Experts and knowledge team have certain desired goals to achieve in certain scenarios of the problems. Interaction between the two is to acquire that knowledge which achieves maximum value of the goal. The knowledge which confirms this achievement is acquired for noting and documentation.

Listing Problem Related Knowledge by Class or Category A problem can be solved by a number of methods, with very little difference in them by any criteria. The list of solutions can then be structured based on technology, application area, type of knowledge, etc, for knowledge users to choose the most appropriate one in a particular case. The methods then are documented in different lists by their worth for use and application in a particular problem scenario.

Laddering the Solution by Approaches A problem domain has a number of knowledge based solution approaches because of different tasks to be done in hierarchical (Laddering) order. They can be laddered in for use depending upon the nature and complexity of the problem. Putting this confirmed list in order is the way knowledge is acquired.

Teach Back to Experts Teach back is a method used by experts to ensure that the solution which is evolved by them acquires third party confirmation before it is acquired for use in the organisation. The knowledge team then proposes to teach the knowledge acquired by them to experts who developed it. In the teaching process, the interaction between the two parties improves the solution. It may under go a change and achieve a better quality of knowledge. This knowledge is then documented for transfer and sharing.

Construct Elicitation The word ‘construct’ is less specific and precise as compared to ‘design’. The construct could be a model, procedure, thumb rule or even a policy to deal with some type of problems as decided by the experts. The construct is described by entities, attributes and their relations. It, therefore, is knowledge for acquisition and documentation.

Conduct Interviews In the absence of the alternatives of knowledge acquisition discussed above, direct interview with experts is the only alternative the team can resort to. Some useful and interesting observations are as under to make interviewing outcome a success. • First few interviews will be unstructured and interactive, and knowledge engineer should make a note of all questions and answers. This would help to build a systematic interviewing approach. • Knowledge engineer should resist the temptation of imposing personal bias on the expert. • Where task can be performed and observed, interview should be conducted simultaneously. Or the expert should be allowed to talk while the task is being performed and the knowledge engineer should witness the task and make notes in detail as the task progresses to conclusion. The interviews could be structured, unstructured, or semi-structured. The success of the interview depends on and varies with the way questions are framed, asked, and understood by the knowledge engineer. Interviewing consists of asking the domain expert questions about the domain of interest, problem, complex scenario, decision requirement and how they perform their tasks. The success of an interview session is dependent on the questions asked and the ability of the expert to articulate his knowledge. The expert may not remember exactly how he performs a task, especially if it is one that he performs automatically. Some interview methods are used to build a particular type of model of the task. The model is built by the knowledge engineer based on the information obtained during the interview and then reviewed with the domain expert. In some cases, the models can be built interactively with the expert, especially if there are software tools available for model creation. We now list different methods of interviewing the experts. The knowledge acquisition methods through the interview process are listed below. • Interview (Structured, Unstructured, Semi-structured) This is a useful method when knowledge is structured and can be described easily in question answer mode. Example: There are a number of situations where questions are asked on phone or mail and answers are given by experts. Over a period, the organisation collects FAQs and its answers which were tested and finalised over a period. This direct interaction of expert with those who put questions is a kind of interviewing process, partly structured and partly unstructured. But after a fair amount of question and answer sessions, the organisation builds FAQs and answers to them, a knowledge which then is posted on the website, or on the knowledge portal for direct access to knowledge users. • Concept Mapping This method is used when knowledge type is ‘concept’ but can be recorded through interviewing the expert. The concept is best understood if described in a’ procedure’ format. Example: The concept of ‘Quality Assurance’ is developed by the organisation over a period after a number of interactions with the customer on number of quality issues, performance issues, etc. The concept of QA is difficult to define because both the words quality and assurance mean different things in each scenario. Does quality means customer satisfaction, superior product performance, no complaints, longer product lifecycle? The expert in this domain finally puts the quality assurance concept in a definition and specification in each subject case so that those in charge of assured quality delivery function understand the concept and work for its delivery. The expert then is asked to lay down a procedure so that concept as knowledge is understood by all.

Experts feel that this concept can best be described by a procedure which is more explicit, easy to understand and measure. So when people on the shop floor are responsible for quality assurance, a procedure, (which is defined for product, service and process in a procedure) is readily available. • Interruption Analysis This method becomes more useful when there is a constant interruption in interviewing because of difficult procedure, or problem solving strategy, and the rationale behind it is difficult to understand. In interviewing process, many times, the knowledge team has to interrupt to understand, in precise terms, what is being delivered as knowledge. Interruption analysis brings in clarity and completeness in knowledge. • Action Based Representation of Knowledge This is used when you are probing the knowledge which has goals and sub-goals network, a relation amongst them, and production rules for action. The interviewing method is such that it extracts action content of the knowledge-the goals and sub-goals and actions which make knowledge complete. Example: All production and service systems are driven by goals and sub-goals and specified actions to archive them. Such systems assess the condition at a particular step and choose the action to move to next step. In inventory management system, stock levels are assessed and, based on the assessed condition, following actions are taken: * Stock is zero, check purchase order status and raise alarm. * Stock is below safety level, send reminder to vendor. * Stock is at reorder level, raise the purchase order. * Stock is beyond permissible maximum, cancel or reschedule purchase order. The goal here is to maintain the desired inventory and the sub-goals are to maintain inventory control parameters (Max-Min. ROL, safety stock and order quantity). • Cognitive Structure Analysis This method is used when knowledge is represented by a structure which makes learning and conceptual understanding of knowledge easy. Example: Product mix problem, influenced by a number of products considered, number of conditions and constraints, and so on, is difficult to solve. Representing the complex problem in multivariate linear programming model for profit maximisation is a cognitive structure analysis and representation of the problem. • Problem Discussion This method is resorted to when knowledge is acquired by problem discussion in a systematic manner. In this method, the knowledge of the problem is correctly understood, defined and modeled for solution. Example: Suppose the organisation is facing the problem of evolving a business strategy to meet the business goals within the scope of vision decided by the organisation. Such complex problem first requires clear understanding of the problem, and knowledge about the problem to easily enable to evolve solution strategies. • Tutorial Interview The method is used when the expert is conducting a tutorial and knowledge engineer listens and questions the tutorial content to acquire knowledge. Example: In many conferences, in company and or third party, tutorial is a method which is conducted for the participants. In these conferences, knowledge team puts questions to get knowledge beyond what the tutorial offers.

• Data Flow Modeling The knowledge is expressed as a data flow by the expert and interview process seeks clarification and reasoning of the flow as modeled. Example: In a number of software applications, understanding data flow is of prime importance. This becomes more critical when data structures are very complex. The data driven system is more a candidate for data flow modeling which gives knowledge about why a data moves in a particular manner, why the particular data enters in to the system at particular stage, and so on. These are knowledge areas containing knowledge about data model, data flow and data processing. The data flow model is displayed in DFD diagram. These diagrams are most often multilayered. • Entity-Relation Diagram The knowledge component has different entities and they have a relation amongst them. The interview process seeks clarification and reasoning of the relationship as modeled. Example: In a system if there are three entities, Vendor, Purchase Order, and Item, all the entities have attributes and relationship with each other. For example, vendor and purchase order have many-to-many relationships. Then vendor and item have many-to-many relationships. Purchase order and item have one-many relationship and item and purchase order have one-to-one relationship. • Object Oriented Modeling The interview process acquires knowledge about object types, attributes and relation between them. Example: Object oriented modeling expresses the scenario in objects. Knowledge team discusses the scenario in terms of objects and their relationship to each other. object oriented modeling bundles number of similar scenarios in concise manner in terms of objects and their attributes. The scenario knowledge is represented by structured and layered model of objects. The advantage of this modeling is that are can modify objects very easily to represent a new scenario. The knowledge of object oriented modeling is extensively used in software development. • Functional Modeling The knowledge is expressed as a functional decomposition. A complex function is decomposed in to sub-functions or smaller functions in the order of occurrence. Some of them are dependent while some are independent. Example: The knowledge of manufacturing or service function is expressed in functional model where each function and its sub-functions have clear goals to achieve. When all goals are achieved, function goal is achieved. • Petri Net The knowledge is expressed as a task network within a function. The functional view of knowledge when expressed in terms of tasks it is a Petri Network. Example: Suppose loading the job on the machine is a function which is to be expressed in terms of a variety of tasks which execute this function. The tasks are represented in Network. • Decision Flow Diagramming The decision making knowledge is expressed as a decision flow by conditions and its probabilistic outcome, in a tree format. Example: There are number of examples of this tree. Du Pont Tree Model of understanding balance sheet and organisation’s performance, Decision Tree Model for investment decisions are a few examples of Decision flow diagramming. • Twenty Questions With this technique, the knowledge engineer develops several scenarios typical of the domain before the interview. At the beginning of the interview, the expert asks whatever questions are necessary to

understand the scenario well enough to determine the solution. Once the expert begins the questions on the scenario and the probable solutions, the expert is asked to explain why each question is asked. In this interaction, when the interviewer perceives a rule, he interrupts and restates the rule to ensure that it is correct. Question and answer session creates the knowledge of solving the problems. • Card Sorting In this procedure, the knowledge engineer prepares a stack of cards with typical solutions to problems in the domain. The expert is asked to sort the cards ‘top down’ according to some important criteria. After each sort, the expert is asked to identify the sorting variable and criteria. After each sort, the expert is asked to repeat the process based on another variable. Note that this technique is usually not as effective as the previous two. During this phase of knowledge acquisition, the interviewer must begin methodically to uncover the more subtle aspects of the knowledge. Typically, this process is based on scenarios. By modifying the scenarios in different ways, the interviewer can probe the expert’s sensitivity to changes in the scenarios.

Use Whiteboard During interviews, it may be helpful to work at a whiteboard to flexibly record and order the exact phraseology of rules or other representations. It may also be helpful to establish recording conventions for use, such as colour coding different aspects of a rule and using flags to note and defer consideration of significant but peripheral details. Structured interviews, the best of the lot, should direct the course of an interview meeting to accomplish the specific goals defined in advance. Other less obvious structures of interviews can be imposed, such as asking the expert to perform a task with limited information or during a limited period of time.

Questionnaires When specific knowledge is needed, a questionnaire can sometimes be used effectively. Questionnaires are generally used in combination with other techniques, such as interviews supported by other aids.

Decision Trees Decision trees are widely recognised to be useful tools for the knowledge engineer in prototyping knowledge representations. In addition, they can be useful in knowledge acquisition on several levels. Some knowledge engineers have found that experts can more readily relate to decision trees than rules.

Rule Development Although complex representation techniques might eventually be used, rules are generally easier to use for characterising knowledge during knowledge acquisition. Prototypic rules should be developed as soon as possible to serve as a focal point for directing the course of the knowledge acquisition process. The initial knowledge base can be developed from written materials or from example cases described by the expert during early unstructured interviews. Initial rules should be treated as approximations and their wording should be general to avoid pressurising the expert. As additional cases are described during interviews, the rule base can be expanded. Once a stable rule base begins to develop, it can provide feedback for structuring interviews. Initially, the rules and procedures can be traced by hand, with the expert considering each step. The same pattern of tracing through rules should continue once a version of the knowledge base is developed on the computer, and its frequent use should become part of the process.

In summary, the recognition of the central role of knowledge acquisition in the development of KMS is a prerequisite for any knowledge engineering project. If problem domain and related scenarios are defined, and experts and specialists are chosen, a knowledge acquisition project’s chances for success will be greatly increased. Once an appropriate domain is identified and a cooperative expert with the necessary stamina is found, then the practical approaches to knowledge acquisition outlined here should be of help. There are several points that need to be emphasised: 1. Knowledge acquisition projects need to be well planned. 2. Initially, the knowledge engineer has the responsibility to define explicit operational goals, consistent with the resources available to a project. 3. Early in the interview process, the purpose of the project and the roles of the participants should be carefully discussed. The discussion should lead to a consensus opinion on what is expected in the final product, who its users should be and how it should be delivered. 4. As the project develops, the operational goals should be consciously reconsidered on a regular basis. 5. The knowledge acquisition process should be carefully planned to match the requirements of the project’s domain expert. For example, time lines that allow for the necessary pre-training, unstructured interviewing and structured interview phases can be developed. 6. Documentation procedures to be used during the project should be defined. 7. Specific interviews or knowledge gathering events should be planned to accomplish specific goals. 8. In pre-training, the goal might be to identify several realistic scenarios, and during the first unstructured interview one of goals the might be to develop a glossary of the expert’s terminology. 9. In planning individual interviews, the knowledge engineer should try to get explicit feedback. Regardless of its size or intended application, the knowledge acquisition process cannot be avoided. Recognition of this is the first step toward successful development of a functional KMS.*

KAT by Knowledge Type Procedures The procedure is a knowledge type where some logic or rationale is used in handling the tasks in the problem solution. Rule, model, process come into this category. These are methods that can be used to determine the steps followed to complete a task.

Problem Solving Strategy The knowledge content is more a strategy evolved based on certain conditions, constraints, resources and confidence in its implementation. These methods attempt to determine how the expert makes his decisions.

Goals/Sub Goals The knowledge is linked to goals and sub goals it achieves on its application to solve the problem. The knowledge on application achieves goals and sub goals under it. These are methods that are concerned with extracting the goals and sub goals for performing the task. * Source Adapted from Information is largely summarized from: Jones, P.H. 1989. Knowledge Acquisition. In: Barrett, J.R. and D.D. Jones. Knowledge Engineering in Agriculture. ASAE Monograph No. 8, ASAE, St. Joseph, MI.

Classification Knowledge is classified for convenience of coding and storage, and then for quick access. The classification of knowledge could be based on technology, customer, product, process and people. It could be work place and intellectual. It could be fact, rule, procedure, heuristics, model, declarative, structured, semantic, and tacit and explicit. These methods are used to classify these entities within a domain.

Dependencies/Relationships Knowledge can be acquired under the banner of dependencies /relationship between different entities.

Evaluation Criteria These methods are used to evaluate constructs, prototypes, designs and models. The evaluation criteria could be cost reduction, performance improvement, reduction in delivery cycle, and so on. Figure 5.8 shows the Knowledge Acquisition Techniques Tree.

Interaction Type

Interview, Case study, Protocol, Critiquing, Simulation, Prototyping, Teach back, Goal Related List related

Direct Interaction with Experts

Role Playing, Observation, Construct, Sorting, Laddering

Indirect Interaction with Experts

Procedures, Problem Solving, Strategy, Goals, Sub goals Classification, Dependencies/ Relationships, Evaluations

Direct Interaction with Experts

Card Sorting

Indirect Interaction with Experts

KAT

Knowledge Type

Fig. 5.8

The Knowledge Acquisition Techniques Tree

Let us illustrate by an example of an organisation

Decide Business Strategy An organisation has developed the following business strategy mix for implementation, based on critical analysis of competition success and emerging business scenario in the next four to five years. These strategies are • Improve resource (Production capacity, Material) utilisation • Improve delivery cycle of existing products • Zero defect product and service quality

Identify Knowledge Areas For this strategy options, identified knowledge areas are:

• • • • • • •

Knowledge for better management of resources Process knowledge to make them lean and efficient Knowledge of process mapping and reengineering People knowledge on process improvement Knowledge of best practices and benchmarks in similar industries Product R&D and design knowledge Customer product requirement knowledge in terms of product application by them and their future direction of product growth • Process knowledge of production and quality assurance of key vendors

Identify Basic Knowledge Elements To build knowledge linked business strategy, it is necessary to identify basic knowledge elements or components. These would be used to build the strategy to implement the vision of the organisation. These are discussed in the following text.

Knowledge for Better Management of Resources The organisation has identified an Enterprise resource planning package (ERP). The identification is recommended by the KM team and the users of the package. The cost benefit analysis is done with the help of vendors of ERP. Its choice is justified based on the attractive ROI. ERP is a knowledge product acquired for implementation.

Process Knowledge After internal study of key processes, it is found that there is scope for improvement through reengineering and process mapping. Benchmark studies show that there is significant scope to improve the processes. On improvement, they would become lean and flexible, enabling the fulfillment of customer needs. Benchmarks of various processes is knowledge.

Process Maps This knowledge is obtained from a consultant, expert in process reengineering using technology, using Visio for process making. The consultant’s engagement was to expedite the process of improvement. The organisation’s team included some members from each process to assist the consultant.

People Knowledge on Process Improvement A workshop on lean manufacturing and process reengineering was conducted by the consultant. Case studies and exercises were used to get precise knowledge of application of these techniques. Case studies and expert trainer offered people knowledge.

Best Practices and Benchmarks This knowledge was obtained by searching on internet and visiting some organisations who claimed to have best practices and processes. This knowledge became a guiding path for a number of improvement activities. It gave the knowledge of technology and its implementation, and knowledge of expected benefits. The consultant chosen for reengineering study was very resource ful in organising these activities. Case studies and exercises were used to get precise knowledge of application of these techniques. The people knowledge was validated by testing, and some exercises in Process Improvement were conducted in a workshop.

• Product R&D and Design Knowledge The exercise identified lot of tacit knowledge about product features and facilities and explicit knowledge about material and technology used in producing better quality product meeting specified customer needs. The tacit knowledge was put to test by the knowledge workers and declared as valid. • Product Requirement Knowledge Marketing management group validated that Identified product requirement knowledge is valid and would support the business strategy. • Process Knowledge of Production and Quality Assurance of Key Vendors Most vendors readily agreed to cooperate and collaborate seeing the larger business interest of theirs and that of their customers. Their participation validates the knowledge offer by them. Figure 5.9 shows the model of Business Strategy and Link to KM.

Business Strategy to Meet Business Goals

Fig. 5.9

Select Knowledge Areas Relevant to Goals

Identify Knowledge Elements to Organise into Knowledge Body

Plan for Obtaining the Knowledge and Building Repositories

Model of Business Strategy and Link to Knowledge

The model explains the process of obtaining the required knowledge and its link to business strategy. What is definite is the business strategy which drives the identification of first the knowledge areas and then the knowledge elements, followed by building knowledge repositories out of knowledge elements required to be used in strategy implementation. In reality, this would be a kind of loop where both strategy and knowledge undergo a change before being freezed. The total body knowledge is validated by the team by testing its application to business strategy and its implementation.

End Notes • In the competitive business of the day, business strategy must be the result of knowledge input developed on business goals achievement. What is being proposed is that for a successful business strategy a consistent knowledge strategy is necessary for successful implementation and for creation of sustainable competitive advantages. • Knowledge, therefore, is a strategic resource of high economic value. Ability to identify such knowledge and acquire it after validation is a high order skill which the organisation should distribute in several locations with experts and in servers and repositories.

• Use of such knowledge as a strategic resource for building knowledge strategy to support business strategy is advantageous. The sustainable advantage comes from the fact that if organisation knowledge is more than competition in many spheres, it is a result of identification of knowledge for business strategy success. • Business organisations of the day have realised the importance of information and knowledge as a cutting edge tool for competitive business management. After successful implementation of various IT solutions and applications, they are now focusing on using the same IT investment for knowledge generation for strategic management of business. • We are taking a broader view of knowledge. We include in its scope that knowledge, which the organisation needs but is not known. Such knowledge may be hard facts, rules, programs, best practices, heuristics, models, knowledge products, and so on. We are not restricting ourselves to the classical definition of knowledge, ‘learning out of experience and developed through SECI model’. • Developing business strategy and its successful implementation is a challenge in the world of global business and global competition. The challenge can be met if strategy is developed by a group consisting of a strategist and people who are responsible for delivering customer requirements. This group should also include some people from the frontline who are interfacing, supporting and servicing customer needs. • SWOT analysis considers knowledge intensive business of the organisation and that of its competition. In this approach, SWOT analysis maps the organisation’s knowledge resources (Tacit and explicit, knowledge products, assets, and so on) against opportunities and threats foreseen by the organisation. This enables SWOT analyst to understand better the advantages and weakness of the knowledge mapped, and probable business strategy options. • Knowledge team should analyse existing organisation knowledge and required knowledge to take the vision forward, and also ascertain the gap between the two. This would lead to an exercise of acquiring knowledge, as knowledge gap is already identified. With full knowledge support to vision and strategy, business strategy would be implemented successfully. • Every organisation in the business has different approach to strategy building because of internal work culture and competition scenario. Each has developed strategy building systems some technology platform, and based on corporate strategy process. Every strategy mix has a link to some intellectual resources and knowledge application skills of the people in the organisation. • A knowledge strategy framework describes the overall approach an organisation takes to align its knowledge resources and capabilities to the intellectual knowledge requirements of its proposed business strategy. The organisation needs to describe and evaluate its current and desired knowledge strategy. The evaluation centres on the area where knowledge needs to be enhanced to offer more benefits to the organisation. It is also influenced by the source of knowledge, internal and external. • The organisation, in this game of closing the knowledge gap, plays the role of explorer, creator and acquirer of knowledge to maintain its competitive advantageous position. The knowledge initiative through the role of explorer, creator and acquirer would be handled by different people or teams as these are specialised areas of knowledge. Besides, its source could be internal or external. • The organisation’s knowledge team must plan and programme various activities of knowledge initiative using technology to expedite the process of closing the knowledge gap. Use of ICT for developing e-learning programmes, conferencing techniques for knowledge transfer to user centres, advancing training programmes for new knowledge initiative, building robust network of knowledge workers and communities are same of the solutions.

• The validation of knowledge is a process which confirms the rightness and appropriateness of identified knowledge for framing business strategy and its implementation. If there are errors in knowledge, there will usually be errors in the performance of its application system. • Logical completeness and consistency are necessary for knowledge to be valid. However, logical completeness and consistency are not sufficient for knowledge validity. Further, knowledge can be logically consistent but not semantically consistent for its intended target application. Semantic consistency occurs when all facts, rules and conclusions of knowledge are true for the intended knowledge application. • Knowledge models are used as proof of correction of knowledge. Therefore, it is important to validate the knowledge models with domain experts. The knowledge model represents the total knowledge identified and coded for further processing. The ability and competence to construct a knowledge model would decide its validation capability. • Though SECI model has some shortcomings, it is the best available model to launch knowledge creation initiative in the organisation. The SECI model in spite of its weakness, is the best bet to begin. • Knowledge is regarded as important for creating organisational value and enhancing organisational competitiveness, especially in an unpredictable environment (Nonaka, 1994). Same is true for learning organisations. In this day and age, knowledge is the key to success of the individual, organisation and even the nation as a whole. Thus, it is imperative that learning organisations must not only have a deep understanding of knowledge construction but must also spearhead its understanding adapted for the changing times. • There are three models of Knowledge Management developed from three different sectors of society at different times. The OODA Loop Model (for Observe, Orient, Decide and Act), a concept applied to the combat operations process, often at tactical, operational tactical and grand strategic level in the military, is adapted today by commercial operations. It was created by military strategist and US Air Force Colonel, John Boyd, in the 1960s. • The SECI Model (Socialisation, Externalisation, Combination and Internalisation) was developed in 1991 by Professor Ikujiro Nonaka of Japan Institute of Science and Technology, and the Organisational Knowledge Creation and Management Framework was proposed in 2004 by Harri Oinas-Kukkonen of the University of Oulu, Finland and Stanford University, USA. The model is called the OinasKukkonen Model. • The new Trilogy Model of Knowledge Creation Process is composed of three processes the learner must undergo before he can develop and demonstrate his new knowledge. These are observation and orientation, adaptation and absorption, and manifestation and substantiation. • Knowledge acquisition/elicitation is the process of extracting, structuring and organising knowledge from one source, usually human experts, files, folders and databases of the integrated enterprise systems. • Knowledge Acquisition Techniques (KAT) can be classified in many ways. One common way is by how directly the knowledge team obtains knowledge from the domain expert. Direct methods involve direct interaction through questioning the domain experts on how they do their job. The domain experts have to be reasonably articulate and willing to share information and knowledge with the knowledge team. The knowledge for the expert is difficult to express as, over a period, problem resolution or task execution becomes automatic. Indirect methods/techniques are used in order to obtain knowledge that can not be easily expressed directly.

• In summary, the recognition of the central role of knowledge acquisition in the development of KMS is important for any knowledge engineering project. If problem domain and related scenarios are defined and experts and specialists are chosen, a knowledge acquisition project’s chances for success would be greatly increased. Once an appropriate domain is identified and a cooperative expert with the necessary stamina and enthusiasm is found, then the practical approaches to knowledge acquisition outlined here should be of help.

Questions 1. Explain the role of the following in the KM cycle: • SWOT analysis • Current knowledge • Knowledge gap analysis • Business case for knowledge initiative • Link between knowledge and business strategy 2. In the first time knowledge initiative of the organisation if the following aspects are taken care of, the KM project leader is in a commanding position. Explain. • Focus first on internal source of knowledge. Being internal, it could be very valuable, unique, and may have high economic value and strategic content. • Form user groups, communities of practices, participate in seminar and conferences to catch the most recent knowledge. • Focus on external sources which are published in journals, magazines, publications of professional bodies. • Enter into alliances with resourceful vendors, institutions, federations. Integration of all three sources may provide a new insight in the knowledge strategy and formulation of business strategy. • Link the knowledge body to business strategy to check whether it supports or not. 3. Explain why knowledge, a candidate for selection for further processing, should be validated. What are the different methods of knowledge validation? 4. Most of the organisations have to make the following decisions. What should be the composition of knowledge components in the knowledge body? • Vendor selection • Material selection • Employee selection • Customer order selection • Job assignment to machine or worker • Product quality • Process quality 5. Explain the role of the following in knowledge validation. • Knowledge model • Source of knowledge, is it a standard? • Experts and specialists

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• True and False test of knowledge • Panel of experts who recommended it • Test it in practice by using it Draw a SECI Model diagram and explain socialisation, externalisation, combination and internalisation. Take an example of your choice and simulate the model to understand the process; tacit to tacit, tacit to explicit, explicit to explicit and explicit to tacit. There are three main topic areas central to knowledge acquisition that require consideration. Explain what would happen if these are not considered properly. • First, the business domain and problem domain within it must be evaluated to determine if the type of knowledge in the domain is suitable for developing into knowledge components to build knowledge strategy to support the desired business strategy. • Second, the source of expertise must be identified and evaluated to ensure that the specific level of knowledge required by the organisation to build its competitive knowledge structure is present. • Third, if the major source of expertise is a person, and/or various storage media, the specific knowledge acquisition techniques and participants need to be identified to involve into knowledge initiative. The list below states KAT by human interaction. Explain the technique in brief. Interviewing, Case study discussion, Understanding protocols, Critiquing, Role playing, Simulation, Prototyping, Teach back, Observation of work, Goal related knowledge, Knowledge construct elicitation, Sorting, Laddering, Document analysis. Outsourcing some processes is chosen as a business strategy to make the organisation lean, cost effective, and for value addition to customer. This is a manufacturing organisation. Use the model of developing knowledge to succeed in this strategy. Develop a knowledge complex to analyse the processes to make a decision of outsourcing. Most of the business strategies in today’s competitive world have customer focus. Suggest a plan of eliciting customer knowledge as a backbone for developing business strategy. Conducting the interviews is one method of identifying knowledge. Explain the use of white board, diagramming of different aspects, such as relationship and flow, Decision tree, Petri net of tasks to make the interviewing technique effective. The list below shows the knowledge types, that is, knowledge is either described, or has focus upon, or is driven by something. In your profession, identify each one of them. Procedures, Problem Solving Strategy, Goals/Sub goals, Classification, Dependencies/Relationships, Evaluation Criteria. Knowledge management process cycle is made of seven steps, as under: • Identify knowledge • Validate knowledge • Create knowledge • Acquire knowledge • Transfer and share knowledge • Measure value of knowledge • Create intellectual capital and intellectual property.

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Execute this cycle by choosing a problem from the personal domain and the professional work domain. What is the difference between SWOT analysis and knowledge driven SWOT analysis. Are both necessary? Why? For home loan processing system of a bank, decide a knowledge framework necessary to make loan disbursement decision most right and of less risk. Specify the entities by name in the framework. For example, you need in the framework a process to conclude that document submission is complete. What is the difference in the following? • Structured interview vs Unstructured interview • Knowledge transfer vs Knowledge share • Knowledge by interaction vs Knowledge by type • Business domain knowledge vs Problem domain knowledge • Developing case study and Developing scenario • Listing vs Laddering vs Sorting When are the following KATs most appropriate? • Prototyping • Observation of the process • Teach back to experts • Role playing Give one example of the following from professional and personal domain. • Action based knowledge • Graphical presentation of the knowledge • Rule as a knowledge • Diagram as a knowledge • Relation as a knowledge In KM cycle, what role and responsibility do the following personnel have? • CEO of the organisation • Business strategist • Knowledge engineer • Knowledge user • Project manager of KM initiative • CTO of the organisation In the following functions, is the person more dependent on tacit or explicit knowledge? • Investment banker • Production planner • Line manager for job planning and loading • Design engineer. • Consulting physician • Online support engineer

6

Chapter

Management: Application Phase (Transfer, Measure, Capitalise and Control)

This Chapter Deals with • • • • • • • • • •

Knowledge Transfer Knowledge Sharing Knowledge Transferring and Sharing Tools Codification of Knowledge Knowledge Mapping Designing Knowledge Transfer and Sharing Strategy Network Structures for Knowledge Transfer Knowledge Asset, Intellectual Capital and Property Skandia Model for Measuring Intellectual Capital Successful Implementation of KM Initiative

Learning Outcome In this chapter, you will learn the steps in the second phase of the KM cycle. These steps focus on knowledge application through knowledge transfer and sharing with knowledge workers. The last step of the cycle in converting some knowledge asset to intellectual capital and intellectual property. You will also understand how knowledge is coded and mapped for transfer, share and adoption for business advantage.

Knowledge Management: Application Phase 189

“Knowledge transfer and sharing is the capability of the organisation, and is a source of competitive advantage in knowledge economy. The factors of effective knowledge transfer at the core are ‘Intent, Trust, Form, Culture’, and largely depend on learning capacity of the people in the organisation: Nicolas Rolland and Daniele Chauvel. Edvinsson model of intellectual capital is built on four pillars-Human capital, Structural capital, Business assets and Intellectual property.” — Lief Edrinson

KNOWLEDGE TRANSFER In Chapter 5, we dealt with the first four steps of KM cycle, from identification to acquisition. The contribution on concluding these steps creates valid knowledge components, tacit and explicit. It relies heavily on the expertise of the human resource in the organisation to make efforts through these steps to produce knowledge components. In this chapter, we deal with the remaining steps in the Knowledge Management Cycle, where knowledge components will be processed from ‘Transfer to Creation of IC and IP’s, as shown in Figure 6.1, designated as ‘Dynamically changing KMS cycle’. Create IC, IP Measure Knowledge Impact

Identify Knowledge Validate Knowledge Vision, Business Strategy

Codify and Transfer to Users to Share

Fig. 6.1

Create Knowledge

First KMS Cycle

Acquire Knowledge Second KMS Cycle and Cycles continue with Changing Dynamics of Business

Dynamically Changing KMS Cycle

In the literature of Knowledge management, Knowledge transfer is a very comprehensive term, which includes not only physical transfer, distribution to the needy locations (Flow Management), but also desire to share, evaluation of knowledge from recipients’ perspective, dissemination of knowledge to wide areas of locations and a number of users, and its formal adoption for intelligent use. It goes much beyond the physical distribution of knowledge. For knowledge transfer to be success, adoption of knowledge is a must.

KEY TERMS • Knowledge Transfer • Knowledge Sharing • Codification of Knowledge • Communities of Practice (CoP) • Knowledge Mapping • KM Strategy • Knowledge Assets • Intellectual Capital • Intellectual Property • Skandia’s Model IC Valuation • Human Capital • Structural Capital • Business Capital.

Knowledge transfer is a culture based process. It is informal and invisible. Formal knowledge transfer is another basic process by which documents, data or other types of knowledge resources are captured and stored in formats in the media that allows retrieval when needed. Knowledge transfer realistically is the transfer of knowledge from one brain to another. Transfer does not mean that knowledge has to be in exactly the same structure at both ends, that of the sender and the receiver. A better way of thinking about transfer is to position it as the growth in current knowledge, increasing its economic value rather than just transferring it. The use of the word transfer implies that the knowledge is physically transferred through the distribution process from one person to another, like exchanging of visiting card. Knowledge transfer, a comprehensive phenomenon, is always a challenge for the organisations for various reasons, technical, managerial and behavioural. Its importance in spite of difficult challenges is now being realised by the organisation. • First, ready access to knowledge, which now forms a substantial percentage of total assets, is a competitive necessity. • Second, organisations have moved away from hierarchical methods of control toward more decentralised and collaborative knowledge driven network organisational structures. This has resulted in more demand for knowledge transfer to share and use for improving performance. • Finally, advances in information and communication technology have created new means of knowledge transfer. Lotus Notes, Internet, and intranets hold the potential for increased diffusion of knowledge through transfer mechanisms. The terms transfer and share go hand-in-hand. The Knowledge transfer process may be automatic or triggered by an individual. Share is voluntary and happens if the individual wishes to share. Sharing is the exchange of knowledge which could be between individuals, within or between teams and knowledge databases and knowledge repositories.

Mechanisms to Transfer Explicit or tacit knowledge can be transferred to share, expand and enrich, using the following options in respective knowledge types.

Transfer of Tacit Knowledge Through • • • • •

Internal consultants made available, as and when required, to all Personnel transfer to the needy location On line, on-the-Job training at work place Conferencing, brain storming in group activity Demonstrating at workplace

Transfer of Explicit Knowledge Through • Forming rules, procedures and directions, tested, documented and made accessible • Conducting seminars, workshops and presentations to interest groups, CoPs • Preparing manuals, templates for e-learning and posting them on organisation portal • Constructing models, diagrams, drawings, images on databases Knowledge transferring is the process of moving knowledge to needy locations, individuals, groups, teams and inter-organisational units, and intra-organisations. Intra and inter-organisational knowledge transfers are essentially communication processes. The knowledge transfer methodology is decided by the character of

the knowledge. If it is tacit then socialisation supported by multimedia technology is the best choice. If knowledge is explicit and coded, knowledge transfer would be best achieved through network, groupware, database technology, and web and internet platforms. Knowledge transfer involves a practical problem of transferring knowledge from one part of the organisation to another (or all other) part(s) of the organisation. Knowledge transfer seeks to organise, distribute and ensure its availability for current and future users, as and when requisitioned by them. It is considered to be more than just a communication problem. It is also just not a knowledge network problem of management. Knowledge transfer is more complex because: • Knowledge resides in organisational members, tools, tasks, and their sub-networks, • Much of the knowledge in the organisation is tacit or hard to articulate (Nonaka and Takeuchi) to make it easily transferable. Argote and Ingram define knowledge transfer as ‘the process through which the recipient individual, group, department, or division is affected by the experience of another’. They further point out that the transfer of organisational knowledge, such as routine or best practices, can be observed/experienced through changes in the knowledge or performance of the recipient. The transfer of organisational knowledge, such as best practices, can be quite difficult to achieve for various reasons. They are: • The inability to articulate knowledge or highly intuitive competencies, termed as tacit knowledge • Geography or distance between two recipients and fulfillment of certain mandatory requirements between two recipients • Limitations of ICTs in handling and transferring knowledge • Lack of mutual identity of recipients in terms of recognition, registration and authentication • Incompatible areas of expertise of recipients • Internal conflicts due to position, competition, power, etc. • Knowledge generated differences in terms of definition, validation, and so on • Lack of incentives and motivational issues to promote transfer • Problems with sharing beliefs, assumptions and cultural norms inhibiting the transfer • Previous exposure or experience with something not very encouraging • Organisational culture non-conducive to knowledge transfer • Lack of trust among recipients These factors or reasons which make knowledge transfer difficult can be classified in to the following classes. • Technical Incompatible technology • Behavioural Sender and receiver are not in sync together. Have conflicts in personal goals. Skills limitation • Cultural The culture of the sender or the receiver does not promote transfer and sharing • Relational No relation of any kind, i.e., customer, partner or professional • Legal/Contractual Sender, by virtue of the secrecy contract, cannot transfer and share knowledge Successful knowledge transfer depends on the well designed transfer process briefly detailed below: • Identifying knowledge holders within the organisation. • Motivating them to transfer and share knowledge • Designing a transferring and sharing plan collaboratively to facilitate the transfer between two recipients

• Executing the transfer plan efficiently, and effectively using appropriate technology • Measuring to ensure that transferred knowledge is being used by the recipients The transfer of knowledge, apart from physical transfer (which includes sharing for gainful use), is handled through the following tools or methods. These are used to ensure that transferred knowledge is used, practiced and improved by the user by virtue of experience in using it. • Mentorship The sender acts as a mentor to the recipient to influence the use of transferred knowledge impacting recipient’s performance. • Guiding and Sharing the Experience The sender interacts with the recipient through guidance and sharing the experience of the knowledge usage. • Simulation The sender uses simulation technique to explain the use of knowledge. Guided experimentation of knowledge is another method to promote the use of transferred knowledge. • Job Shadowing A less experienced performer pairs with a veteran on the job to facilitate knowledge transfer. • Communities of Practice The recipients at either end form communities of practice to encourage transfer of knowledge as well as its effective use in business operations. The practice is a process developed locally, taking in local conditions. Though the goal of the practice at all locations is the same, each practice offers something unique for other practice owners to think and improve. More detailed elaboration on CoP is given in the chapter below.

Components of Knowledge Transfer Process In principle, knowledge transfer can be broken down into four distinct components namely sharing, evaluation, dissemination, and adoption. These component stages overlap in the exercise of knowledge transfer.

KNOWLEDGE SHARING: A PROCESS Knowledge sharing is a process where an individual or an expert group interacts with recipients of knowledge, primarily to expose knowledge to them for its merit from recipients point of view and evaluate its use in their work. For example, a work group might share its ideas in a meeting, where the merits of knowledge are discussed and debated for pros and cons for its application or adoption. Here, sharing refers to the need to expose others to the idea in order for it to be evaluated. Dissemination takes place once knowledge has passed some minimum level of acceptance by value. For efficient and effective sharing of knowledge, it must be ready in the form or frame for recipient to understand, interpret and infer. The subsequent sub-processes, like dissemination, would then be easier. Here, the form and frame of knowledge means it is fairly explicit, documented and coded. Knowledge can be stored for distribution through network. The sharing then is through face to face interaction, hand holding, training, and finally through experiential learning. Nonaka has emphasised the rich interactions between tacit and explicit knowledge. While conventional wisdom on why knowledge is difficult to transfer within firms focused on motivational barriers, Szulanski found that features of knowledge itself and the receiver’s inability to interpret it were two of the most important factors in inhibiting knowledge transfer and share. The second condition required for sharing to succeed is that employees with knowledge must be willing to share it. Sharing takes place at multiple levels, with overlapping but distinct concerns: from a worker to a workgroup, between workgroups, between departments, between business units, and between organisations. Unsurprisingly, Szulanski found that when the relationship between the source and the recipient was distant or problematic, knowledge transfer was more difficult.

Knowledge sharing is the process by which knowledge is disseminated across the organisation. It contains two process dimensions, formal and informal processes used to distribute knowledge throughout the organisation. For example, knowledge can be shared informal processes, such as meetings, seminars and workshops, by using co-workers, company knowledge data-bases and internal documents. On the other hand, informal processes consist mainly of informal discussions between individuals that can be encouraged by the organisation which can define time, space and social initiatives for this purpose. Further, knowledge sharing can be supported by the use of ICT, e.g., Groupware, online databases, data warehousing/knowledge repositories, intranets and decision support tools. The strategy to adopt ICT appears to be one of the most followed managerial practices within the organisations, but just the implementation of ICT does not ensure knowledge sharing. Individuals generate knowledge and they have to be encouraged to share their knowledge; ICT can just be a facilitator. Therefore, an investment in ICT that disregards the human dimension of the knowledge sharing process will inevitably fail. (Source: CiteMan Network Testimonials) Knowledge sharing goes beyond simply viewing and commenting on some documents. It also includes efforts like bringing people from different backgrounds together, debating with purpose the acquired knowledge, using it in business processes and decision making. Knowledge sharing adds further value to an individual’s work experience. The benefits of knowledge sharing are quicker problem solving leading to resolution of status quo, prevention of duplication of effort leading to better use of resources and savings in operations cost, faster delivery times leading to enhanced customer satisfaction, improvement in performance leading to better financial results, improvement in total quality leading to continuing assured business, more innovation, leading to creating sustainable competitive advantage.

Knowledge Evaluation by Receiver The knowledge proposed for transfer and share must be evaluated by its receivers. The evaluation focuses on the point of view of relevance, ease of use and presence of required skills to use. If the ground is ready, the receiver might undertake experimental experience of knowledge before confirming its transfer.

Optimise Knowledge Dissemination In principle, more knowledge is better than less. At the same time, too much knowledge creates overload, confusion and reluctance to use it. The key to disseminating knowledge is that the receiver must be able to use it. Several technological and organisational solutions exist that continuously audit the knowledge portfolio of the user from the usage angle, and if found lacking in usage and adoption in decision making, knowledge is withdrawn or barred for dissemination to the user.

Knowledge Adoption at Organisation Level Knowledge adoption is a sub-process of knowledge the transfer where shared knowledge is actually adopted in practice at organisation level by all. It is observed that even though knowledge is transferred after its evaluation to the right receivers or users, the organisation does not adopt it in formal sense. The reasons for non-adoption by the organisation are inadequate capability of users, poor incentives and lack of suitable management structure to absorb the change due to knowledge adoption.

Aids to Succeed in Knowledge Transfer, Sharing and Adoption The aids to succeed in knowledge transfer sharing and adoption are: • Train people in higher order problem solving and analytical skills using knowledge. • Offer attractive incentives to knowledge users to adopt knowledge.

• Modify and bring in suitable organisational structures whereby transfer and sharing of knowledge is facilitated. • Implement supportive network technology for ease of knowledge transfer. • Create a culture of trust and collaboration amongst the people of the organisation. • Make special efforts to convey the benefits of knowledge adoption.

Training Training to employees should be such that their personal competencies and skills are enhanced. The focus should be on how to generate new ideas using knowledge. New ideas would come from lateral thinking, thinking impossible or thinking out of the box. The competencies include problem solving skills using analytics, modeling and developing decision processing systems. The training programme should also include topics like developing human relations skills, team building and working in team, and providing leadership to the people around. To share knowledge, employees need to be computer literate and technology savvy. They should be good at quantitative methods, AI applications, system modeling, etc. The training programme should handle these topics. Training employees to both disseminate and adopt new ideas may revolve around making them aware of where else in the organisation their ideas may be useful, and from where else ideas may arrive. Employees must also know how to use technology to post and search for new ideas.

Incentives To create an environment that encourages generation of new knowledge and ideas, giving extra incentive to those who contribute is the best policy. The management should consider following the given policies and further encouraging knowledge transfer and sharing for productive application, even though some transfers may not have been successful. • Extra incentive pay for ideas generated by groups or individuals • No layoffs for productivity improvements that follow from new ideas • Job duties that include tinkering, permitting or encouraging experiments that are well conceived but may fail • Giving credit to employees who generate new ideas • Recognition of the employee publicly by displaying the story or event on the notice board, or announcing the contribution in the house journal, or by holding an award distribution function. • Special award to those who contribute through knowledge and ideas benefiting employees or processes in other departments • Rewards and incentive schemes • Recognition in newsletters • Special assignments • Give time off • Share information • Make employees partners • Empower employees • Celebrate success • Increase employability via training

Creation of People Structures The most important component that encourages knowledge generation, transfer and share is the time officially given to experiment and tinker around, using formal or informal employee structures. Other employee involvement structures, such as brainstorming, suggestion programmes, quality circles, communities in network and self-directing teams, support both creating and sharing knowledge. Employees take pride in getting involved in these structures and enjoy the power and the responsibility to make improvements through knowledge contribution. These structures should also be used for evaluation, whether employees are learning out of experience-failure or success.

Technology to Share and Collaborate A number of technologies support knowledge transfer and sub-processes within it. We will cover these technologies in the Chapter on technology. It will suffice to mention here few of them as information to the reader. Intranet, Groupware, Web portals, Video conferencing are the proven and tested technologies whereby knowledge transfer and share is easily possible. Most important and crucial is how to integrate these technologies in other business operations and managerial practices. Knowledge transfer is only valuable when it is integrated into a set of policies for knowledge generation and capture and its application in business operations. Knowledge transfer is enabled by a variety of technologies, including databases, collaboration tools, content management, parsers, search engines, and portals. The tools, used to enable knowledge transfer, allow organisations to transfer knowledge into a data bank and to an employee or a group of employees. There is a cost associated with the transfer of knowledge. The more tacit the knowledge the more costly it is to transfer.

Knowledge Transfer Partnership Knowledge Transfer Partnerships (KTP) is enabling businesses to improve their competitiveness, productivity and performance. KTP achieves this through the forming of a partnership between a business and an academic institution (such as university, further education college or research and technology organisation), enabling the business arganisation to access skills and expertise to help develop business. The knowledge sought is embedded into the business from the knowledge base through a project, or projects, undertaken by a recently qualified person (known as an Associate), and recruited to specifically work on that project.

KNOWLEDGE TRANSFERRING SHARING AND TOOLS* These tools are designed to tap the collective experience, knowledge and expertise of your peers, co-workers and partners, and to more effectively share the results of your work with others. The knowledge sharing tools are simple, quick, and proven to be effective for providing and promoting open, transparent discussion on topics, issues, activities and projects with which you work.

Peer Assists Meeting: Learn from the Collective Experience of your Peers A peer assist is a meeting that brings together a group of peers to get feedback on a problem solved, project under execution or activities carried out. The meeting seeks to learn from participants’ knowledge and

* Source An Evolving Collection of Practical Knowledge Sharing Techniques, Mark Faul, [email protected],KemlyCamachokcam [email protected]

experience with topics related to the problem, project or activity. A peer assist meeting can happen before an activity to help with the planning process, or during an activity to help steer the direction.

After Action Review Meeting: Learn More from Events, Projects and Activities An after action review (AAR) is a meeting to capture lessons learned immediately after an event, project or an activity. AARs should be carried out immediately after an activity or event, while the team is still available and memories are fresh. Retrospect: Learning after your events, projects and activities. A retrospect is an in-depth discussion meeting that happens after the completion of an event, project or an activity to capture lessons learned during the entire activity. A retrospect meeting helps individuals involved reflect upon and learn what happened, why it happened, what went well, what needs improvement and what lessons can be learned from the experience.

Online Communities Meeting: Tapping into the Collective Knowledge of a Group Online communities are groups of people who interact in an online environment to discuss and share resources around a common topic. One type of online community is Community of Practice (CoP), which is ‘groups of people who share a concern, a set of problems, or a passion about a topic, and who deepen their knowledge and expertise in this area by interacting on an ongoing basis’.

Barriers to Knowledge Transfer The transfer process essentially is a person driven action to distribute knowledge at various knowledge centres on the knowledge map. Further, transfer is not a one time act, it has to happen when knowledge needs replacement, when it becomes obsolete or it is enriched and current knowledge needs an update. Having said this, real life knowledge transfer does not always happen most reliably. There are barriers to the act. They are: • Lack of trust among knowledge workers and knowledge creators. The reason could be cultural diversity, language difference or difficulty in communication. • Lack of formal opportunities made available to interact and to transfer knowledge. In view of this, there is a lack of affinity or emotional attachment among the members where knowledge transfer is absolutely essential. In other words, there is no motivation to transfer without fail. • The status of knowledge holder also creates a barrier in the transfer process. Many times, the people in high position suffer from ego and are unwilling to transfer. Also, status conscious people may have political reasons for not transferring knowledge. • Knowledge transfer does not take place because those who are holding it decide its utility and make decision on transfer. They fear that their pride of holding knowledge would be lost. Lack of interest or shear lethargy to act on the transfer may also be the barrens. Once these barriers are handled carefully and set right, knowledge transfer can happen in the following manner: • Systematic planned periodic transfer of tacit knowledge among experts and users. This could be on the initiative of knowledge holder as well as from knowledge users. The methods of transferring tacit knowledge are discussed at length in this chapter. • Systematic planned periodic transfer of explicit knowledge from knowledge centres to knowledge users’ location. If explicit knowledge is of common interest to many, it gets posted on the knowledge portal and is communicated to all through the intranet. If knowledge is not to be posted on the portal but is to

remain in the knowledge base or repositories, the transfer is effected and communicated to users as per specification on the knowledge map.

CODIFICATION OF KNOWLEDGE Codification of knowledge is a process of converting knowledge in the form so that it can be handled by technology to store, transfer, and share. Tools and techniques of codification of such knowledge of high value are discussed here for implementation in the organisation. The form could be a procedure, case study, case history, story telling or digital library. Knowledge codification is organising and representing knowledge whereby its identification and access are easy, and also its form and structure is so designed that user understands it and is encouraged to use it with confidence. The structure and form of code makes knowledge easily usable. The code of knowledge makes it visible, accessible. When we are talking about tacit knowledge, its coding is difficult for obvious reasons. But when it becomes explicit over a period of time, its coding is possible. Coded knowledge should have a suitable identity (Id) and appropriate form of representation. Explicit knowledge is: • Organised in DB structure, file format, text format • Classified by category, nature, ‘where use’ • Indexed for using in IT enabled processes • Has pre-decided access rights, exclusivity • Clearly identified owner, roles and responsibility The form of representation, expression could be • Spread sheet • Decision tree • Decision table • Model for problem solving • Algebraic equations • Drawings, diagrams • Audio, video clippings of knowledge • Indexed procedure in E-manual • Software programmes • Heuristics • Object modeling with complete specification • Production rules • Knowledge product • Intelligent agent • Case • Case analysis • Case study

Codifying Knowledge from Project Experience In project implementation, review and closure meetings, and while writing the final project report, knowledge is created and noted by a number of people working in the project team. It can be documented in a systematic

manner. Experience gained and lessons learnt in solving problems affecting project management, different issues, and methods and models used to resolve them, and so on, can be codified for public awareness and use at large in other projects. This can be achieved in different ways. They are: • Write the procedure evolved or the one improved or modified after experience. • Write case studies in standard format and put them into knowledge repositories. • Write learning histories which combine case facts, problems, approach, context, analysis and solution. • Write about a scenario in a story telling format. • Post on WiKi. • Build a digital library of videos recording notable events and their effective handling for people to watch, learn and apply.

Codify Before Employee Leaves When people retire or leave for another job, the knowledge possessed by them is lost as it is not codified in the organisation. Once their exit is announced, it is very difficult to codify the knowledge as time is very short. It is much better to identify such people and involve them in formal KM activities, making them member of communities, and so on, as a systemic process in their tenure. They should be involved in mentoring, Hindsight and Foresight reviews and other knowledge sharing activities. Such involvement ensures capturing and coding of knowledge. Hindsight and Foresight are the techniques for Hindsight deals with the past, i.e., learning from what has been done and how it has been achieved. Foresight deals with using this knowledge in new projects and tasks to do them better, i.e., learning from application of knowledge. Hindsight and Foresight together avoid repetition of old mistakes and do not require reinvention of the solution.

WiKis: Website Created by Its Users WiKis, a collaborative tool for information and knowledge repository, has been developed by software engineers. This offers a facility to codify knowledge instead of relying on standalone documents for recording knowledge from Hindsight and Foresight, exit interviews, and so on. These standalone documents have limited visibility, content lacks coherence, and knowledge is spread all over the document. WiKis offer user friendly framework for quick access to standalone documents containing knowledge.

Story Telling Stories are real life situations that someone experienced. Experts find sharing stories an easy and effective way of illustrating solutions to problem situations and lessons learned. Story telling is a method for experts to share their knowledge in a way that aids understanding and appreciation for unique situations. It is used in work group meetings, team projects, organisational unit meetings, training courses, and in all formal gatherings. We know story telling is the most engaging and efficient communication tool. We practice it very often in our personal life. This tool is suggested as a tool for codifying knowledge. The technique is good at: • Evoking and engaging interest • Triggering action • Understanding concepts and fundamentals • Striking new ideas • Sharing of contextual knowledge • Promoting norms, values and cultural land marks

• Evoking interest in the subject • Increasing confidence in knowledge and its adoption. A successful story telling event has some features which make it a good codification tool. These features are: • People find themselves in the story • Story teller is seen as a champion • Story structure makes it memorable • Has an element of surprise • Has a positive ending • Leaves behind a vivid image • Focuses on central idea of interest • Use of analogy and metaphor keeps the listener engaged • Focus on action and results

Exploitation of Existing Documents Holding Knowledge During the course of business operations management, project management or transaction processing a number of documents are created by respective employees who record a number of knowledge elements or components. These documents, distributed and stored in business systems, hold the knowledge of economic value. If the number of such documents is small, it may be possible to search the knowledge and codify it for use in appropriate application. But, when number increases, the search becomes difficult and cumbersome. To succeed in the search of knowledge, intelligent search software is necessary to produce manageable number of knowledge hits for user to codify separately in the repositories.

Data Mining Data mining is a processing tool which unearths the knowledge from databases, e-mails, and transaction databases. These tools provide insight into the emerging scenario for knowledge worker to act. Such knowledge on confirmation can be coded for storage and sharing for use. The technology of data mining will be discussed in the chapter on technology.

Yellow Pages of Experts and Specialists By now, it must have been noticed that tacit knowledge is difficult to code and process for transfer and sharing. The shortest way to get knowledge is knowing who has it and how he can be reached, for which knowledge is the safest, quickest and assuring way. The ‘Yellow pages’ is the best way to code people by profile and knowledge so that they can be approached to get knowledge. Yellow pages is a database of experts created for the user to access. A typical yellow page of an expert would have the following data and information. • Name, designation, location, Id, contact numbers, e-mail Id, photograph • Area of expertise, knowledge strength, know how • Membership of CoPs • Web links to pages where the expert has worked and has created specific documents

Building Communities of Practice (CoP) Communities of Practice (CoP) are groups of individuals who regularly interact to share knowledge regarding a particular practice. CoPs exist as project teams, work groups, organisational units, and even as professional associations. These CoPs include people with varying levels of experience who have interest and shared levels of involvement in specific subject areas. They also have a sense of trust and willingness to gain and contribute knowledge to solve problems. Since, KM is acknowledged as HR activity of interaction, collaboration and communication, developing Communities of Practice (CoP) and using it for knowledge sharing is a standard practice. The concept of CoP emerged from the model of matrix organisation where professionals and operations personnel interact vertically and horizontally with the people in the organisation structure for different purpose in different roles. CoP is a people body coming together with single context and interest to help and assist each other through sharing of their experiences, leanings and innovations. Personal benefits and enthusiasm due to the CoP environment are the drivers of CoP. Diverse membership and their participation strengthens the functioning of CoP. CoPs are liked by all as it is a tool which impacts the organisation in the following manner: • Improves Business Performance CoP platform expedites problem solving process producing results in less time. It improves decision making due to visualising multiple perspectives of the problem and assisted by other through knowledge exchange. • Develops Organisational Capability CoPs develop capabilities of managing new challenges and requirements in most efficient manner. The organisation may have number of CoPs, each having different interest and focus, which can be networked enhancing the capability of the organisation. It further ensures adherence to same standards, develops mutual trust, expedites development of knowledge assets providing better service to customers. Through CoP, people work in a network platform of knowledge. • Improve Personal Competencies Due to sharing of knowledge within and across CoPs, people develop different competencies. They become more skilled in application of knowledge, meeting squarely the professional challenges. The key features of CoP are: • They stand alone and have separate identity within the formal organisation structure. • If required, they cut across the organisation boundaries. • Self organising due to flexibility and diverse membership. • Interaction and sharing of knowledge is possible without coming together at one location. They work in virtual mode. • They have terms of reference, domain of operation and generally have common goal due to common interest, personal, organisational and professional. • CoP may have mentors and leaders developed in a natural course of its functioning.

Mentoring Mentoring is a mutually agreed upon relationship in which mentors, experts in the organisation, advise and assist their mentees. From the perspective of knowledge management, it allows individuals to pair with experts, as needed, to learn ways to improve their skills. Its use is effective in individual cases because it allows mentors to share knowledge one-on-one with individuals to enhance their knowledge and skills. It is

the process of providing guidance, as and when sought by the member of CoP or colleague. Mentoring role emerges out of expertise, seniority and maturity. Mentor is a ‘coach’ who influences the process and people without actually participating in it. In this role, he is sharing the knowledge through one of the techniques of knowledge transfer. Mentor is a great asset to the newcomers as they feel at home, are able to improve quickly due to experience and knowledge of the mentor. It also helps to retain knowledge with all members, taking care to secure knowledge if somebody leaves.

Personal Publishing: Web Logs Web logs are personal journals of knowledge workers published on the World Wide Web, or the Intranet. They enable individuals to publish text and images in an easy way. Every entry receives a permanent URI through which it can be addressed later, and is archived in a searchable repository. Interaction between web log-writers and readers is made possible through ‘commenting’: Readers can attach comments to individual entries which appear on the web log visible for the author and other readers. Knowledge workers use web logs to capture knowledge, to document current thoughts, to reflect and to converse with others. It is a tool for voluntary sharing of knowledge. They become personal information repositories of individuals publicly known in the organisation. By publishing web logs, knowledge workers can be discovered by other knowledge workers who have similar interests. The barrier to start communicating is very low. This way, loose connections can develop into deeper relationships leading to formation of CoPs. Web logs support knowledge work by providing a space to capture information, annotate it, reflect, get feedback, share, discuss and network with others. Additionally, they provide organisational benefits: They improve data on the intranet, capture experience, make it visible and disseminate it through story telling. They help to provide ground for a learning organisation and support the forming of networks and communities of practice. Web logs in organisations need not replace other KM and information management systems. They should be seen as a complement to, and an augmentation of, existing systems.

BUILD KNOWLEDGE MAPS Knowledge map is a navigational tool for knowledge worker to find ‘where is what’ and access the knowledge fast for use, or for sharing new knowledge. In the event of new problem confrontation, knowledge map provides information on centres of expertise in and outside the organisation. In case of tacit knowledge identification and capture, it is difficult to verbalise unless it is visualised. One way to visualise is codify the knowledge in a knowledge map. Knowledge map is an equivalent of a site map of website, or the organisation portal. It helps in quickly identifying and locating experts, knowledge databases, and repositories. Knowledge map is an added incentive for people in the organisation to actively involve in KM and related activities. Knowledge map adds efficiency and effectivencess in the working of the organisation. It is an aid to expedite the process of making an organisation a learning organisation. Knowledge map is a visual representation, not a knowledge database. In simple terms, it is a classified directory of experts, documents, videos, drawings, images, and so on. It is a navigational tool pointing out to the user where knowledge of interest is available and how to reach there. In case of tacit knowledge need, it helps to identify the experts in the organisation, and in case of explicit coded knowledge, it helps to identify document, knowledge base, and repositores. The purpose of knowledge map is not just a tool for navigation in knolwedge world, but a tool for expeditious handling of KM processes, such as transfer, share and apply.

It can take multiple forms, from a pictorial display to yellow pages directory, to linked topic or concept map, to BOM lists, materix, knowledge grid, knowledge tree, knowledge product in the form of diagram, software programme drawing, animated learning solution, case study, and so on. Let us illustrate some knowledge expression forms: • Knowledge tree of a raw material Id and Definition Description

Applications in Product

Specifications

Processes

Web links

Material

Preferred Vendors

Inspection Guidelines

Tools Recommended

Storage Instructions

Alternative Materials

Specifications

Processes

• Knowledge product It packages complete knowledge of processes, decisions with objective of maximisation of use of resources at enterprise level. Example: SAP, ERP solution for superior business performance through resource mobilisation (Figure 6.2). SAP ERP is considered as a knowledge product as it comprises best practices of business processes, a knowledge which are may not have. It also provides tools and techniques of business process integration when SAP is implemented in the enterprise. It helps to build queries and reports on KRAs of the business. The product is general but has an ability to get customised to a local situation at ease. This knowledge is unique and one may not have it. SAP ERP is a knowledge product where knowledge of running different processes in an integrated manner is mapped for users to implement so that enterprise resource planning is efficient and effective. On the same lines, organisations develop knowledge products exclusively for their business, based on their processes and practices and business goals to be achieved. These knowledge products could be in the form of Spread sheet, Visio diagrams describing processes of Input – Output, Decision support systems, Forecasting Models, Templates, and so on. When these knowledge products become highly productive they become Knowledge assets. Some of them, over a period, assume high economic value because of their contribution to business. When all such knowledge products are made public and are made available to all concerned in the organisation, they are shared and improved. These products then are put on the knowledge map, explaining where, when and how of the knowledge. The design of knowledge product uses mapping techniques to communicate internal knowledge of the product and offers navigational aids to use it.

Enterprise Resource Planning

In-Store Food Production Integration Product data

In-Store Food Production

Master data management

Marchandise category data (incl Hierarchy)

Recipe management

Store data Goods movement processing

Store group data

Scale management

Supplier data

Order management

Price data In-store production planning

Cost data

Inventory management

Goods movement data Request to execute physical inventory count

...

...

Inventory data Master Data

Fig. 6.2

Transactional data

Master Data

Transactional data

SAP ERP

Bill of Material: Part List for a Component in a Machine BOM maps engineering information and knowledge for manufacturing personnel. Example: Part list of a component displaying engineering data is given below.

Component Name: Code:

Code

Raw Material

Drawing Number

Component Specification

Specification

Drawing Number

Source of Mfg

Inspection

Remarks

BOM is a format designed to pack the knowledge of how to manufacture a component. It gives all details of RM, machine drawing to be used, where it would be manufactured, the inspection guidelines, and so on. It also gives information on backward connectivity to find out where it is used and the function it performs. This knowledge is mapped in the BOM-Part list.

Knowledge Grid-Matrix for Making a Cup of Tea* Knowledge can be mapped in a matrix by some attributes vs processes. Let us take an example of tea preparation where objective is to offer a cup of tea of proper strength, flavour, aroma and temperature. The tacit knowledge of tea preparation is expressed in relation between these attributes and processes which are required to make a cup of tea. The relation is either strong, medium, weak or no relation. This knowledge matrix can be used by anybody whose goal is to make tea of certain attribute specification. For example, if strong tea is to be made, selection of tea becomes crucial as strength and tea have a strong relationship. Processes Attributes

Collect Heat Select Water Water Tea

Boil Tea

Select Pour Add Sugar, Cup Tea Milk

Temperature

NR

SR

NR

MR

SR

NR

SR

Strength

MR

MR

SR

SR

NR

NR

MR

Colour

MR

MR

SR

SR

NR

NR

SR

Flavour

MR

MR

SR

SR

NR

NR

MR

NR

No Relation

SR

Strong Relation

WR

Weak

MR

Medium Relation

Legend

While closing the topic of knowledge mapping, it will be worth to know the entire knowledge competency structure and the need of mapping to users in the organisation. The range of competency spans from global (for all employees in the organisation) to division (only divisional employees) to functional (selected few) to local (individual). The following table models the knowledge competency structure in this order. • Policy, Rules, Regulations, Practices, and Values: Needed by all in the organisation • Product, process customer knowledge: Needed by manufacturing and QA employees • Procedures, Models, DSSs, Domain knowledge: Needed by concerned functional employees • Basic but specific working knowledge competency: Needed by an individual or designated group for the job The knowledge map is built in progressive manner as knowledge portfolio increases and improves. The map is never complete as there is scope for expansion and enhancement.

DESIGNING KNOWLEDGE TRANSFER AND SHARING STRATEGY The design of knowledge sharing programme addresses the following issues.

* Source Adapted from Knowledge Mapping (K-MAP): A Practical Means of Managing Knowledge in Manufacturing Industry, R. A. Ricks and P. V. Evans Technology Strategy Consultants Innovation Centre, Warwick Technology Park, Gallows Hill, Warwick, CV34 6UW. U.K.

What knowledge to share? With whom to share knowledge? How will knowledge be shared? Will knowledge be shared at all?

What Knowledge to Share? The knowledge sharing programme would differ considerably depending on the type of knowledge being shared. Comprehensive, organisation wide programmes for sharing knowledge typically emerge when the organisation’s know how is perceived as critical to its mission, where the value of the organisation’s knowledge is high, and where the enterprise is geographically dispersed. Knowledge sharing aims at making available various types of knowledge in the form required by the users. The tools, techniques, methods and technology would be very different depending on what is proposed to be shared, know how, best or good practices, or knowledge of clients or customers, or competitive intelligence, or knowledge of processes, or people knowledge. In organising knowledge sharing programmes, it is common to put processes in place to ensure that knowledge has certain minimal threshold of value and reliability before it is declared as sharable. Some programmes make no explicit distinction between different levels of reliability of the material offered, once the initial threshold has been met, thus allowing users to reach their own conclusions as to its ultimate value. The programmes that offer external knowledge sharing, provide explicit guidance on whether it has been authenticated, so that users can make inferences about its reliability. Most knowledge sharing systems also allow in varying degrees the inclusion of new and promising ideas that have not yet been authenticated and, in this sense, are not yet knowledge. The knowledge sharing programmes have to cope with the issue of adapting know how to the local context in which it is to be applied. Where the know how is extremely robust and the local context largely predictable, this may not pose so much of a problem. But in most areas of complex activities, or in areas of rapid development, know how is typically less than fully robust, and the local context is often unpredictable; hence knowledge of the local context and local know how becomes very important beforehand.

With Whom to Share Knowledge? One of the major decisions concerns the intended beneficiaries of the knowledge sharing system. Knowledge sharing programmes may aim at sharing with either an internal or an external audience. Internal knowledge sharing programmes typically aim at making the existing business work better, faster or cheaper, by arming the frontline staff of an organisation with higher quality, more up-to-date and easily accessible tools and knowledge inputs to do their jobs, and to add value for clients or save costs. External knowledge sharing poses greater risks than internal sharing programmes — raising complex issues of confidentiality, copyright, and, in the case of the private sector, the protection of proprietary assets — but it may also offer greater potential benefits.

How will Knowledge be Shared? There needs to be a consensus within the organisation as to the principal channels by which knowledge would be shared, whether face-to-face, or by way of help desks, by telephone, fax, e-mail, collaborative tools, or the web, or some combination of the above. It is important not to ignore face-to-face communication, since this is still the best and the highest quality to transfer knowledge between individuals. Many organisations have also found that communities of practice cannot be successfully launched and sustained unless there is face-to-face contact.

Why will Knowledge be Shared? Knowledge management is not something that is undertaken for its own sake, but rather something that supports the business of the organisation. Reaching explicit agreement as to why knowledge is being shared, and its likely contribution to organisational performance, is crucial for knowledge sharing to sustaining support over the medium term if not on long-term basis. The parties in this exercise of transfer and share will fall for it if they are motivated by the awareness about the benefits of knowledge adoption.

Will Knowledge be Shared? In large organisations, discussions of knowledge strategy, knowledge sharing, can go on for long periods without ever coming to conclusion. In the end, communicating the decision of knowledge sharing explicitly throughout the organisation is a key step in launching a knowledge sharing strategy. An explicit decision is critical because knowledge management typically involves a shift from a vertical hierarchical mode of operation to a horizontal boundary crossing mode of operation. Such a shift is unlikely to occur on a sustained basis unless there is an explicit decision at the very top of the organisation that it should occur. Without such a decision, KM will sooner or later face the resistance.*

Knowledge Management Strategy Knowledge Management (KM) comprises a range of well defined processes used in an organisation to identify, create, represent, distribute and enable adoption of insights and experiences termed as Knowledge for the benefit of the organisation and customer it serves. Such insights and experiences comprise knowledge, tacit or explicit, either embodied in individuals or embedded in organisational processes or practices. KM processes typically focus on organisational objectives, such as improved business performance, creation of competitive advantage, creativity and innovation in delivery systems, and sharing of lessons learned for continuous improvement of the organisation. The KM initiative always aims to achieve these benefiting requirements and is handled by well thought out KM strategy or mix of strategies. There are five KM strategies, each having a different focus, of which one you should choose for the organisation. A mix, if suitable, can also be evolved for KMS implementation.

Knowledge Management Strategy as Business Strategy Focus It emphasises knowledge creation, capture, organisation application, renewal, sharing, and use in all the enterprise’s plans, operations, and detailed activities for the purpose of having the best possible knowledge available and used at each point of action in business management processes. This is a core strategy, linked to and influenced by Business strategy.

Intellectual Asset Management Strategy Focus It emphasises enterprise-level management of specific intellectual assets, such as patents, technologies, operational and management practices, customer relations, organisational arrangements, and other structural knowledge assets. Management may centres on renewing, organising, valuating, safekeeping, as well as increasing the availability and marketing of these assets. This strategy is higher in content as it goes beyond knowledge acquisition and application. This strategy provides distinctive competitive advantage to the organisation. * Source Stephen Denning, The Springboard: How Storytelling Ignites Action in Knowledge-Era Organisations. Boston, London, Butterworth Heinemann, October, 1998).

Personal Knowledge Asset Responsibility Strategy Focus It emphasises personal responsibility for knowledge related investments, innovations, and the competitive state, knowledge renewal, effective use, and ensuring availability to others.

Knowledge Creation Strategy for Organisational Learning Focus It emphasises organisational learning, basic and applied research and development and motivation of employees to innovate and capture lessons learned for the purpose of obtaining new and better knowledge that will lead to improved competitiveness. The KM strategy aims at creating a learning organisation.

Knowledge Transfer Strategy Focus It emphasises systematic approaches to transfer obtain, organise, restructure, warehouse or memorise, repackage for deployment, and distribute knowledge to points of action where it will be used to perform work. Includes knowledge sharing and adopting best practices. The strategy heavily weighs in favour of distribution of knowledge for sharing and adoption where possible. (Figure 6.3)

Human and Structural Capital

Embed into Process

Build and Support to Strategy Implementation

Raising Org. Competency Organisation Learning

Fig. 6.3

Business Strategy

Knowledge Adoption

KM Strategy Focus

Raising Org. Productivity

Create

Intellectual Capital and Property

KM Strategy Focus

The choice of which KM strategy to build and pursue is typically based on other strategic thrusts of the organisation, such as technology, market, business direction and the value proposition that the organisation pursues, challenges it faces in business and opportunities it wishes to exploit. Knowledge management strategy would be successful if certain aspects and factors of KM are taken care of. First, KM strategy should aim at building IC assets which are continuously reviewed for their effectiveness. Some steps towards this goal are: • Identify the IC assets need to be created and maintained for business benefits. • Create, transform and provide the required knowledge and ascertain that it is continually renewed. • Ascertain that all available IC assets are leveraged for business advantage. • Provide enterprise wide support, infrastructure and leadership to KM initiative and strategy implementation. Further, within this strategy framework, following sub-steps should be taken: • Ensure understanding of organisation’s vision, mission, strategy and aim of direction. • Focus KM vision and practice to align with enterprise direction. • Provide effective governance for KM practice.

• Promote integrative management culture by fostering a knowledge supportive culture. • Implement and practice accelerated learning programmes of KM initiatives and processes. • Educate employees in professional, craft and navigational skills necessary to deliver quality work products. • Provide opportunities to employees where they can use their capabilities to exploit knowledge assets and knowledge in general. • Motivate employees to act intelligently using knowledge in decision making, designing DSSs, designing knowledge embedded systems and processes. • Create supportive IT infrastructure and application capabilities in people.

NETWORK STRUCTURES FOR KNOWLEDGE TRANSFER Networks play an important role in knowledge transfer and sharing. They are a structures built out of organisations, people in the organisation, CoPs in and outside the organisation, and social network of people of common interest. These networks operate on internet platform supported by computer networks within and across the organisation. (Figure 6.4). Social Network CoP Networks People Networks in Organisation on Internet Organisation

Organisation

Fig. 6.4

Organisations Network

Organisation

Network Structure for Knowledge Transfer and Share

Organisation networks are built formally or informally by way of business relations or through formal knowledge exchange agreements. Such networks serve the business interests of the networked organisation. Federations, associations developed for industry and business, are the organisation network. The people network in the organisation is built to transfer and share knowledge. There is a large network which operates as a platform for knowledge exchange. Within this network, task based, activity based network of individuals or teams are developed. The people in these networks collaborate to perform. In the process, knowledge is transferred and shared. When knowledge is explicit, it gets transferred to all nodes (people) as specified in the knowledge map of the organisation. If the knowledge is tacit, people in the network come together and use suitable tool of knowledge transfer. The next network in the knowledge structure is network of CoPs. CoPs are formed by professional groups whose knowledge interests are common and issues they confront are also similar. Their coming together is

motivated by these requirements. They meet regularly and exchange knowledge for application. The CoPs could be for domain knowledge, or for process or technology. The last network in knowledge structure is social network of people of same rank or position from different businesses and industries. These networks enable socialisation, and interaction helps in exchange of knowledge. The informal chat among members is useful in sharing knowledge. People in social network trigger the action back in their respective organisation based on the knowledge gained in the interaction. All these networks use web technology and IT enabled tools such as e-mail, fax, knowledge portals, servers and repositories, knowledge bases, video conferencing, chat, and voice mail for knowledge transfer and share.

KNOWLEDGE ASSET, INTELLECTUAL CAPITAL AND PROPERTY Knowledge assets are of far greater value than any tangible asset, such as land and buildings, machinery, and many other fixed assets reported in the books of accounts. They provide the organisation a knowledge platform for creating sustainable competitive advantage. The nature of knowledge and knowledge management has given rise to a range of different designs of knowledge management systems that enable organisations to convert their knowledge into actionable information, and into IC & IP. Such an implementation process is a comprehensive course of action that requires focus and commitment throughout the organisation for achieving results. Yet, there is no universally accepted framework or methodology for such process. There are two types of knowledge assets: • Explicit or formal assets like copyrights, patents, templates, publications, reports, archives, knowledge products, etc. • Tacit or informal assets that are rooted in human experience and include personal belief, perspective and values. Knowledge assets are often described as the intellectual capital of an organisation. The value of intellectual capital is often intangible. A popular measure is the difference between the cost of capital assets and the cost of replacing them. Knowledge asset (KA) is a codified knowledge owned by the organisation, combining tacit and explicit, created and stored in electronic media for access and use by the knowledge worker of the organisation to create an economic value of significance. The advantage of knowledge asset is its impact on efficiency and effectiveness of the knowledge worker in business operations and performance. It impacts, enables better decision making in speed and accuracy, as KA is uniquely developed out of experience of solving well defined business problems. It is tested and proven for solving such problems. The problems may be operational or strategic. Its advantages are: • Time saving is valuable as decision maker does not have to get into search mode to find the knowledge and construct a method or model to solve the problem. KA is readily available. • KA is available most reliably world over to authorised users, when needed by them in critical times. Knowledge asset is created through a systematic process of knowledge generation: IdentificationValidation-Creation-Experience of application and Improving to level of value of significance. Once an organisation experiences its value in competitive business management, it is considered an ‘asset’. KA then gets the treatment like of any other physical asset. It is guarded, protected and declared as knowledge to leverage upon, having competitive advantage. Its value goes up with its use over and over again in the strategy of improving business performance.

Knowledge asset is the result of collaborative participation of the knowledge worker, customer, vendor or business partner, experts and specialists, academicians and regulators, such as industry associations, federations and government bodies dealing with intellectual capital, registration and protection. There are four conditions to be verified before a body of knowledge is declared as KA, with exclusive ownership is with the organisation. These conditions are: • Creation of a set of graphical procedure guides, codes, models, and so on, which permit and facilitate a knowledge worker to perform at ease the task, or tasks, independently without further assistance or guidance. • Produces precisely identical results on application of KA to problem resolution. It is proof of accomplishment of correct application. • The result of its application in terms of value conforms to the standard economic measure specified in KA performance specification. • KA is established on verification by an independent authority and is certified by an authority after its assessment. Knowledge asset measurement relates to valuation, growth, monitoring and managing from a number of intangible but increasingly important factors of business success. In the context of knowledge assets, knowledge represents the collective body of intangible assets that can be identified and is measurable. This interpretation of knowledge differs from the notion of knowledge as knowing and learning, which concerns how organisations acquire, share and use knowledge. In contrast, the notion of knowledge assets is about the identifiable aspects of the organisation that, although intangible, can be considered as adding some kind of value to it. Knowledge capital, intellectual capital, is the term given to the combined intangible assets that enable the organisation to function smartly. Examples of such knowledge assets could include shared knowledge patterns, service capability and customer capability.

Definitions of Intellectual Capital* 1. The new source of wealth is not material; it is information, knowledge applied to work to create value: Walter Wriston, former chairman of Citibank. 2. A definition of intellectual capital from a managerial perspective is: ‘The knowledge out of experience, its applied experience, organisational technology, relationships, and professional skills that provide for a competitive edge in the market’. 3. A dynamic version of the definition says that ‘intellectual capital is the knowledge that can be converted into value or profit. It is the value embedded in the ideas embodied in people, processes and customers/stake holders’. 4. A definition that is located more in an information technology framework is that ‘intellectual capital is the intellectual material that has been formalised, captured, and leveraged to produce a higher valued asset’. This definition assumes that knowledge resources can be captured and processed, and that the outcomes from these efforts can exist separately from the people that created them. 5. A fourth perspective is even more active and states that intellectual capital is ‘the ability to transform knowledge and intangible assets into wealth creating resources’. All five definitions are based on knowledge, a source for IC, and talk about value which creates competitive edge over competition. A substantial mass of IC together creates wealth for the organisation. Intellectual * Source www.virtuailes.com-Intellectual Capital

capital can be thought of as ‘the stored knowledge possessed by an organisation’. This knowledge may be tacit. In other cases, it may be explicit, which is codified and stored by the organisation and is available to all employees. Intellectual property is a major component of intellectual capital. All of these definitions are usable and complementary. They all acknowledge that there are intangible resources that are a vital component of the value in an organisation, and that those resources must be recognised and mobilised for the benefit of the organisation. This is true whether that organisation is a forprofit enterprise, a not-for-profit entity, or a public sector institution.

SKANDIA MODEL FOR MEASURING INTELLECTUAL CAPITAL In Skandia’s view, intellectual capital denotes intangible assets, including customer/market capital, process capital, human capital, and renewal and development capital. The value of intellectual capital is represented by the potential financial returns that are attributable to these intangible or non-financial assets. The Skandia model attempts to provide an integrated and comprehensive picture of both financial capital and intellectual capital. Generally, national economic indicators, supported by hard quantitative data, are used for examining the internal and external processes occurring in a country. However, the model questiones if such indicators provide a full and accurate assessment of the country’s assets, and if they provide an indication of its potential for future growth. In doing so, it has developed the framework of intellectual capital as a complement of financial capital. In this model, there are four components of intellectual capital: market capital (also called customer capital), process capital, human capital, and renewal and development capital. While financial capital reflects the nation’s history and achievements of the past; intellectual capital represents the hidden national potential for future growth. The value chain according to Edvinsson and Malone expresses the various components of market value on the basis of the following model: Market Value = Financial Capital + Intellectual Capital The key determinants of hidden national intellectual capital are human and structural capital, defined thus: Intellectual Capital = Human Capital + Structural Capital Human Capital It is the combined knowledge, skill, innovativeness and ability of the nation’s individuals to meet the tasks at hand, including values, culture and philosophy. This includes knowledge, wisdom, expertise, intuition, and the ability of individuals to realise national tasks and goals. Human capital is the property of individuals, it cannot be owned by the organisation. Structural Capital Structural capital signifies the knowledge assets that remain in the organisation when it doesn’t take into consideration human capital that is the property of individual members. It includes organisational capital and customer capital. Unlike human capital, structural capital can be owned by the nation and can be traded. Structural Capital = Market Capital + Organisational Capital Market Capital In the context of the original model applied to market enterprises, this component of intellectual capital is referred to as customer capital to represent the value embedded in the relationship of the firm with its customers. In the context of national intellectual assets, it is referred to as market capital to signify the market and trade relationships the nation holds within the global markets with its customers and its suppliers. Organisational Capital It includes national capabilities in the form of hardware, software, databases, organisational structures, patents, trademarks, and everything else of nation’s capabilities that support the

individuals’ productivity through sharing and transmission of knowledge. Organisational capital consists of two components: process capital and renewal and development capital. Organisational Capital = Process Capital + Renewal and Development Capital Process Capital It signifies national processes, activities and related infrastructure for creation, sharing, transmission and dissemination of knowledge for contributing to individual knowledge worker’s productivity. Renewal and Development Capital This component of intellectual capital reflects the nation’s capabilities and actual investments for future growth, such as research and development, patents, trademarks, and start-up companies that may be considered as determinants of national competence in future markets. Figure 6.5 shows the components of intellectual capital described by Edvinsson and Malone. Market Value

Financial Capital + Intellectual Capital

Human Capital + Structural Capital

Market Capital + Organisational Capital

Process Capital and Renewal and Development Capital

Fig. 6.5

Components of Intellectual Capital

Intellectual capital includes collective employee expertise, knowledge based organisation systems and knowledge products exclusively owned by the organisation. This together is termed as intellectual property. If the organisation’s book value is Rs.100 per share and its stock is being traded at Rs. 500 per share, the difference is termed as intellectual capital, made of human capital plus structural capital. Leif Edvinsson of Skandia offers a model of intellectual capital as shown in the Figure 6.6 The model suggests a scheme for organising four components of intellectual capital and its interaction creating value for the organisation. Human Capital While human capital has always been the primary focus in human resource management, the recent trend is towards intellectual capital rather than focusing solely on human capital. Intellectual capital can be broadly conceptualised as the sum of all knowledge an organisation is able to leverage in the process of conducting business to gain competitive advantage. It is possessed by human resources who can be converted in value through creation of specific routines and procedures, methods processes which are codified, and are tangible. For example, source code of a software is tangible, and has high economic value for the organisation who developed it. IBM, Intel, Infosys, TCS, Qalcomm, ONGC, CSIR Labs are the examples of the organisation that compete on human capital resourceful to generate knowledge and develope it as intellectual property.

Human Capital

Supports

Structural Capital

Fig. 6.6

Creates Innovatively

Business Assets

Generates Knowledge of Economic Value using Business Assets

Develop and Owns

Intellectual Property

Relation and Impact of Components of Intellectual Property

Structural Capital This includes physical infrastructure, such as buildings, networks, hardware, operating systems and so on, and work culture and experience of using the structure for the organisation’s advantage. Organisations like ICICI, HDFC, Sony, Marico, Amul and many more compete and leverage on structural capital, which includes physical structure and distinctive customer oriented work culture. Business Assets This includes business operating units, such as distribution network, R&D units, engineering and design departments, strategy and implementation group and legal and security establishments. Auto companies like Maruti, Tata Motors and Mutual Fund companies, telecom companies are some examples of the organisation that have built business assets. Intellectual Property This includes all that which has been patented and is exclusively owned by the organisation. The IBM, Intel, SAP and cellphone companies are examples of organisations that have built products which are patented and owned by them. It is also a practice to include customer capital under intellectual asset capital. This includes customer relationships by way of preferred customer category, or a kind of partnership by way of inclusion of the products in the customer’s Bill of Material as a standard feature by way of brands, trademarks, and so on. This is a dynamic model where human capital, supported by structural capital and aided by business assets, interact to generate knowledge progressively, taking it to the height of intellectual property. Intellectual property distinctly offers competitive advantage to the organisation. In the competitive environment, it is necessary to measure knowledge capital in general in terms of economic value and strategic leverage it offers before it is declared as intellectual property of the organisation. Knowledge, a composite structure of human capital, structural capital and business assets, is to be measured. Skandia offers five measures to assess the value of knowledge to be declared as intellectual property, labeled as trademarks, patents, copyrights, and licenses. Skandia calls it ‘Navigator’, a group pf measures classified into five categories. The five measures cut across all entities in the organisation, Finance, Customer, Process and Human resource. • Financial measure Income per employee, market value per employee, repeat business • Customer measure Number of customer visits, number of customer calls, lost customers • Process measure IT expense per employee, process productivity, number of benchmark processes, number of knowledge driven or embedded processes

• HR development Training and learning expense per employee, economic value contribution per employee, employee retention rate per period • HR contribution index Patents, trademarks, licenses created, number of exclusive knowledge products offering distinct competitive advantage Having understood the five measures of intellectual capital, property, owned by the organisation, it is necessary to lay down a process for measurement. • Assess leveraging use of IC in business strategy build up. • Develop organisation specific an IC model, a common framework for all to understand. • Develop understandable measures of IC which focus on creation of competitive advantage. • Make these measures a part of MIS, EIS through BSC and score card. • Review these measures periodically to assess their effectiveness. This process implementation ensures that, as organisation and its business changes dynamically, the IC measures are tested for continuity and new measures are thought to assess the changed requirement of knowledge and IC.

Classification of Intellectual Capital Measurement Models According to Sveiby (2004) and Malhotra (2003), there are four basic methods to classify measurement models for intellectual capital:

Market Capitalisation Method The difference between market capitalisation and stockholders’ equity is calculated. This method is useful for illustrating the financial value of intellectual capital, and for inters-firm benchmarking and comparison within the same industry. One of the disadvantages of this method is that it does not provide information on value contribution on the knowledge components contributing to intellectual capital.

Return on Assets Method Tangible assets and the annual financial figures are compared to the industry average. Above average earnings are then used to estimate the value of intangible assets. In this method, the ROA is computed by dividing the pre-tax earnings of the organisation by the average tangible asset and then comparing the result with the industry average. The difference is then multiplied by the organisation’s average tangible asset to calculate an annual earning from the intangibles. Dividing this average earning by the organisation’s average cost of capital or an interest rate gives the value of the organisation’s intellectual capital. The disadvantage of this model is that it does not contain information on value of knowledge components that contribute to intellectual capital. It also has an exclusively monetary focus and is unsuitable for holistic socio-economic and human development approaches.

Direct Intellectual Capital Method Components are identified and valued. In this model the monetary value of the intangible assets is estimated by identifying the various knowledge components of IC. This model allows for the valuation of separate components of intellectual capital. It also allows for combinations of monetary and non-monetary valuation.

Scorecard Method In the scorecard method, various knowledge components of intellectual capital are identified and indicators are generated and reported in scorecard.

A composite indicator based the synthesis of all components of intellectual capital can be created. This model allows for measurement closer to actual inputs, processes and outcomes. The scorecard model is one of the most widely used models in knowledge management. The other measures of measuring IC are proposed by • Karl Eric Sveiby’s Intangible Assets Monitor (IAM). IAM consists of values of External structure (customer and stakeholder, and partners relationships), internal structure (Processes and systems, business units) and competence of the organisation’s employees. All the three are measured and valued for growth, efficiency and stability. • The Inclusive Value Methodology (IVM) of Professor Philip M’pherson. This combines financial and non-financial hierarchies of value using combinatorial mathematics. It is observed that in all systems of measurement, the most widely practiced is the Skandia Approach. The experience of using these systems is that the value they give is context dependent and subjective. Hence IC measurement systems focus on broad measures and improvement in them and do not attempt to find the absolute values. Following steps give a broad approach of using the IC management system, giving a fair amount of correct value of the asset. • Develop an IC model for the organisation by category, namely human, structural and business units. • Develop within each category couple of measures which together help in assessing the value. These measures should be easy to use, and practical and predictable. • Use these measures in the specification of goals and objectives of the organisation. If the organisation has number of business units some of these measures can be used for comparison of these units. • The experience of using these measures will establish their fruitfulness and in terms of cause and effect on the business goals and objectives. • When experience confirms the use of these measures, take them forward to value by one of the methods of your choice. • On conviction of these values, declare them for reporting in appropriate document. We have used the phrase ‘competitive advantage’ a number of times. Let us understand it in clear terms. Knowledge, knowledge products or IC is competitive advantage if and only if the following conditions are satisfied. • Is its potential strength understood by the people holding key positions? • Can it be accessed, learned for usage in decision making by knowledge workers? • Can it create new business opportunities to accelerate growth, more synergy in customer offerings? • Are your customer offers ‘ Product or Service’ intelligent and knowledge driven, making them faster, convenient, comfortable and less costly? • Are you known in the business community and rated as a leader in some aspects of business due to knowledge, knowledge products and IC? • Is your Communication Manager using this advantage in corporate communication, advertising and marketing campaigns? • Are you recognised by different business associations, institutions of standards, industry associations? Have they conferred an award or certificate? • Is your value proposition content dominant due to knowledge, knowledge products and IC exclusivity?

SUCCESSFUL IMPLEMENTATION OF KM INITIATIVE The success of KM initiative is controlled by many factors which are technical, social and managerial. Understanding proactively what these factors are is a critical necessity to succeed. In today’s business climate, some experts consider knowledge to be the first among key factors offering sustainable competitive advantage. With knowledge usage, there are better decisions, more efficient use of resources and organisation’s competence to face the challenge of competition increases. KM system is a multidisciplinary effort whose success depends on organisation culture and supporting ICT platform. There are many barriers to successful implementation of KM of which the most common is people. People are always on the backfoot in participation of KM initiative. There is also inertia of instituting any type of change. An organisation must have individuals, teams, and the organisation as a whole believing that knowledge management is a healthy and normal way to do business. They must be convinced that in the global world, organisation has to be knowledge driven. If the organisation’s culture is not KM friendly, no amount of technology and best knowledge would make KM effort successful. If people really believe that sharing knowledge is essential to the organisation and is in their long-term interest, they will use every available process or technology to share and learn. In addition to culture, management should develop effective policies, procedures and guidelines for the organisation to switch new paradigm. While motivational incentives alone do not guarantee success, they are still critical to becoming a learning organisation where KM would be successful. Rewarding employees helps reinforce positive behaviour, and is one element in changing an organisation’s knowledge based work culture. Recommendations include moving away from individual performance incentives and towards group- or team-based compensation. The goal is to create a sense of shared work and purpose which stimulates collaboration and fosters teamwork. These should be tied into job or project performance reviews as well as annual evaluations. The KM initiative linked approach should, in general, be long-term, and be visible across the organisation. Keep in mind that not all incentives need to be financial in nature. Recognition and acknowledgement by certification also work well. The KM initiative message can be through seminars, bulletins, announcements on website to get employees and managers familiar with KM. The public announcement of this nature takes away the secrecy from KM and makes it a holistic organisation initiative. While the goal of KM is to make organisations smarter and more efficient, this does not happen overnight. KM is an investment in the future of the organisation, and it takes time, money and effort to get there. Time is needed for training, process reengineering, occupying new KM roles, and performing knowledge sharing activities. Investment may be needed to purchase new hardware, software and services for a new KM system. The organisation should take care of this requirement before KM initiative is announced. In nutshell, introduction of KM is a hard core change management issue and it should be handled correctly from all angles. Ultimately, in the game of competition, the organisation should remain agile to face the challenges which would happen on the successful completion of the KM initiative. The organisation would involve itself through KM in the following activities enhancing the benefit potential of KM efforts. • Search for new knowledge • Knowledge assimilation • Knowledge evaluation • Reordering, synthesis of opportunities by chosen criteria of priority • Identifying new growth opportunities and avenues to implement them • Measuring risks in strategy and its implementation • Defining and re-evaluating preferences for changes in systems, processes and strategy

Successful KM initiative calls for going beyond managing HR into adding features and facilities in KM system. KM should be supported by ICT enabled tools to make KM effort a convenient and comfortable proposition. A successful KM initiative team should have competence in: • Leading the project, capable of bringing a management change to knowledge • Changing the organisation structure from hierarchical to network • Building CoPs in relevant areas of knowledge within and outside the organisation • Partnering with academia, research bodies and institutions of knowledge • Bringing on knowledge board consultants, domain experts, technology wizards • Establishing knowledge map for ease of navigation in the knowledge world • Training leading lights in various tools of knowledge transfer and share • Auditing the KMS and knowledge database for confirming its continuing utility to the organisation and to ensure that knowledge overload is not built up • Demonstrating continuing benefits of knowledge for business Over and above these competencies, the KM team should be backed by the management by declaring that KM initiative is a business policy decision and knowledge is a critical resource. The expense and investment budgets should be approved forthwith for efficient and effective KM function. It would ensure that rewards and recognitions are conferred on CoPs for promoting collaboration, sharing of knowledge and demonstration of creativity and innovation in bringing change in the way business is done. The HR function focuses on team building, collaborative working, knowledge networking within and outside organisation. The management appreciates that KM initiative is a paradigm shift in the management process and handles it through a designed change management system. The management would demonstrate the success of KM through exposure to HR and innovation perspective in balance scorecard, scorecard of knowledge enabled key results impacting brand image, and a dashboard showing convincingly the superior performance in key result areas of the business.

Concluding KM: An Interview Extract There is as yet no common consensus on the concept of knowledge management. However, the shared theme is that increasingly, knowledge, as an organisational resource, is of greatest value in the minds of organisational members. This organisational wealth of knowledge is referred by various labels such as knowledge capital, knowledge assets, intangible assets, intellectual capital, and so on. The notion of ‘organisational stock of knowledge’ is often extended to also include intellectual property, such as patents, trademarks, copyrights, etc. A couple of years ago, while in India, I (Dr. Yogesh Malhotra) observed that a major Indian business magazine cover story considered organisational knowledge assets primarily in terms of such intellectual property. However, in the western world, despite the recent boom in outsourcing and downsizing activities, we are observing that organisations are becoming more aware of the value of knowledge that resides in peoples’ heads. On one hand, one observes greater thrust by the HR departments on creating and maintaining portfolios of organisational skill sets in terms of knowledge assets. On the other hand, one observes the bean counters trying to translate the organisation’s intangible assets into dollar figures on the company’s balance sheets so that they may be used for determining the company’s `real worth.’

I take a relatively strategic view of Knowledge Management and would define it in the following terms: ‘Knowledge Management caters to the critical issues of organisational adaptation, survival and competence in the face of increasingly discontinuous environmental change. Essentially, it embodies organisational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings’. First, KM is increasingly important because of the shift from a predictable world paradigm to one governed by discontinuous change. Second, it is essential for organisational survival in the long run, given that knowledge creation is the core competence of any organisation. This knowledge may relate, among other issues, to new products or services, to new product/service definitions, to new organisation/industry definitions, or to new channels of distribution. Third, it is not a separate function characterised by a separate KM department or a KM process, but is embedded into all organisation’s business processes. Fourth, latest advances of information technology can facilitate the processes, such as channeling, gathering, or dissemination of information. However, the final burden is on humans to translate this information into actionable knowledge depending on an acute understanding of their business context. Having the best-ofbreed technologies doesn’t necessarily ensure creativity and innovation that is necessary for organisational competence. Effective utilisation of technology is necessary synchronized with effective utilisation of the creative and innovative capacity of the human components. In this view, KM is not limited to collecting information from various domain experts and creating databases supported by organisational intranets. Nor is it defined in terms of determining the individual knowledge needs of every employee and then trying to parcel out quotas of knowledge that are considered relevant to each employee’s needs. More on the above view of knowledge management is accessible in the following articles.*

End Notes • Knowledge transfer is a very comprehensive term which includes not only physical transfer, distribution to needy locations (Flow management) but also desire to share, evaluation of knowledge from recipient’s perspective, dissemination of knowledge to wide areas of locations and number of users, and formal adoption for intelligent use. • Knowledge transfer is a culture based process. It is informal and invisible. Formal knowledge transfer is another basic process by which documents, data, or other types of knowledge resources are captured and stored in formats in the media that allows retrieval when needed. • A better way of thinking about transfer is to position it as growth in current knowledge increasing its economic value rather than just transfer. The use of the word transfer implies that the knowledge is physically transferred through distribution process from one person to another, like exchanging of visiting card. • Knowledge transferr is the process of moving the knowledge to needy locations, namely individual, group, team, and inter-organisational units and intra-organisations. Intra- and inter-organisational knowledge transfers are essentially communication processes. • The knowledge transfer methodology is decided by the character of knowledge. If it is tacit then socialisation supported by multimedia technology is the best choice. If knowledge is explicit and coded, knowledge transfer would be best achieved through network, groupware, database technology, and web and internet platforms. * Source Interview of Dr. Yogesh Malhotra, Founding Chairman and CKO of BRINT Institute, by the Times of India, the largest newspaper of India, on the topic of Knowledge Management.

• The transfer of knowledge, apart from physical transfer (which includes sharing for gainful use), is handled through tools or methods. These are used to ensure that transferred knowledge is used, practiced and improved by the user by virtue of experience in using it. • In principle, knowledge transfer can be broken down into four distinct components, namely sharing, evaluation, dissemination, and adoption. These component stages overlap in the exercise of knowledge transfer. • Knowledge sharing is a process, where an individual or expert group interacts with recipients of knowledge primarily to expose knowledge to them for its merit from the recipient’s point of view and evaluate its use in their work. • For efficient and effective sharing of knowledge, it must be ready in the form or frame for recipient to understand, interpret and infer. The subsequent sub-processes, like dissemination would then be easier. The form and frame of knowledge here means it is fairly explicit, documented and coded. • Nonaka has emphasised the rich interactions between tacit and explicit knowledge. While conventional wisdom on why knowledge is difficult to transfer within firms has focused on motivational barriers, Szulanski found that features of knowledge itself and the receiver’s inability to interpret it were two of the most important factors in inhibiting knowledge transfer and share. • Knowledge can be shared in formal processes, such as meetings, seminars and workshops, by using co-workers, company knowledge data bases and internal documents. On the other hand, informal processes consist mainly of informal discussions between individuals that can be encouraged by the organisation which can define time, space and social initiatives for this purpose. • The benefits of knowledge sharing are quicker problem solving, prevention of duplication of effort or reinvention of solution, and savings in operations cost, faster delivery leading to enhanced customer satisfaction. • The codification of knowledge is a process of converting knowledge in the form so that it can be handled by technology for transfer, store and share. The form could be a procedure, case study, case history, story telling or digital library, model, algorithm, software programme, knowledge product, and so on. • Knowledge mapping is a process of creation of knowledge map for the users of knowledge to find out ‘where is what’. It highlights location, shows the way to reach and also its best application. • For successful knowledge transfer and sharing, a strategy needs to be designed considering knowledge type, its code and its users. • In organizing knowledge sharing programmes, it is common to put processes in place to ensure that knowledge has certain minimal threshold value and reliability before it is declared as sharable. • The knowledge sharing programmes have to cope with the issue of adapting knowledge, know how to the local context in which it is to be applied. Where the know how is extremely robust and the local context largely predictable, this may not pose so much of a problem. But, in most areas of complex activities or in areas of rapid development, know how is typically less than fully robust, and the local context is often unpredictable; hence knowledge of the local context and local know how before hand becomes very important. • Internal knowledge sharing programmes typically aim at making the existing business work better, faster or cheaper, by arming the front line staff of an organisation with higher quality, more up-todate and easily accessible tools and knowledge inputs to do their jobs to add value for clients.

• External knowledge sharing poses greater risks than internal sharing programmes — raising complex issues of confidentiality, copyright, and, in the case of the private sector, protection of proprietary assets. • There needs to be a consensus within the organisation as to the principal channels by which knowledge would be shared, whether face-to-face, or by way of help desks, telephone, fax, e-mail, collaborative tools or the web, or some combination of the above. • Knowledge sharing, a process in KM, is not something that is undertaken for its own sake, but rather something that supports the business of the organisation. Reaching explicit agreement with the users as to why knowledge is being shared and its likely contribution to organisational performance is crucial to sustaining support to KM over the medium term if not on long term basis. • In large organisations, discussions of knowledge strategy, knowledge sharing can go on for long periods without ever coming to a conclusion. In the end, communicating the decision of knowledge sharing explicitly throughout the organisation is a key step in launching a knowledge sharing strategy. • Knowledge management (KM) comprises a range of well defined processes used in an organisation to identify, create, represent, distribute and enable adoption of insights and experiences, termed as knowledge, for the benefit of the organisation and the customer it serves. • KM processes typically focus on organisational objectives, such as improved business performance, creation of competitive advantage, creativity and innovation in delivery systems, and sharing of lessons learned for continuous improvement of the organisation. The KM initiative always aims to achieve these benefiting requirements and is handled by well thought out KM strategy or mix of strategies. There are five KM strategies, each having a different focus, of which one you should choose for the organisation. • The choice of which KM strategy to build and pursue is typically based on other strategic thrusts of the organization, such as technology, market, business direction and the value proposition that the organisation pursues, challenges it faces in the business, and opportunities it wishes to exploit. • Knowledge assets are of far greater value than any tangible asset, such as land and buildings, machinery and many other fixed assets reported in the books of accounts. They provide organisation a knowledge platform for creating a sustainable competitive advantage. The nature of knowledge and knowledge management has given rise to a range of different designs of knowledge management systems that enable organisations to convert their knowledge into actionable information, and into IC & IP. • There are two types of knowledge assets—explicit or formal assets like copyrights, patents, templates, publications, reports, archives, knowledge products, etc., and tacit or informal assets that are rooted in human experience and include personal belief, perspective, and values. • Knowledge asset is a codified knowledge owned by the organisation, combining tacit and explicit, created and stored in electronic media for access and use by the knowledge worker of the organisation to create an economic value of significance. The advantage of knowledge asset is its impact on efficiency and effectiveness of knowledge worker in business operations and performance. • Knowledge asset is a result of collaborative participation of knowledge worker, customer, vendor or business partner, experts and specialists, academicians and regulators such as industry associations, federations and government bodies dealing with Intellectual capital, registration and protection. • Knowledge asset measurement relates to the valuation, growth, monitoring and managing from a number of intangible but increasingly important factors of business success. In the context of













knowledge assets, knowledge represents the collective body of intangible assets that can be identified and is measurable. A definition of intellectual capital from a managerial perspective is: knowledge out of experience, its applied experience, organisational technology, relationships, and professional skills that provide for a competitive edge in the market. Also, intellectual capital of the organisation is the ability to transform knowledge and intangible assets into wealth creating resources. In Skandia’s view, intellectual capital denotes intangible assets, including customer/market capital, process capital, human capital, and renewal and development capital. The value of intellectual capital is represented by the potential financial returns that are attributable to these intangible or nonfinancial assets. The KM system is a multidisciplinary effort whose success depends on organisation culture and supporting ICT platform. There are many barriers to successful implementation of KM of which the most common is people. People are always on the backfoot in participation of KM initiative. An organisation must have individuals, teams, and the organisation as a whole believing that knowledge management is a healthy and normal way to do business. They must be convinced that in the global business world, the organisation has to be knowledge driven. If the organisation culture is not KM friendly, no amount of technology and best knowledge would make the KM effort successful. The KM team should be backed by the management by declaring that KM initiative is a business policy decision and knowledge is a critical resource. The expense and investment budgets should be approved forthwith for efficient and effective KM function. It would ensure that rewards and recognitions are conferred on CoPs for promoting collaboration, sharing of knowledge and demonstration of creativity and innovation in bringing change in the way business is done. The HR function focuses on team building, collaborative working, knowledge networking within and outside the organisation. The management will demonstrate the success of KM through exposure to HR and innovation perspective in balance scorecard, scorecard of knowledge enabled key results impacting brand image, and a dashboard showing convincingly the superior performance in key result areas of the business.

Questions 1. Explain the status and nature of knowledge when it is ready for transfer. 2. Identify the methods of transfer which are technology led and which are led by expert. 3. The following methods are used for transferring tacit knowledge. Transfer of tacit knowledge through: • Internal consultants • Personnel transfer • On-the-job training • Conferencing • Brain Storming • Demonstrating at Work Place (a) Rank these methods in order of their efficiency for transfer of knowledge. (b) Identify the knowledge cases and scenarios where each is the best method.

4.

5. 6.

7.

8.

(c) What qualities, besides knowledge competency, should a person have if chosen as an agent for knowledge transfer? (d) Suggest different aids the person should have to make the process of transfer more effective. Following methods are used for transferring explicit knowledge. Transfer of explicit knowledge through: • Forming rules, procedures and directions tested, documented and made accessible • Conducting seminars, workshops and presentations to interest groups, CoPs. • Preparing manuals, templates for e-learning, posting them on organisation portal • Constructing models, diagrams, drawings, images on databases (a) Rank these methods in order of their efficiency for transfer of knowledge. (b) Identify the knowledge cases and scenarios where each is the best method. (c) What qualities, besides knowledge competency, should a person have if chosen as an agent of knowledge transfer? (d) Suggest different aids the person should have to make the process of transfer more effective. Before undertaking the task of knowledge transfer, what checks and preparations would you do to make the transfer process a success? You are attending a conference on the subject in which your organisation has a business interest. The conference is attended by experts drawn from different fields of the domain. Your management has requested you to transfer and share the knowledge and information with the board members on return from the conference. Prepare a proposal for yourself specifying different methods of capturing knowledge and information and then sharing it with the board members. The transfer of organisational knowledge, such as best practices, can be quite difficult to achieve for various reasons. • The inability to articulate knowledge or highly intuitive competencies termed as tacit knowledge. • Geography or distance between two recipients and fulfillment of certain mandatory requirements between two recipients. • Lack of mutual identity of recipients in terms of recognition, registration and authentication. • Incompatible areas of expertise of recipients. • Internal conflicts due to position, competition, power, etc. • Knowledge generational differences in terms of definition, validation, and so on. • Lack of incentives and motivational issues to promote transfer. • Problems with sharing beliefs, assumptions, and cultural norms inhibiting the transfer. • Previous exposure or experience with the practice not very encouraging. • Organisational culture non-conducive to knowledge transfer to share. Lack of trust among recipients. In each case (reasons), suggest a solution to overcome the difficulty in transfer of knowledge. You were on deputation to the company to learn new technology and then transfer it to your organisation for implementation. Develop a process for transfer of this technology knowledge

9.

10. 11.

12.

13.

14.

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to a group of senior employees. After the process execution, you are required to form a team for technology implementation. Assume that a ‘Knowledge product is developed and transferred to prospective users in the organisation. Your observation is that knowledge product is not picked or adopted by the targeted employees. Following methods are available to you to promote the use of product. Explain in detail the content of each method and the scenario in which each method is important and preferred. • Mentorship • Guiding and sharing the experience • Simulation • Job shadowing • Communities of practice Find the similarities in design and structure between tourist map of a metro city, site map of a Website and knowledge map of HR of the organisation. Draw a knowledge map to handle the following situations: • Sudden stoppage of the car on the road • Increase in product returns from the customer • Software bugs removal In following organisations what could be the knowledge competency structure. • Call centre for answering insurance claim related queries • IteS organisation for a cellular company • Pathology lab • Selection of a vendor as a business partner/alliance partner Build knowledge grid, or a two-by-two matrix for the following. • Baking a birthday cake • Sudden increase in process rejection violating the control limits • A loyal customer switching to competition You have following KM strategy options, each focusing on one unique aspect of the business: Knowledge Management Strategy as Business Strategy Focus, Intellectual Asset Management Strategy Focus, Personal Knowledge Asset Responsibility Strategy Focus, Knowledge Creation Strategy for Organisational Learning Focus, Knowledge Transfer Strategy Focus. Suggest most appropriate KM strategy focus for the following organisations. • L&T project business unit • ONGC offshore oil drilling centre • Mutual fund organisation. • LIC of India • Cardiac Hospital • A Pharmaceutical company producing drugs for prescription by doctors What is a knowledge asset? When does knowledge becomes an asset to the organisation? When do knowledge assets become does intellectual capital? When does intellectual capital become intellectual property? Classify following knowledge assets into two classes: Explicit or formal and Tacit or informal.

17.

18. 19.

20.

• Copyrights, Patents, Human experience, Templates, Publications, Reports, Archives, Knowledge Products, Legal Adviser, Project Management Experience, Case History Database. Following companies have number of ICs & IPs to their credit. State the conditions which are satisfied by the knowledge asset to become IC & IP. • IBM • Intel • Amway India • Mico Bosch What is the difference between human capital, structural capital, market capital, organisation capital, financial capital and intellectual capital? Explain the importance of the following in the success of the knowledge initiative: • Motivation, Individual vs Group incentive • Acknowledgement, Certification of achievement • ICT infrastructure • Convincing the strong relationship between knowledge and creation of competitive advantage • Relationship between knowledge and creativity and innovation Explain the role of the following in KM system success. • Communities of Process (CoP) • Knowledge map • Codification • Validation of knowledge • Groupware technology • Knowledge networking • Yellow pages of experts • Human capital • Mentoring • Socialisation

7

Chapter

and Learning Organisation (Management of Human Capital)

This Chapter Deals with • • • • • • •

Building a Learning Organisation Five Core Disciplines of a Learning Organisation The Concept of Learning Organisation Organisation Learning Organisation Knowledge Human Resource Management for KM Paradigm Shift in HRM Functions

Learning Outcome The terms learning organisation and organisation learning should be clearly understood. Organisation learning process builds a learning organisation. The five core disciplines are the pillars of the learning organisation. The difference between single loop learning and double loop is clear, and for learning organisation, double loop learning, also called generative learning, is most important. The traditional role of HRM as personnel management and industrial relations (a supportive role), has changed radically to a role of strategic partner in the business, contributing to knowledge development.

s

“In human resource management, in the knowledge economy, adopting a new approach to HR is a formidable challenge. It requires a new focus on building strategic capability, and on managing new roles that expand the methods and process of human resource management.” —Lengnick-Halls

The discussion on the subject of knowledge management so far has given enough evidence that success of KM largely depends on social and cultural factors prevailing in the organisation. These factors play an important role in shaping knowledge initiative, building strategies, spreading knowledge culture and making an organisation knowledge driven. KM efforts are primarily taken on people of the organisation, recognised as human resource, converting them to human capital. The effort is towards winning them to first accept the fact that the organisation needs knowledge capital on first priority in addition to money and machines. The era of business driven by knowledge inputs has already set in. In the knowledge capital, human capital is a major component which brings quality and value to knowledge. The knowledge building initiative would succeed only when people, more particularly the people in the category of experts, specialists, champions, experienced functional professionals and those possessing rare skills and competencies, participate in the initiative process. They must accept that they are leading lights for the knowledge initiative to move forward to a successful conclusion, making the organisation a knowledge driven organisation. This human body of the organisation must change in number of ways to take the initiative forward. They must understand and change to the new approach to business management. They should appreciate the following: • Business model is structurally changed to knowledge driven. • Sustainable competitive advantage and differentiators need knowledge input. • The organisation culture should change from function management to knowledge supported function management. • The focus of management has changed from target achievement to superior performance achievement where knowledge makes all the difference in the outcome. • It is not sufficient to build core competency. It is important to build knowledge capital of the organisation. • The people in the organisation are either creators or users of knowledge.

KEY TERMS • Learning organisation • Organisation learning • Organisation Knowledge • Single loop learning • Double loop learning, or Adaptive learning • Generative learning • Five core disciplines, • Experiential learning • PDCA cycle • A ‘half life’ curve • Systems thinking – fifth discipline.

• The people in the organisation have to change their attitude of holding knowledge to themselves and be more open, social and willing to transfer and share it with others. • The command and control work culture needs to be replaced by collaborative, participative network based work culture where the key is knowledge sharing. • The organisations are no longer top heavy but they are flat and lean. An organisation structure is made of formal and informal groups, teams, communities, working, interacting and using web based groupware technologies. • The time has come to recognise knowledge management, a function of equal importance if not more, as compared to finance, material and capacity of production and delivery management functions. • HRM holds the key to bring in this change in the organisation. • HRM function now goes beyond recruitment, training, manpower planning, grievance handling, mentoring and motivation to building human capital. Building human capital is now a primary focus in human resource management and its research. A recent trend is moving to increased consideration of intellectual capital rather than focusing solely on human capital. Intellectual capital can be broadly conceptualised as the sum of all knowledge an organisation is able to leverage in the process of conducting business to gain competitive advantage. More specifically, intellectual capital may comprise at least three forms of capital – human, social and organisational. All three come under the purview of HRM function. • Human capital refers to individual employee capabilities – their knowledge, skills and abilities, and their willingness to transfer, share and put it to use for business benefit. • Social capital, in contrast, does not reside with any individual. Rather, it reflects the aggregate of knowledge resources embedded within, available through, and derived from, the network of relationships where people in the network have accepted collaborative and participative work culture. • Finally, organisational capital refers to institutionalised knowledge and codified experience stored in processes, routines, models, knowledge products, knowledge databases, patents, manuals, structures, portals, and so on. HRM function drives the knowledge initiative directly, or as a catalyst. That critical mass of human resource of the organisation is the creator and user of the knowledge. This growing focus on social and organisational capital, in conjunction with human capital, presents a much different understanding of the role of HRM in the organisation, and raises many important questions. • How should HRM systems be designed to maximise the potential of a firm’s intellectual capital? • What are the relationships among human capital, social capital and organisational capital? How HRM would make this relationship strong and effective? • Where does intellectual capital reside? Is it within a company, across companies, across countries? How can HRM throw their net on such broad spectrum? • How is knowledge from disparate locations coordinated and leveraged by the people in the network? How can HRM energise and motivate the people on the network to participate aggressively to leverage on knowledge? • How does the management of intellectual capital influence innovation, value creation, performance and competitive advantage? How can HRM create reward, recognition incentive structure to stimulate innovation and knowledge development and its application? • How do we encourage learning, knowledge creation and knowledge sharing among employees?

BUILDING A LEARNING ORGANISATION There are several definitions of learning organisation developed by scholars and theorists. some of these are: • Organisation learning means the process of improving actions through better knowledge and understanding.) —C Marlene Fiol and Marjorie A Lyles • Organisations are seen as learning by encoding inferences from history into routines that guide Behaviour. —Barbara Levitt and James G March • Organisational learning is a process of detecting an error and correcting it. —Chris Argyris Peter Senge popularised the concept of ‘learning organisation’. He describes learning organisation as the one ‘where people continually expand their capacity to create results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspirations are set free, and where people are continually learning how to learn together’. Ikujiro Nonaka characterised knowledge creating company as a ‘place where inventing new knowledge is not a specialised activity …… It is a way of behaving where every one is a knowledge worker’. In the interest of carrying the subject forward, the most simple definition is: A learning organisation is an organisation skilled at identifying, creating, acquiring, transferring, sharing and measuring the knowledge, taking it forward to a level of intellectual capital. It continues to modify its behaviour to reflect new knowledge and insights. The organisations that are learning organisations, translate new knowledge into new ways of behaving. They also believe that learning process needs to be managed through design and not by chance or accident. They believe that policies, practices, systems, specially intended and designed to learn and reflect, are the building blocks that build a learning organisation. Peter Senge suggested five component technologies, namely systems thinking, mental modeling, shared vision, team learning and personal mastery. David A Garvin developed these five technologies in practical terms into five activities. The organisations which practice these activities are learning organisations. David A Garvin’s activities are further divided into seven, as under: • Systems approach to problem solving • Experimenting, prototyping • Learning from own doing, past experience: Study of success and failures • Learning from others experience • Learning from best practices elsewhere • Transferring and sharing the knowledge • Working towards building intellectual capital and property

Systems Approach to Problem Solving The systems approach to problem solving calls for systematic thinking on the lines of Herbert Simon Model of Decision Making to solve the problem. (Figure 7.1) The model is a three step approach to make a decision in a problem situation. In the first phase, intelligence made of data, information and knowledge is gathered and analysed. This process defines the problem clearly in its entirety. In the second phase, the problem is modeled to generate solution alternatives, which could be several. In the third phase, decision maker chooses a criterion to select one alternative, a decision. If the problem design is not satisfactory in the first cycle, the model recommends to go back to gather more data,

*Gather Intelligence

Design Model, Develop Solution Alternatives

*Includes Data, Information and Knowledge

Make a Choice of one Alternative

Fig. 7.1

Herbert Simon Model of Decision Making

information and knowledge. If the problem is clearly defined and sufficient number of solution alternatives are generated, then model recommends choosing a criterion to make one choice of solution out of many. If the selection is difficult and not satisfactory, model recommends to either go back to design stage or to gathering intelligence. This recursive process teaches a lot to the decision maker. Learning organisations follow the systematic approach to decision making and improve their knowledge. In each cycle of the effort of making a decision to solve the problem, knowledge of the decision maker is improved. The model building skill is improved, ability to generate number of innovative solution ideas is improved, and the analytical skill to select one out of many improves further the knowledge of analytics. The organisations practicing systems approach and Herbert Simon Model for Decision Making at all levels for operations and strategic decisions become learning organisations. Another popular systems approach to planning and control is developed by Deming. The model is popularly known as PDCA Cycle. (Figure 7.2) The model is simple to understand and easy to follow. ‘Plan, Do, Check, Act’ cycle is known as PDCA cycle. In the planning phase, the goal is decided, plan to achieve goal is made, resources are mobilised and allocated. In the next step, ‘ Do’, the plan is executed and results or outcome are measured. In the checking phase, results are valued in terms of expectations and, if found unsatisfactory, action is taken to improve upon the plan and resources allocation. And the cycle continues. In each cycle, individual or a team learn a lot leading to the improvement of their current knowledge. The learning organisation practicing PDCA approach gets number of opportunities to improve the knowledge portfolio. The improvement is in quality of knowledge and its value.

Fig. 7.2

Plan

Do

Act

Check

PDCA Cycle of Problem Solving

In PDCA cycle, focus is on checking the problem solving approach and its implementation plan. If the results are not satisfactory, PDCA cycle demands new approach and new plan for resolution of the problem. In systems approach, the decisions are made using decision making tools, such as modeling the problem, generating solution alternatives and selecting one alternative which satisfies the chosen criteria. It uses decision

tree or decision table approach in framing the problem and incorporating the conditions and constraints and then deciding where the problem scenario lies. In solving the problem systematically, the goal is either minimisation or maximisation of the relevant objective. The system analyst pays attention to quality of data and its source, the assumptions are questioned and data is cleansed before putting into use in any one of the approaches mentioned here. The systematic approach also uses statistical tools for data analysis, variation analysis, testing of hypothesis, and so on. If experiments are conducted, they are designed on the principles of ‘Design of Experiments’. In systems approach to problem solving these methods are used. In the learning organisation, people continue to learn out of experience they get by resorting to these methods. The learning is on two accounts, first the problem and best choice of tool is understood, and their second better insight is gained in to problem definition and the results it gives impact on the performance. This knowledge gained out of experience of solving different problems then becomes organisation’s knowledge capital embedded in the people and knowledge products.

Learning from Experimentation and Prototyping Experimentation is an activity undertaken by the organisations where identified knowledge needs to be tested and validated before it is taken into creative process and acquisition. If knowledge passes the test and checks for validation, only then is it taken into store for using it directly or along with other knowledge entities. Since, knowledge in question has not been used before its identification it is tested through an experiment. The experiment results prove the strength of knowledge, suggesting whether it should be taken in to the knowledge portfolio. The experiments need to be designed with proper input output specifications and expected results clearly identified. If the results of the experiment of new knowledge give the results that fairly match the expected results, it is further codified, mapped and transferred for sharing. The newfound knowledge could be about material property, technology or new customer segment suggested by data mining exercise, throwing a new opportunity for product modification with additional features. Since this is knowledge captured and not used in any manner, an experiment is conducted in the market segment by putting the product with the required features. The test market experiment gives additional precise knowledge and also its efficacy in terms of market impact. If these results are encouraging, a product modification programme is undertaken. Developing a small batch of the product with new features and marketing it in a small area of the market segment is an experiment. This experiment confirms a number of things about the newfound knowledge of the product and the market segment. Prototyping approach is taken when knowledge is not totally newfound but needs to be tested, as there is some risk in using it directly. Such knowledge is used in prototype, which could be a product, or process, or technology. The prototype approach saves time and cost and controls the risk of implementation when implemented subsequently. Experimenting and prototyping approach is taken when knowledge is unique in nature and its application may turn out to be a innovative. The learning organisations are continuously in experimenting and prototyping mode of knowledge as they are constantly required to innovate. The experiments are carried out to test new knowledge in R&D, shop floor, engineering, products and processes and in customer segments. Some experiments and prototypes may be successful and some may not be. In either case, the experience of experimenting and prototyping provides new insight in the area of experimentation. The learning organisation thereby becomes richer in knowledge.

Learning from Experience: Study of Success and Failures Learning organisations periodically review and research into successes and failures. Normally, successes are few and failures are more. In all cases, lots of revelations emerge, new insights and directions are found. This is a new learning of strength useful for incorporating into the knowledge base. The study could be of product launches, new material usages, findings of quality improvement programme, strategy successes and failures, and so on. The organisations bringing out products at frequent intervals rely on the experience of launching new products. They have large knowledge base about design, technology, process design, material and material sciences. They also have enhanced knowledge about customer requirements, perceived by customers and articulated by them in specifications, features and facilities.

Learning from Others Experience Not all knowledge in a learning organisation is found inside it. Often, more valuable knowledge is found outside the organisation. The learning organisations make special efforts and step out to capture knowledge from various sources outside it. The organisations encourage their employees to form Communities of Practices (CoPs) in their areas of interest. The employees are encouraged by sponsorship to become members of professional bodies and clubs where knowledgeable people come together for social get together. These bodies announce seminars, workshops and conferences on the subject of current interest as well as on emerging subjects. The learning organisations ensure that employees participate in these events and bring home new knowledge, innovative ideas, prospects of new business opportunities, and so on. Many times, learning from others breaks deadlocks and bottlenecks. Learning organisations make special efforts to learn from experiences of value adding partner organisations developed in the course of business management. The value adding partners contribute significantly to the organisation’s business. In order to continue the relationship, the partners continuously develop knowledge in their domain of operation. This knowledge could be of immense use in the organisation. The learning organisations enter into alliances and partnership agreements to exchange the knowledge. The relationship between the organisation and its value adding partners is mutually beneficial due to knowledge exchange. Learning organisations sponsor research projects in reputed research organisations and the benefit from the research findings. The topic for research of business interest could be suggested by the organisation to the research organisation. Hence, instead of investing in internal research facility, organisations find such sponsored research to be more cost effective. Learning organisations continually benchmark their processes, products, services, and so on. Benchmarking indicates the gap between the best and their process, product and service. Benchmarking is a process of analytical comparison between two comparable things. The organisations continue to benchmark critical processes and adopt the best one in the organisation. It is one way of getting outside perspective on their critical processes, products and practices. The process is a source of new ideas. The benchmarking process could be through dialogue with customers and value adding partners. The dialogue brings out number of ideas, perspectives, insights, and so on, which is knowledge to the people in the organisation.

Transferring and Sharing the Knowledge Learning organisations are very strong in transferring and sharing knowledge with all centres of work. The network infrastructure of knowledge worker is in place over and above the communication and data flow network. It is very difficult to become knowledgeable in a passive way. Knowledge may be transferred but it

may not be digested so as to reap the benefits. Hence, standard methods of reporting posting are not effective. Whenever interaction mechanisms are used, knowledge is not only transferred but is also stored and used when required. Learning organisations generally resort to the following methods of knowledge transfer: • Personnel rotation at work centres • Deputation for a limited period • Working together and hand holding • Demonstrating and exhibiting • Transferring line manager to staff function Learning organisations have real and virtual networks of individuals and teams who interact regularly to transfer and share knowledge. Traditional command and control structure is used for administration while network structure is used for knowledge transfer and share (Figure 7.3). Command and Control: Top down (Execution by Command as Directed)

Fig. 7.3

Network Team Structure: Collaborative (Execution by Team, Knowledge Sharing)

Command and Control and Network Organisation Sructure

Learning organisations promote their employees to work in a virtual network, using internet/intranet/ extranet network. For a given problem resolution, a real time team formation is necessary. And it is quite possible that all are not at their formal work desk. The employees quickly assemble in virtual mode by logging in and collaborate to resolve the problem. Extensive use of virtual networks teaches a lot to team members who probably may not get opportunity to interact or work together. Learning organisations take formal steps to establish networks, provide tools to work with, and create opportunities for interaction, and so on. They also go ahead and establish a method of measuring the impact of learning of knowledge in their organisations. The standard methods of measuring the impact of knowledge initiative are to check its reflection in the organisation scorecard and dashboard. But, this might come up too late to react. Another measure is developed, known as ‘ half line’ curve. The method is invented by Analog Devices, a leading semiconductor manufacturer, to measure and compare internal improvement rates. A ‘half life’ curve measures the time it takes to achieve 50 percent improvement in a specified performance measure. The performance measures could be defect rates, on time delivery, time to market, time to respond and so on. These measures are put on Y-axis in a logarithmic scale and time is plotted on X-axis. The slope of the curve is a measure of pace of learning. The steeper the slope the faster is the learning. Figure 7.4 illustrates the example. Measuring the learning pace in four divisions where an attempt is made through learning to improve the time taken for customer deliveries.

100 %

Div. A

Div. B

Div. C

Div D

10 % 1% Div. A: No improvement in late deliveries, No learning: Flat curve Div. B: Some improvement in late deliveries, some gain of learning: Some slope in curve Div. C: Rapid improvement in late deliveries, learning at rapid pace: Deep slope in curve Div. D: Meager improvement in late deliveries, slow learning: Little slope in curve Division C is best and Div. A is very poor in reducing late deliveries.

Fig. 7.4

Half line curve showing improvement in reducing late deliveries (Source: Ray Stata, ‘Organisational Learning—The Key to Management Innovation’, Sloan Management Review, Spring 1989: HBR on KM by David A Garvin)

The logic behind half life curve is very simple. Those who learn fast will show faster improvement rate. The 50 percent target is a measure of convenience. The roadmap of learning organisation has three milestones: • Cognitive: Exposure to new ideas, expansion of knowledge and thinking differently • Behavioural: Internalise by practicing the use of knowledge and change in behaviour • Performance: Shows measurable significant improvement in Key Result Areas The successful organisations in todays’ competitive world are, in some way, learning organisations. The road map shown here may not be so visible in these organisations but the results and learning efforts behind their success is evident. The underlying process through these milestones first exposes to knowledge, then creates receptivity to it, and finally disseminates it to users in the organisation. Over a period, once the experience of KMS is satisfactory, critical KM activities are institutionalised. We however can model the characteristics of the learning organisation.

FIVE CORE DISCIPLINES OF A LEARNING ORGANISATION The theoretical findings of organisational learning and other research in organisational development, system theory, and cognitive science prescribe specific recommendations about how to create organisations that continuously and effectively learn. It has been developed by Peter Senge.The five disciplines (Organisational Pillars) were originally outlined in 1990 in the book ‘The Fifth Discipline’ The Art and Practice of the Learning Organisation, and are the core pillar of strength to organisational learning efforts. There are many other discipliness that support and expand on the above five. They are: • Shared Vision • Team Learning • Systems Thinking • Mental Models • Personal Mastery These pillars stand tall on the foundation of five corporate entities, Culture, Responsibility, Leadership, Dialogue, and Work-life Balance. (Figure 7.5)

Organisation

S H A R E D V I S I O N

T E A M L E A R N I N G

S Y S T E M S T H I N K I N G

M E N T A L M O D E L

P E R S O N A L M A S T E R Y

Corporate

Fig. 7.5

Peter Senge’s Five Pillars of Learning Organisation

Shared Vision It is not an idea…. rather a force of impressive power. It lifts us out of our existing aspirations, and opens the doors to new ones, forcing us to learn more. It gives a real sense of purpose providing the focus and energy for learning. The learning organisations and high performing teams can not excel without sharing individual vision. It promotes a long-term commitment to organisational effectiveness and survival, as shared vision is developed with every one’s input. The learning organisations encourage individual vision but ensure through action that they are shared and a new vision emerged. Shared vision emerges when everyone in an organisation understands what the organisation is trying to do, is genuinely committed to achieving that vision, and clearly grasps how his or her role in the organisation can contribute to making the vision real. Practicing this discipline involves knowing how all the parts of the organisation work together and being clear about how each one’s personal goals align with those of the organisation. A shared vision among the people of the organisation brings clarity to everybody about ‘What the organisation intends to create? Shared vision is vital for the learning organisation the because it provides focus to work upon and energy for learning. It is impossible to achieve something concrete without a vision and its sharing with those who can contribute to its advancement. A shared vision makes every piece of work a part of a bigger endeavour such as new product launch, changeover to new technology, launching a product in new market, and such other path breaking activities. Visions are exhilarating as they strike a spark and excitement in the people of the organisation. Shared vision

is the most successful tool to build relationship and trust among the team or the people in the organisation. It creates common identity and purpose for work. Shared vision, because of its strength, gives courage to handle risk and experiment. Because of the vision shared entire team, they finds it easy to use system thinking to resolve the problem. Abraham Maslow study of high performing teams revealed that the one most common thing among performing teams was shared vision and common purpose among the team members.

Team Learning Team learning is the process of aligning and developing the capacity of a team to create the results its members truly desire. It is team learning, not individual learning, that adds to organisational learning. Team learning is best when team members understand that: • People need each other to achieve their personal and team objectives • Teams are the key learning groups of organisations • Talented teams are made up of talented individuals • Team learning is the building block for organisational learning where each member is capable of learning individually Team learning is what happens when a group of people working together experience a feeling of synergy and productiveness. When a team is truly learning, the group as a whole becomes much more competent than just the sum of its individual competencies. It enhances in all dimensions when members are honest and, respect each others views and vision. Team learning is maximum and is productive when team members towards of common goal and share a common vision. Figure 7.6 models the team behaviour and outcome under shared and unshared vision. Goal

Team members not aligned towards goal. Result waste of resources and time

Goal

Team members aligned towards goal. Result full utilisation of individual potential and no waste of resource and time.

Disorganised Unaligned Team

Organised Aligned Team

Fig. 7.6

Team Members with Aligned and not Aligned Vision and Corresponding Outcomes

The team members perform through dialogue and discussion on the subject of resolution. In a dialogue, there is free exchange of thoughts and ideas and members listen carefully to what other members are saying. In a discussion different views and solutions are expressed and commented upon. In all such discussions, consensus may not emerge. The team members learn a lot whether it is a dialogue or discussion due to collective discipline of working for common goal. A unique relationship of trust and respect is developed due to dialogue and discussion. Team learning is the process of aligning and developing the collective capacity of the team to work together for achieving the goal. It is built on the basis of shared vision and exploits individual mastery for common

good of the team. Team learning has two main characteristics where team members think insightfully about the problem and think how to tap individual members’ potential to common goal achievement. Then the members learn to take innovative coordinated action due to mutual trust that each member is working for a common goal. Team members believe that it is a collective discipline.

Systems Thinking Systems thinking requires people to view the aspects of organisational performance rather than individual performance. It creates a framework for focusing on patterns and interrelationships between different parts of the organisation’s sub-systems. It widens people’s perspective and enforces adoption of holistic approach to problem solving. It further uses the ability of individuals and teams to see connections between issues, events and information as a whole framework rather than as a series of unconnected parts. A system is a perceived whole, whose sub-systems are held together by common vision because they continually affect each other over time and operate toward a common purpose. Systems thinking is the art of seeing the world in terms of wholes, and the practice of focusing on the relationships among the parts of a system. By looking at reality through systems thinking ones can work with a system to create lasting solutions to complex problems of business management. Systems thinking enables integration of other four disciplines, namely, personal mastery, vision, team potential and mental models of team members. Peter Senge has developed laws around systems thinking, which together are known as the Fifth Discipline. They are: • Today’s problems come from yesterday’s solutions. • Often we solve a problem by creating a new problem or shifting the problem elsewhere. • The harder you push, the harder the system pushes back. • When our initial efforts fail, we push harder but what we do not realise that we are contributing to the obstacles ourselves. • Behaviour grows better before it gets worse. • A solution comprising small interventions does give result but then slowly the solution itself becomes the new problem of worse nature. • The easy way out usually leads back in. • We all find comfort in applying familiar tested solutions to the problem. But the problem resurfaces again. • The cure can be worse than the disease. • Sometimes, solution can be addictive and dangerous. • Faster is slower. • Faster implementation of a solution may be exciting but when the system is not geared to run faster, it eventually slows down, or may die permanently. • Cause and effect are not closely related in time and space. • Cause and effect are not universal in time and space. They may become be inconsistent when time and space change or advance. • Small changes can produce big results, but the areas of highest leverage are often the least obvious. If we see a problem as a snap shot in time and space, small changes or simple solutions may work. But, in case of a complex problem, solution may be in something less obvious.

• You can have your cake and eat it too, but not at once. • Dividing the elephant in half does not produce two small elephants. Living systems have integrity. They function effectively because of their integrated character, making them single whole of some substance. When we solve the problem by splitting it, the solution fails. Remember, in a system, 2 is not equal to 1+1. • There is no blame. In failure, we blame circumstances, technology, competition, and so on, which are outside the system. In systems thinking, there is nobody outside to blame except the system itself.

Mental Models Mental models are the deep beliefs and assumptions we hold about how the world works. They develop the way you think. These models shape the decisions we make in life, the actions we take in response to events, and the ways in which we interpret others’ behaviour. Practicing this discipline involves surfacing and testing your deepest assumptions and beliefs, and helping others do the same. Your mental models stand between you and reality, distorting all perceptions. They create both limits and opportunities due to thinking influenced by already formed mental models. If you can think impossible thoughts, you can do impossible things. (Yoram (Jerry) Wind, Colin Crook and Robert Gunther) The problems with mental models lie not in whether they are right or wrong but whether they are too simple and are below the surface of awareness. Due to this, they remain unchallenged, unexamined and continue to influence one’s thinking. Learning organisations create a challenge where mental models are challenged before use. In the history books of the Auto industry, it is written that US automakers’ perception of American consumer was that buying decision was influenced by styling of the body and not the quality of the car on the road. However, automakers from Japan educated American consumers on quality and changed the priority of styling to second. The other mental models which prevailed upon were: • Business is for making money and not cars. • Cars are status symbol. • American car market is distinguishingly different from the rest of the world. These mental models remained unchallenged, and the American car industry suffered while the Japanese auto industry prospered. People in the organisation continuously interact with a number of problem situations, and they are being solved using existing mental models. In the process, models do undergo changes because of solving various problems using the old mental model of solving the problem. This is a learning process whereby the mental process modifies the model. This experience of solving a problem with new model is a learning experience. The learning organisations ensure that people continuously revalidate their models before their application. Mental models change for the better when people resort to generative learning where they question the basic premise of the model and its application. Organisation learning is faster when individuals adopt generative learning model. Learning organisations take special efforts in internalising mental models into decision making systems. Mental models are the pillars of learning organisation because developing models and improving them continuously by challenging, questioning and thinking new add to the organisation learning. Learning organisations have the calibre to handle models.

Personal Mastery Without personal mastery, individuals and organisations are unable to continue to learn how to create. The essence of personal mastery is focusing on ultimate desires—approaching life from a creative, rather than a reactive viewpoint. Personal mastery, a special level of proficiency, is the result achieved through commitment to lifelong learning in a focused area of knowledge, or skill, or competency. It goes beyond competence and skills though it is grounded in it. When personal mastery becomes an individual’s goal, it becomes a discipline, a part of a never failing routine. In such a case, personal mastery involves two things. First is that continuous attempt is made to decide what is important today and what is not. The important is reinforced and the unimportant is sent to the recycle bin. The second thing is learning to see the current scenario more clearly to deal with it more effectively. This learning teaches where one is now and where one desires to go. Learning to attain personal mastery or proficiency actually means learning more, but simultaneously expanding the ability to produce results. It is lifelong learning; generative learning. For organisational learning, individuals with mastery in something and proficiency in delivering the results are required at all levels. Individuals with personal mastery, a capability, • Have a special sense of purpose emanating from their vision and goals • Continually live in ‘learning mode’ • Are aware of present level of ignorance and incompetence • Are strongly committed to acquire or achieve something There is a clear connection between individual’s personal mastery and his contribution to team learning, and eventually organisation learning. Personal mastery is the art of identifying the unique purpose in personal and professional life, and how to go about fulfilling it. Practicing this discipline involves some honest indepth exploration of life, experiences and desires, and a willingness to take some risks in applying them to overcome a complex situation. Organisations learn only through individuals who learn continuously. Individual learning does not necessarily assure organisation learning; special effort is needed to build a structure of individuals, teams or the organisation as a whole. Learning organisations promote and encourage individuals to be in the practice of building personal mastery. Organisational climate is that of questioning the status quo, and continuity of past into future. It is emphasized that personal mastery in something that is valued by the organisation. The learning organisation creates a climate where building personal mastery is enjoyed by individuals. To illustrate this point, we take the example of academics where faculty and research associates are recognised awarded, promoted, and are encouraged to develop personal mastery. Universities and institutions create the climate for building personal mastery by sending, sponsoring academicians to conferences, workshops and seminars. They are encouraged to publish their new findings in international journals. Individuals with personal mastery are rewarded financially and recognised by promotions in the organisation. These five pillars of strength are supported by • Corporate culture (which mainly refers to policies, beliefs, activities and rituals) • Corporate social responsibility (ensuring fitment of the organisation in larger social framework) • Corporate dialogue (adopting new communication form and formats for effective learning) • Corporate leadership (which unleashes the full potential of the people) • Corporate: Work – life balance ( balancing professional life with Personal and family life)

Corporate culture is ‘something’ that influences the work environment in which we work every day. It refers to the policies, beliefs, activities, protocols, practices and rituals that determine an organisation’s character and personality, which influences it employees. A culture can support or obstruct learning, encourage or curb creativity and innovation. A supportive culture could be a driver or an enabler. We can shape our organisation’s character to its advantage purposely through careful attention to policies, beliefs, activities, protocols, practices and rituals. Corporate social responsibility addresses the question of how well the business organisation fits into the larger social setting. Corporate responsibility sees beyond own industry domain. Corporate social responsibility enforces organisation to look into actions so that the interests of neighbourhoods, other undertakings, hospitals, educational institutions, and families are not affected in adverse manner. The corporate social responsibility focuses on how the organisation can specifically make society a better place for everyone. Corporate dialogue focuses on new communication forms, rejecting traditional forms of communication that strengthen and enhance the organisation’s collective intelligence. The new communication forms and channels are technology enabled, and are highly effective in taking the message across the board. The technology enabled dialogue stimulates questions and reveals insights that we often miss in traditional methods of communication. Corporate leadership in the field of organisational learning takes on a particular focus. The focus is on unleashing the full potential of each and every employee in the organisation. Often this involves moving away from more traditional command-and-control management structures and toward more fluid, self-organising leadership. It demands empowering individuals, and groups with knowledge and encouraging experience based learning. The corporate leadership encourages collaborative working, giving a chance to individuals to contribute to common cause, making use of unleashed potential. Striking work/life balance is another area receiving increasing attention in the organisation. More and more people are seeking to design their work so that they have room and energy for the other important dimensions of their lives—family, community, self development, and so on. At the same time, boundaries between work and home life have blurred in recent decades. Due to internet one can be anywhere but be connected to the corporate office data and people. The discipline of work/life balance seeks to explore the ramifications of these changes and address the question of how to set priorities and find meaning in office, family and social life. The discipline of maintaining work/life balance creates a comfort zone at the work place reducing stress and strain an the individuals. Because everything said above is structurally connected through systems thinking of an organisation committed to true learning practices, all the above disciplines are in some form, tackled together and not in isolation. After all, they each reinforce one another, and when they come into alignment, the organisation truly builds itself as a strong learning organisation. The dynamics of learning organisation are shown in Figure 7.7. Organisation learning is a continuous process leading to organisation development. Organisation learning has four process steps as under. • Captures signals of compelling change • Drives to study of the changed environment • Enforces the review of strategy mix and its outcome • Specifies the required change in capacity and competencies of the organisation

Drives to Captures Signals of Compelling Change

Enforces Study of the Changed Environment

Specifies

Review of Strategy mix and its Impact, Outcome

Change in Capacity and Competencies of the Organisation

Organisation Learning

Supported by Five Disciplines: Shared Team Systems Mental Personal Vision Learning Thinking Models Mastery

Fig. 7.7

Organisation Learning Dynamics

Organisation learning, in this dynamic process of bringing change in competencies and capabilities, focuses on: • Systems and processes, to be efficient and effective • Work culture and attitudes encouraging continuous improvement • Knowledge management to aid learning process • Creativity and innovation of employees • Continuous improvement of key result areas

THE CONCEPT OF LEARNING ORGANISATION The concept of learning organisation is increasingly relevant, given the increasing complexity and uncertainty of the organisational environment in today’s globalised world of business. As Senge (1990) remarks: ‘The rate at which organisations learn may become the only sustainable source of competitive advantage.’ The key ingredient of the learning organisation is how it processes its managerial experiences. The managers in learning organisations learn from their experiences rather than being governed by their past experiences. In Generative Learning Organisations, the ability of the manager is not measured by what he knows, but rather by how he learns. What is the process of learning? In learning organisations, the management encourages, recognises, and rewards for openness, systemic thinking, creativity, sense of efficacy, and empathy towards the organisation. To understand the desire to become a learning organisation, you must understand a little about organisational change. Everyone agrees that change is inevitable. It is also understood that every change, small or big, is disruptive. The reason for the change is, the global business environment continues to place growing demands on organisations to be more efficient and competitive. Everybody enjoys some level of stability without the disruption of change being forced on them. At the same time, some change is preferred to the boredom that

comes from excessive routine. The key factor here is personal control over the change process. The second factor is the magnitude of organisational change that is involved in most planned change projects. The issue is how can change be accomplished with less disruption and more personal control? The answer can be found in the approach taken to change and change management and the assumptions held about it. The real problem in the organisation arises not from change, but from not recognising and suppressing the change from occurring. Not changing does not eliminate the need to change; it only delays it. The risk of not changing at the appropriate time continues to mount. And when the inevitable change occurs, it is often very large and more disruptive. The change effort is then more difficult. The alternative to a large, planned change effort is to see change as an emergent continuous process. In this manner, many incremental changes are encouraged, creating an organisation that has more flexibility and speed to meet competitive threats. This requires an organisation that understands the change process and actively builds individual and organisational core competencies that are needed to create sustainable competitive advantages. The only significant competitive advantage in all areas is the ability to continue to innovate, staying one step ahead of others. This cannot be duplicated by competition. And this involves and all employees working together with outside partners. Our knowledge and drive to use our full capabilities to be the best cannot be duplicated easily elsewhere. This is the only true competitive advantage. Therefore, organisations must continue to move towards excellence so that everyone looks up to them as the standards of competitive excellence. The basic assumption about successful organisational change is that the management takes leadership role to bring in effective change. One reason is that large, transformational change touches so many parts of the organisation that the top management must get involved for the change process to be effective. So, what is a learning organisation? It is an organisation that tests its assumptions, policies, strategies and continually strives for improvement. Organisational learning is also challenging many of the assumptions about organisational change that we sometimes hold without questioning. It attempts to provide organisations with mechanisms to deal with the issues and assumptions implicitly held without questioning. The issues could be: • Changing strategy for better • How to bring in continuous improvement • How to face the risk not identified earlier • How to arrest declining influence of competitive advantage • Issues like organisation restructuring, business restructuring • Developing new core competency and such other issues A well thought out learning organisation design can only help in dealing with the crises. The learning organisation builds capabilities to deal with the crises of management of business.

What is the Manager’s/Leader’s Role in the Learning Organisation? Peter Senge argues that the leader’s role in the learning organisation is that of a designer, teacher and steward, who can build shared vision and challenge prevailing mental models. The leader is responsible for building organisations where people are continually expanding their capabilities to shape their future. In learning organisations, leaders are responsible for learning.

What is the Role of Information Systems in the Learning Organisation? Huber explicitly specifies the role of IS in the learning organisation as primarily serving the task of building organisational memory. IS can serve three processes, Knowledge Acquisition, Knowledge Distribution and Knowledge Interpretation. One instance of use of IS in knowledge acquisition is that of Market Research and

Competitive Intelligence Systems. At the planning level, scenario planning tools can be used for generating possible futures. Similarly, use of Groupware tools, Intranets, E-mail, and Bulletin Boards can facilitate the processes of information distribution and information interpretation. The archives of these communications can provide the elements of the organisational memory. Organisational memory needs to be continuously updated and refreshed.

ORGANISATION LEARNING Argyris defines organisational learning as the process of ‘detection and correction of errors.’ In his view, organisations learn through individuals acting as agents for them: ‘The individuals’ learning activities, in turn, are facilitated or inhibited by an ecological system of factors that may be called an organisational learning system.’ Huber considers four constructs as integrally linked to organisational learning: knowledge acquisition, information distribution, information interpretation, and organisational memory. He clarifies that learning need not be conscious or intentional. Further, learning does not always increase the learner’s effectiveness, or even potential effectiveness. Moreover, learning need not result in observable changes in behaviour. Three theorists have given the meaning of organisation learning. They are: • ‘The essence of organisation learning is the organisation’s ability to use the amazing mental capacity of all its members to create the kind of processes that will improve its own’. –Nancy Dixon, 1994 • ‘Organisations where people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free, and where people are continually learning to learn together’. –Senge P, The Fifth Discipline • ‘A model of strategic change in which everyone is engaged in identifying and solving problems so that the organisation is continuously changing, experimenting and improving, thus increasing its capacity to grow and achieve its purpose’. Rowden R.W. 2001, The Learning Organisation and Strategic Change, S.A.M. Advanced Management Journal, Summer 2001. It is team learning, not individual learning, that adds to organisational learning. The path to organisation learning moves through individual learning to team learning to organisation learning. The field of organisational learning explores ways to design organisations so that they fulfill their function effectively, encourage people to reach their full potential, and, at the same time, help the world to be a better place. Organisational learning is an area of knowledge within organisational theory that studies models and theories about the way an organisation learns and adapts. In Organisational Development (OD), learning is a characteristic of an adaptive organisation, i.e., an organisation that is able to sense changes in signals from its environment (both internal and external) and adapt accordingly. OD specialists endeavour to assist their clients to learn from experience and incorporate learning as feedback into the planning process. Argyris and Schon distinguished between single loop and double loop learning, related to Gregory Bateson’s Concepts of First and Second Order Learning. In single loop learning, individuals, groups, or organisations modify their actions according to the difference between expected and obtained outcomes. (Figure 7.8) In double loop learning, the entities (individuals, groups or organisation) question the values, assumptions and policies that led to the actions in the first place; if they are able to view and modify those, then second order or double loop learning has taken place. Double loop learning follows the learning about single loop learning. (Figure 7.9)

Organisation Knowledge: Values, Norms, Assumptions, Policies, Knowledge Body

Fig. 7.8

Action

Events and Conditions

Adjust: Modify Actions

Match

Expectations

Mismatch

Single Loop Learning (Adaptive Learning)

Organisation Knowledge: Values, Norms, Policies, Assumptions, Knowledge Body.

Action

Events and Conditions: Outcome

Mismatch

Expected Outcome

Questions Organisation Knowledge and Improves Knowledge and then Modifies Action

Fig. 7.9

Double Loop Learning (Generative Learning)

Peter Senge argues that increasing adaptiveness is only the first stage of learning; organisations need to focus on generative learning or double loop learning Generative learning emphasises continuous experimentation and feedback in an ongoing examination of the very way organisations define and solve the problems. In Peter Senge’s view, generative learning is about creating. It requires systemic thinking, shared vision, personal mastery, team learning, and creative tension. Generative learning, unlike adaptive learning, requires new ways of looking at the world. In contrast, adaptive learning or single loop learning, focuses on solving problems in the present without examining the appropriateness of current learning Behaviours, or questioning the current knowledge, assumptions, policies, etc. Adaptive learning gives incremental improvements, often based upon the past track record of success. Nonaka and Takeuchi developed a four stage spiral model of organisational learning. They started by differentiating Polanyi’s concept of tacit knowledge from explicit knowledge, and described a process of alternating between the two. Tacit knowledge is personal, context specific, subjective knowledge, whereas explicit knowledge is codified, systematic, formal, and easy to communicate. The tacit knowledge of key personnel within the organisation can be made explicit, codified in manuals, and incorporated into new products and processes. They called this process externalisation. The reverse process (from explicit to implicit) was called internalisation because it involves employees internalising an organisation’s formal rules, procedures, and other forms of explicit knowledge. They also use the term socialisation to denote the sharing of tacit knowledge, and the term combination to denote the dissemination of codified knowledge. According to this model, knowledge creation and organisational learning take a path of socialisation, externalisation, combination, internalisation, socialisation, externalisation, combination . . . etc., in an infinite spiral.

Ang and Joseph contrast organisational learning and learning organisation in terms of process versus structure. McGill et al do not distinguish between learning organisation and organisational learning. They define organisational learning as the ability of an organisation to gain insight and understanding from experience through experimentation, observation, analysis, and a willingness to examine both successes and failures. Organisation learning depends on many factors, as explained below: • Organisation Culture Which enables, promotes, motivates learning and ensures provision of learning resources and clearly defines learning expectations and outcome. • Network The scope and reach of network of CoPs, organisation knowledge, customers and people in the organisation. The network is nurtured and maintained to enhance learning capacity. The established network accelerates the learning process. • Approach to Learning The approach could be formal through plan and action, PDCA cycle. The approach could be informal providing guidance on web search, CoPs, referring to a knowledge content already developed. • Technology Technology is a driver to learn, hence the pace of learning depends on choice of technology which enables collaboration, networking, transfer and sharing easily. If the simple technology configuration is inexpensive, the returns are very high. • Thinking Skills The level of thinking skills make all the difference in pace and quality of learning. The thinking skills include ability to view, decipher, analyse, see the hidden connections or associations, evaluate and in decision making.

ORGANISATION KNOWLEDGE We talked about learning organisation and organisation learning. Both are different. Organisation learning creates learning organisation. In this section, we discuss the term ‘organisation knowledge’. Some of this knowledge can be termed technical, so called professional knowledge, such as knowing the meaning of technical words and phrases, formulae, being able to read and make sense of technical data and being able to act on the knowledge. Knowledge is scientific knowledge, which is universal, but must have it as ones part of the competency. A large part of the knowledge used by managers, however, does not assume this form. Besides knowing technical and scientific knowledge, it is important for the manager to know how, when and where it can be applied. In contrast to scientific knowledge that guides the engineer, the physician or the chemist, managers are often informed by a different type of know how. This comes from experience and resides in stories, narratives, case studies of how real people in the real world dealt with real life problems, successfully or unsuccessfully. Experiential knowledge is what we use in everyday life, professional and personal, to deal with awkward situations or tough problems. Experiential knowledge could be out of one’s experience or gained from others’ similar experience. We seek the stories of people in the same category. As the Chinese proverb says ‘A wise man learns from experience; a wiser man learns from the experience of others. One gets experiential knowledge while performing some work, activity. The learning is out of experience and feedback received out of application of knowledge. When knowledge is applied, well meaning, motivated employees reflect into themselves, think and look for new ideas. Experiential learning is a continuous process which captures new knowledge, uses it and improves upon using new ideas. (Figure 7.10) The prerequisite for organisational learning is ‘individual learning.’ Learning by individuals in requirement of organisation’s business needs is the traditional domain of human resources department. HRD activities

1. Focus on Learning While Working

2. Experience New Learning

Experiential Learning: A Continuous Process

On Satisfaction, Integrate New Knowledge Formally Into Organisation Knowledge.

Fig. 7.10

6. Apply and Practice New Knowledge, New Learning

3. Reflect on New Learning and Experience

4. Think on New Experience

5. Gain More Knowledge and Modify Behaviour, Actions, Decisions

Experiential Learning Process

include such activities as, training, increasing skills, work experience, and formal education through sponsorship to various training programmes. Given that the success of any organisation is founded on the knowledge of its people, HRD will continue. Some organisations take it forward with continuous learning. Change has become the norm rather than the exception. Continuous learning throughout one’s career has become essential to remain relevant and competitive in the workplace. Consistent to this requirement, organisational learning also becomes relevant and necessary. The traditional learning process of offering need based training programmes has limitations of retaining knowledge. As the time goes by, retained knowledge is lost. But, if training is through assessment of needs, supported by coaching, mentoring, involving in CoPs and making training a part of career development it helps considerably in retaining knowledge. Individual learning moves through the four stage cycle: • Concrete Experience An individual learns out of hard core of experience by trial and error, making mistakes and correcting them. This learning is out of live wire experience. The individual is an activist. • Reflective Observation The same individual works with practical experience but then he gets into reflection mode. The individual questions, thinks and, while applying practical knowledge, tries to improve upon the learning made out of concrete experience. The person is a reflective observer. Such person is then a reflector. • Abstract Conceptualisation The individual, after becoming first activist and then reflector, goes into conceptualisation phase. The individual tries to build theories around what has been learned and recorded as knowledge. The individual becomes a theorist. • Active Experimentation Having advanced into the theorist’s role, the individual ventures into active experimentation of trying out new learning to confirm its validity with the intention of improving it by further active experimentation. The individual is then a pragmatist. Individual learning moves through this cycle. Summing individual employee learning is not equivalent to model organisational learning. The learning organisation is a result of comprehensive impact of individual learning and collective group learning through interaction to achieve specific knowledge goal achievement.

The following definition outlines the essential difference between the two: A learning organisation actively creates, captures, transfers, and mobilises knowledge to enable it to adapt to a changing environment. Thus, the key aspect of organisational learning is the interaction that takes place among individuals. Organisational learning is a group activity of interaction for specific knowledge goal attainment. A learning organisation does not rely on passive or ad hoc process, stated earlier, in the hope that organisational learning will take place as a by-product of normal work. A learning organisation actively promotes, facilitates, and rewards collective learning. Creating (or acquiring) knowledge as specified in KMS can be an individual or group activity. Capturing individual learning (knowledge) is the first step to making it useful to an organisation. There are many methods for capturing knowledge and experience, such as publications, activity reports, lessons learned, interviews, and presentations. Capturing includes organizing knowledge in ways that people can find it; multiple structures facilitate searches regardless of the user’s perspective (for example., who, what, when, where, why, and how). Capturing also includes storage in repositories, databases, or libraries to ensure that the knowledge will be available as and when needed. An organisation must learn so that it can adapt to the changing environment. Historically, the lifecycles of organisations typically spanned stable environments between major socio-economic changes. Blacksmiths who didn’t become mechanics simply fell by the wayside. More recently, many Fortune 500 companies or top hundred Indian companies of two decades ago no longer exist. Given the accelerating rate of change, more critical learning of organisation relevance and its adaptation is necessary for success and ultimate survival. Organisational learning is a process, involving interactions among many individuals leading to well informed decision making. Thus, a culture that learns and adapts as part of everyday working practice is essential. Re-use of knowledge and inventing something new is considered as desirable behaviour. Clearly, shifting from individual to organisational learning involves a non-linear transformation. Once someone learns something, it is available for their immediate use. In contrast, organisations need to create, capture, transfer and mobilise knowledge before it can be used.

HUMAN RESOURCE MANAGEMENT FOR KM In order to gain competitive advantage from KM, organisations need to identify core competencies, and HRM can play an important role in creating and developing the organisational capabilities required to compete in the knowledge economy. Saint-Onge also refer to the need for the HRM function to transform itself in order to respond to changing requirements of the knowledge era. He suggests that a strategic capabilities approach where resources are structured across individual capabilities, organisational capabilities and knowledge architecture. The role of the HRM professional will then focus on integrating individual, team and organisational learning for the benefit of both customers and shareholders. HRM can play an important role in creating and developing the organisational KM strategies geared to creating wealth from intellect. In the knowledge economy, knowledge based capabilities are the key to competitive advantage. At the firm level, this places the people, their knowledge and innovative capacity, at the heart of strategic potential, and organisations that excel in attracting, creating, and managing and sustaining knowledge capabilities are advantaged. Human resource management (HRM) has, in recent years, been exhorted to demonstrate its position as a strategic partner to executive management: this promise has been only partially realised. We explore the knowledge economy and the management of knowledge from an HRM perspective.

Commanding a central position in realising value from knowledge assets is proposed as a strategic role for HRM. Specifically, HRM must respond to the key challenges presented by the knowledge economy. We identify four HRM priorities: becoming expert in identifying and defining strategic knowledge capabilities; developing and managing knowledge workers by leveraging the knowing-learning-doing nexus; building knowledge value as an organisational as well as an individual asset; and minimising enterprise knowledge risk. There are several roles that can be played by HR in developing knowledge management system. First, HRM should help the organisation articulate the purpose of the knowledge management system. Investing in a knowledge management initiative without a clear sense of purpose is like investing in an expensive vehicle which one does not need. Effectively framing the knowledge management issue, before deciding on a course of action, is a crucial prerequisite for success. Second, as a knowledge facilitator, HRM must ensure alignment among the organisation’s mission, statement of ethics and policies. These should all be directed toward creating an environment of sharing and using knowledge with full understanding of the competitive consequences. Furthermore, HRM must nourish a culture of organisation learning. Third, HRM should also create the ‘ultimate employee experience’. That is, by transforming tacit knowledge into explicit knowledge through education, the organisation must build employee skills, competencies, and careers, creating ‘bench strength’. This combines the traditional training and development responsibilities of HRM with the new responsibilities of human capital steward: using all of the organisation’s resources to create strategic capability. Fourth, HRM must enable integration of effective knowledge sharing and usage into daily life. That is, knowledge sharing must be expected, recognised, and rewarded. Often, the common pattern is to hoard knowledge because it makes the individual more valuable and more difficult to replace. Effective knowledge management requires this trend to be changed and requires those individuals to become teachers and mentors. Teaching must become part of everyone’s job. Clearly, for such a cultural shift to take place, HRM must overhaul selection, appraisal, and compensation practices. Human resource management has the capabilities for creating, measuring, and reinforcing a knowledge-sharing expectation. Fifth, HRM must relax controls and encourage behaviours that facilitate formal and informal interaction among employees. In the knowledge economy, conversations through various opportunities of interaction inside and outside the company are the mechanisms for making change and renewal of company’s introvert culture. Sixth, as employees increasingly rely on technology to communicate, they lose opportunities to develop the rich, multifaceted relationships that encourage the communication of tacit knowledge. Human resource management can contribute to developing social capital by sensitising employees to the negative consequences of excessive reliance on electronic media and by creating opportunities for face-to-face contact.* The authors identify five new roles that human resource practitioners should adopt. They are given in Figure 7.11.

Human Capital Steward HR has long understood ‘human capital’ to be the collective knowledge, skills and abilities of the organisation’s workers. But the role of steward of these resources is a new one. Unlike raw materials or equipment, human capital cannot be simply bought and used. The authors write, “Human capital must be contributed by the * Source Mark Lengnick-Hall and Cynthia A Lengnick-Hall, Human Resource Management in the Knowledge Economy: New Challenges, New Roles, New Capabilities, Berrett-Koehler Publishers.

Change Agent and Strategic Partner Human Capital Steward

Knowledge Facilitator

HR Manager Roles Relationship Builder

Fig. 7.11

Knowledge Deployment Specialist

HR Manager’s Roles in Knowledge Driven Organisation

employee voluntarily”, and the role of HR is “to create an atmosphere in which employees can contribute their skills, ideas and energy”. This is achieved by “facilitating employees without controlling them”.

Knowledge Facilitator In this role, HRM helps the organisation acquire and disseminate knowledge and use it to create competitive advantage. Lengnick-Halls write that transforming tacit knowledge into explicit knowledge can help build employee skills, competencies and careers. HRM facilitates this transformation. Actually the knowledge facilitator role of the is much broader and requires creative integration across traditional HRM activities. The role forces both rethinking old ways of managing the workplace as well as using innovative approaches outside the box of traditional HRM. Most important, becoming an effective knowledge facilitator requires conceptualising HRM as a vehicle for creating capabilities and capitalising on the human factor to create a community of knowledge workers within the organisation. This transformation comes about when knowledge sharing is valued and teaching must become part of everyone’s job.

Relationship Builder The author atate that HR must facilitate cross-functional teamwork. “HRM must build networks and shared people communities around the strategic objectives of the business to ensure competitiveness”, the authors write.

Rapid Deployment Specialist The global economy moves quickly, requiring HR to anticipate and implement any staffing adjustments that evolving markets and business strategies require. This will necessitates a versatile, flexible HR architecture.

Change Agent and Strategic Partner From its traditional role as service function, HRM now needs to be a change agent to bring in change in culture, practices and management. HRM is a participant in the change process. The change in business environment calls for knowledge driven strategies where critical mass of HR is activated to implement them for business benefit. HRM function, therefore, is a strategic partner in this endeavour.

PARADIGM SHIFT IN HRM FUNCTIONS In Human Resource Management in the Knowledge Economy, Lengnick Halls acknowledge that adopting a new approach to HR is a formidable challenge. It requires a new focus on building strategic capability,” they write, “and on managing new roles that expand the methods and processes of human resource management.” In an era competition, competitive advantage is perceived to be linked to knowledge, which alone can enable the organisation to be creative and innovative to build an array of competitive advantages. Since KM is essentially a Human Resource driven activity, it is but natural that the relationship between KM and HRM has increased over recent years. Both KM and HRM have grown more sophisticated and complex, asking for more intelligent management of knowledge and HR. In terms of the HRM function, the rise of the knowledge economy has had a major impact, with a considerable shift from HRM as a bureaucratic ‘personnel management and industrial relations’ operation to the development of discrete HRM functions aiding knowledge management. This has been accompanied by the integration of these functions to support competitive advantage and a more strategic thrust to maintain it. The rise of the knowledge economy has seen a proliferation of information and communication technologies, resulting in the growth of virtual and global organisations with rapid change in organisation structure, culture, and so on. This, in turn, requires drastic changes within HRM to respond to changing demands of the knowledge economy. Traditional HRM functioned under narrow operational boundaries within the organisation that were limited to recruitment, training, personnel management, work place safety, human relations compensation, and so on. In the knowledge economy, the role of HRM needs to expand, looking both within and outside the organisation. The traditional focus on managing people has been broadened to managing organisational capabilities, managing relationships and managing learning and knowledge. The emphasis on discrete HRM practices is also broadening to a focus on developing themes and creating environments conducive to learning, as well as to the acquisition, sharing and dissemination of knowledge within organisations. In order to gain competitive advantage from KM, organisations need to identify core competencies, integrated knowledge sets, termed as knowledge products, intellectual capital and property, that distinguish them from competitors and add value to customers requirements. This body of competencies and knowledge sets are termed as organisational capabilities. HRM can play an important role in creating and developing the organisational capabilities required to compete effectively in the knowledge economy. A revitalisation of the HRM function on these lines to respond to the demands of the knowledge economy and to develop linkages with KM requires major changes across four key areas: Roles, Responsibilities, Strategic Focus and Learning Focus impacting organisational learning. Saint-Onge also suggest the need for the HRM function to transform itself in order to respond to changing requirements of the knowledge era. He suggests a strategic capabilities approach, where resources are structured across individual capabilities, team capabilities, organisational capabilities, and KMS architecture. The role of the HRM professional will, then, focus on integrating individual learning, team learning and organisational learning for the benefit of both customers and shareholders, and keep the competition at bay. The HRM function is now loaded with additional responsibilities of actively participating in the executive function of the business enterprise, deviating from the support role to responsive, collaborative and participative role in management of business. In the knowledge economy, HRM has following three tasks focusing on:

Relationship Building HRM should take up the task of developing and sustaining organisational capabilities through activities that overlap with traditional business functions, such as strategy formulation and implementation, finance and marketing, as well as new functions, such as KM. This involves moving away from the service function to the participative involved role of a driver and not just a catalyst. This requires developing new relationships among managers, employees, and customers. This relationship strengthens the effort of HR in developing a learning organisation. The relationship of involved nature takes away the barriers of sharing and transferring knowledge across the organisation. HRM also requires participating in value adding processes of the organisation which facilitate building value adding partnerships with vendors, motivating employees to create value in whatever they are entrusted to do and making customers more involved in organisation’s activities so that their expectations are articulated more explicitly.

Strategic In the knowledge economy, HRM should be involved in the development of human capital the management of knowledge towards the goal of building a learning organisation. This requires HRM professionals to identify the ways and means to canalise intellectual capital toward the development of core competencies, strengths and capabilities, knowledge products, and so on. An emphasis should be on developing HR strategies along with traditional short-term strategies which impact KM lifecycle. The new HR strategy should build strategic competence of HR where by they are able to think strategy, design strategy and implement it effectively. This effort of HRM professionals will accelerate the development of knowledge and related activities, enabling the organisation to create knowledge based competitive advantage which distinguishes it from competition. The role of the HRM professionals will then focus on integrating individual, team and organisational learning for the benefit of the organisation, customers and stakeholders.

Learning In the knowledge economy, the need for learning continuously is paramount. HRM practices broadening to focus on developing and creating environments conducive to learning, as well as to the acquisition, sharing and dissemination of knowledge within the organisation. HRM should recognise that knowledge, knowledge sets and knowledge products are active assets which create required competencies to effectively use other physical assets to their fullest strength. HRM initiates, and participates in implementation of KM strategy. Its focuses on the activities which help in generative learning, as against adaptive learning. It can assists in learning efforts of employees to build quality, creativity, leadership and problem solving skills by facilitating continuous learning and identifying sources of knowledge. In summary, based on the discussion so far, learning organisations would be specifically characterised by processes and mechanisms which: • Expose the organisations to new information and revelations, whether created internally or acquired from the external environment. • Create receptivity in the organisation, so that it can consciously interpret and codify this information into business relevant knowledge. • Enable the organisation to disseminate this knowledge across the organisation, so that it becomes collective learning. • Institutionalise the above knowledge based activities, so that they can be carried out on a conscious and continuing basis.* * Source Competing Through Knowledge, Building a Learning Organisation, by Madhukar Shukla, Response Books, A Division of Sage Publications, New Delhi.

End Notes • The success of KM largely depends on social and cultural factors prevailing in the organisation. These factors play an important role in shaping knowledge initiative, building strategies, spreading knowledge culture and making an organisation a knowledge driven learning organisation. KM efforts are primarily taken on people of the organisation, recognised as Human Resource, converting them into human capital. • Building human capital is now the primary focus in human resource management and HRM research. A recent trend is moving to increased consideration of intellectual capital rather than focusing solely on human capital. Intellectual capital can be broadly conceptualized as the sum of all knowledge an organisation is able to leverage in the process of conducting business to gain competitive advantage. More specifically, intellectual capital may comprise at least three forms of capital – human, social, and organisational. • There are several definitions of learning organisation developed by scholars and theorists. • Organisation learning means the process of improving actions through better knowledge and understanding. –C. MarleneFiol and Marjorie A Lyles • Organisations are seen as learning by encoding inferences from history into routines that guide Behaviour. –Barbara Levitt and James G March • Organisational learning is a process of detecting an error and correcting it. –Chris Argyris • A learning organisation is an organisation skilled at identifying, creating, acquiring, transferring, sharing and measuring the knowledge, taking it forward to a level of intellectual capital. It continues to modify its behaviour to reflect new knowledge and insights. • The organisations that are learning translate new knowledge into new ways of behaving. They also believe that learning process needs to be managed through design and not by chance or accident. They believe that policies, practices, systems, specially intended and designed to learn and reflect, are the building blocks that build a learning organisation. • Peter Senge suggested five component technologies, namely systems thinking, mental modeling, shared vision, team learning and personal mastery. • A shared vision makes every piece of work a part of bigger endeavour, such as new product launch, changeover to new technology, launching a product in new market, and such other path breaking activities. Visions are exhilarating as they strike a spark and excitement in the people of the organisation. Shared vision is the most successful tool to build relationships and trust among the team or people in the organisation. It creates common identity and purpose for work. • Abraham Maslow’s study of High Performing Teams revealed that one most common thing among performing teams was shared vision and common purpose among the team members. • Your mental models stand between you and reality, distorting all your perceptions. They create both limits and opportunities due to thinking influenced by already formed mental models. If you can think impossible thoughts, you can do impossible things. • The mental models are the pillars of learning organisation because developing models and improving them continuously by challenging, questioning and thinking new add to organisation learning. • Personal mastery is the art of identifying what’s your unique purpose in personal and professional life, and how you want to go about fulfilling that purpose. Practicing this discipline involves some honest indepth exploration of life experiences and desires and a willingness to take some risks in applying them to overcome a complex situation.

• Learning organisations are continuously in experimenting and prototyping mode of knowledge as they are constantly required to innovate. The experiments are carried out to test new knowledge in R&D, shop floor, engineering, products and processes, and in customer segments. • Some experiments and prototypes may be successful and some may not be. In either case, the experience of experimenting and prototyping provides new insight in the area of experimentation. The learning organisation thereby becomes richer in knowledge. • Not all knowledge in the learning organisation is found inside. Often, more valuable knowledge is found outside the organisation. The learning organisations make special efforts and step out to capture that knowledge from various sources outside the organisation. • Learning organisations periodically review and research into successes and failures. Normally, successes are few and failures are more. In all cases, lots of revelations emerge, new insights are found, and new directions are found. This is a new learning of strength useful for incorporating into the knowledge base. • Learning organisations continually benchmark their processes, products, services, and so on. The benchmarking indicates the gap between the best and the organisations process, product and service. • Learning organisations sponsor research projects in reputed research organisations by funding the research and benefit from the research findings. The research topic of business interest could be suggested by the organisation to the research organisation. • Learning organisations make special efforts to learn from experiences of value adding partner organisations developed in the course of business management. The value adding partners contribute significantly to the organisation’s business. • The organisations encourage their employees to form Communities of Practices (CoPs) in the areas of organisations’ interest. The employees are encouraged by sponsorship to become members of professional bodies and clubs where knowledgeable people come together for social gettogethers. • Learning organisations frequently resort to following methods of knowledge transfer: • Personnel rotation at work centres • Deputation for a limited period • Working together and hand holding • Demonstrating and exhibiting • Transferring line manager to staff function • The standard methods of measuring the impact of knowledge initiative are to check the reflection in organisation score card and dashboard. But this might come up too late in time to react. Another measure is developed, known as ‘half life’ curve. The method was invented by Analog Devices, a leading semiconductor manufacturer, to measure and compare internal improvement rates. • The five disciplines (Organisational Pillars) were originally outlined by Peter Senge, and are the core pillar strengths for organisational learning efforts. There are many other disciplines that support and expand on the five pillars, • Shared vision • Team learning • Systems thinking • Mental models • Personal mastery

• The key ingredient of the learning organisation is in how it processes it managerial experiences. The managers in the learning organisations learn from their experiences rather than being governed by past experiences. • The real problem in the organisation arises not from change, but from not recognising and suppressing the change from occurring. Not changing does not eliminate the need to change; it only delays it. The risk of not changing at appropriate time continues to mount. And when the inevitable change occurs, it is often very large and more disruptive. • The only significant competitive advantage in all areas is the ability to continue to innovate, staying one step ahead of others. This cannot be duplicated by the competition. And this involves and all employees working together with outside partners. Our knowledge and drive to use our full capabilities to be the best cannot be duplicated easily elsewhere. This is the only true competitive advantage. • Organisational learning is also challenging many assumptions about organisational change that we sometimes hold without questioning. Organisational learning attempts to provide organisations with mechanisms to deal with the issues and the organisational assumptions implicitly held without questioning. • It is team learning, not individual learning, that adds to organisation learning. The path to organisation learning moves through individual learning to team learning to organisation learning. The field of organisation learning explores ways to design organisations so that they fulfill their function effectively, encourage people to reach their full potential, and, at the same time, help the world to be a better place. • In Organisational development (OD), learning is a characteristic of an adaptive organisation, i.e., an organisation that is able to sense changes in signals from its environment (both internal and external) and adapt accordingly. OD specialists endeavour to assist their clients to learn from experience and incorporate the learning as feedback into the planning process. • Individual learning moves through the four stage cycle: • Concrete experience • Reflective observation • Abstract conceptualisation • Active experimentation • Organisational learning is a process, involving interactions among many individuals leading to well informed decision making. Thus, a culture that learns and adapts as part of everyday working practices is essential. Re-use of knowledge and inventing something new is considered as a desirable behaviour. • Saint-Onge refer to the need for the HRM function to transform itself in order to respond to changing requirements of the knowledge era. He suggests a strategic capabilities approach where resources are structured across individual capabilities organisational capabilities, and knowledge architecture. • In the knowledge economy, the role of HRM needs to expand, looking both within and outside the organisation. The traditional focus on managing people has been broadened to managing organisational capabilities, managing relationships and managing learning and knowledge. • The emphasis on discrete HRM practices is also broadening to focus on developing themes and creating environments conducive to learning, as well as to the acquisition, sharing and dissemination of knowledge within the organisations.

• A revitalization of the HRM function to respond to the demands of the knowledge economy and to develop linkages with KM requires major changes across four key areas: Roles, Responsibilities, Strategic Focus and Learning Focus, impacting organisational learning. • The HRM function is now loaded with additional responsibilities of actively participating in executive function of the business enterprise, deviating from the support role to responsive, collaborative and participative role in management of the business.

Questions 1 Peter Senge developed the concept of ‘learning organisation’. He describes the learning organisation of the one where people continually expand their capacity to create results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspirations are set free, and where people are continually learning how to learn together. Explain the concept in detail. 2. Learning organisations resort more to following methods of knowledge transfer: • Personnel rotation at work centres • Deputation for a limited period • Working together and hand holding • Demonstrating and exhibiting • Transferring line manager to staff function Explain the situations where these methods of knowledge transfer will be used for transfer. 3. Peter Senge originally outlined five disciplines in the book ‘The Fifth Discipline: The Art and Practice of the Learning Organisation. They are core pillar strengths to organisational learning efforts. • Shared vision • Team learning • Systems thinking • Mental models • Personal mastery What is the outcome when these disciplines are followed in building a learning organisation? 4. Peter Senge developed following laws for Systems Thinking. Take each law and identify one example in your personal and professional life which illustrates the law. • The harder you push, the harder the system pushes back. • Behaviour grows better before it gets worse. • The easy way out usually leads back in. • The cure can be worse than the disease. • Faster is slower. • Cause and effect are not closely related in time and space. • Small changes can produce big results—but the areas of highest leverage are often the least obvious. • You can have your cake and eat it too—but not at once. • Dividing the elephant in half does not produce two small elephants. • There is no blame.

5. Explain and find the contrast among the following. • Adaptive learning vs Generative learning • Learning organisation vs Organisation learning • Experiential learning vs Experience based learning • Individual learning vs Team learning vs Organisation learning 6. Explain the new role of HRM in the learning organisation. 7. Test your understanding. Fill in the gaps in the following statements. • HRM must ensure _________ among an organisation’s mission, statement of ethics, and policies. • HRM must relax _________ and encourage behaviours that facilitate formal and informal interaction among employees. • HRM must build _________ and shared people communities around the strategic objectives of the business to ensure competitiveness. • The traditional role of HRM as _________ _________ now needs to be a _________ _________ to bring in change in culture, practices and management. • In order to gain _________ _________ from KM, organisations need to identify core competencies, integrated knowledge sets, termed as knowledge products, intellectual capital and property. • HRM should take up the task of developing and sustaining _________ _________ capabilities through activities that overlap with traditional business functions, such as strategy formulation and implementation, finance and marketing, as well as new functions, such as KM. • Organisation learning means the process of _________ _________ through better knowledge and understanding. • Human capital refers to individual employee _________ their knowledge, skills and abilities, and their willing ness to transfer, share and put to use for business benefit. 8. Explain how Herbert Simon Model and PDCA cycle help in learning. 9. Explain how mental models are opportunities and limitations for learning. 10. What is the manager/leader’s role in the learning organisation?

8

Chapter

Management: Tools and Technology (A Driver of Successful KM Implementation)

This Chapter Deals with • • • • • • • • •

Information and Communication Technology (ICT) Unified Communications Technology (UCT) WiMAX Technology Data Warehouse and Data Mining, Business Intelligence OLAP Search Engines Intelligent Agents Knowledge Portal, Knowledge Products Groupware Technology for Knowledge Transfer

Learning Outcome The objective of this chapter is to provide a meaningful, indepth exposure to tools and technology used extensively in KM. It will raise the reader’s understanding and he will be an intelligent user of tools and technology in driving KM function in the organisation.

Technology is enabler/driver and not substitute for the knowledge

“Today, after years of steady progress, artificial intelligence has evolved new techniques, such as neural networks and intelligent agents, and is being widely applied in a growing number of applications. The main hurdle affecting all applications of ICT to knowledge management is coping with the fundamental difference between explicit and tacit knowledge”. –Dr David J. Skyrme, David Skyrme, Associates Limited

In a knowledge driven learning organisation, tools and technology drive the KM function. They are inseparable. Tools and technology add speed and efficiency in driving KMS operations. They contribute in all phases of KMSLC, and identification of knowledge to raising it to level of intellectual capital. They facilitate its storage, transfer and sharing with the users. In this chapter, we cover major tools and technology which contribute significantly towards the success of KM function in the learning organisation. The objective of this chapter is to give a meaningful exposure to this topic so that the learner would understand its role and importance in KM, and would play a value adding partner’s role in taking KM forward in the organisation.

INFORMATION AND COMMUNICATION TECHNOLOGY ( ICT) ICT is defined as a set of technologies and tools used to communicate, and to create, disseminate, store, and manage information and knowledge. These technologies include computers, networks, the internet, WEB radio and television, mobile devices, cameras and digital technology in general. More specifically, they include: 1. Audio cassettes 2. Video cassettes 3. Streaming videos 4. Radio 5. Television 6. Computers 7. Networked computers: Servers and clients 8. Internet, Intranet, Extranet 9. Audio conferencing 10. Tele conferencing 11. Web based conferencing

KEY TERMS • CEBP • E-Learning • Blended Learning • Enterprise Information Portals • Data Mart • IA Environment • Query and Reporting Tools • Learner Centric Environment • Digital Literacy • UC Enabled Business Process • Extended Unified Workspace • Wi-Fi Network.

12. Data and Data base management systems 13. Data warehousing and data mining Different technologies used in different combinations for delivery of the subject. Telephone, radio, and television popular for a number of years. Other technologies are now increasingly being used as delivery mechanisms to transfer and share knowledge across the organisation.

Potential Capabilities of ICT Information and Communication Technologies (ICT), with their proven capabilities, have potentially been considered powerful enabling technologies for Knowledge Management. The potential capabilities of ICT are: • Delivery anywhere • Presentation in any form • Demonstration in multi media • Experimentation to test hypothesis • Interactive, collaborative through networks for knowledge exchange and sharing • Manipulation and creation of new formations of knowledge and its products • Seamless communication of knowledge in any format • Restrictive as well as open The limited experience of making KM ICT enabled reveals that full realisation of its potential is not possible automatically. The ICTs need to be integrated in an overall KM system, giving regard to organisational readiness, employee competencies and knowledge strategy.

E-Learning, Blended Learning and Distance Learning E-Learning E-learning is more popular in higher education and corporate learning. It extensively uses the internet, intranet and extranet on LAN and WAN. It uses internet platform for knowledge delivery, interaction, communication evaluation and feedback. It is also called online learning and Web based learning. Blended Learning Blended learning assumes that not all learning is achieved through E-learning. It is necessary to have expert or mentor interaction and intervention. This is largely decided by the characteristics of the learner and the subject itself. • This method combines traditional classroom interaction with e-learning. • It uses print material and online material for all steps of learning. • Blended learning is gaining ground as not all learning is effective through e-learning. • The necessity of expert’s intervention or interaction in the process is a necessity. Distance Learning Distance learning is chosen where reach and access is a problem, compounded by cost of delivery. • This method separates employee and expert in time and distance. • It uses electronic and print media to communicate and share information and knowledge. • It is, by and large, time bound and delivers a structured knowledge course in structured manner on a time scale.

Learner Centric Environment The key to effective knowledge transfer, sharing and application is whether the delivery of knowledge is in Learner (Employee) centric environment. Learner centric environment is described by learner’s current level of knowledge, digital literacy, attitudes and beliefs, and access to ICT platform. Digital literacy is measured by four factors. • Functional Ability to make a meaning out of images, graphics, videos, charts and graphs. • Scientific Ability to understand both theoretical and scientific aspects in any situation. • Technological Ability to use ICT for effective learning. • Application Ability to find and use information through ICT for decision making, or for enhancing knowledge level. Further, digital literacy is dependent on three other skills, namely, inventive thinking, communication skills and personal skills. Inventive thinking is governed by: • Curiosity Desire to know, desire to search • Creativity Ability to create new thing with imagination • Adaptability Ability to adjust fast in a complex world of interdependent systems • Problem solving Ability to identify the problem and get a quick solution Communication skills are built on: • Collaboration Ability to interact smoothly within the team • Interactive communication Ability to convey, transmit information effectively Personal Skills are built on: • Teaming Ability to work in a team with comfort and confidence. • Productivity Ability to plan, prioritise programmes and delivers results Knowledge in electronic format is most useful when it is linked to business and knowledge strategy of the organisation. It is seen more useful when used as a tutor, or for becomes demonstration and practice and for instructional delivery. Most common uses of ICT are in promoting ICT literacy, developing course materialText and PPTs, creation of self learning material. The full realisation of ICT’s potential is not automatic. It needs planning and implementation of an ICT enabled system considering the learner centric environment. The access to ICT can be exploited if learner has digital skills and inventive thinking. It helps to reduce knowledge divide and raises digital literacy. ICT is effective if employee is motivated to initiate the learning. Full realisation of ICT capabilities is possible through its effective integration in the KM system, institutional readiness, expert’s knowledge competencies and employee focused KM design.

UNIFIED COMMUNICATIONS TECHNOLOGY (UCT) In today’s world of work, organisations face multiple challenges—globalisation, maintaining a connected mobile workforce and increased competition. To maintain their competitive advantage, organisations must adapt and get better through process innovation, capturing strategic insights and delivering customised services. Unified communications technologies improve efficiency and effectiveness of supply chains by enabling stakeholders to collaborate even when located anywhere in different time zones. Different functional teams and experts, along with external supply chain and logistics partners, can share data and information to act

fast. With integrating of UC capabilities into business processes, employees can quickly and easily find the right person and communicate through the software applications and business processes currently in use. The unified communications solution makes it possible for executives to access instant messaging, presence, and audio, video, and Web conferencing from any location. This provides great flexibility in work options, improving the quality of life for employees. In addition, it increases home and flexible working opportunities for those who stay far away from work place and find it difficult to commute to the office every day. Unified communications technologies bridge the divide between computers and telephones with two integrated servers: Exchange Server and Communications Server. They integrate in the organisation’s existing phone system and deliver complete communications services using existing data network. Unified communications technologies maximise existing infrastructure by integrating legacy PBX systems through a VoIP/IP-PBX gateway. Databases: Product, Material

Knowledge Database

Critical Information DB

Unified Communication Enabled Business Process

Fig. 8.1

UC Enabled Business Process

While UC integrates people and communication hardware through messaging and exchange of information, it is possible to make the business process UC enabled to the extent that it is completely automatic, termed as Communication Enabled Business Process (CEBP). We will talk about CEBP in greatwr detail later in this chapter. The business processes function with support of databases. These processes, however, need human intervention by way of approval, choice of alternative, sending alert to other location, and so on. UC technology implementation in the process makes it automatic saving time, cost and delays.

What is Unified Communications? Unified communications (UC) systems bring together voice, video, data and mobile applications in business to improve business competitiveness and profitability. Such integration of different communication technologies liberates employees from their desks and Desktop’s adding speed into decision and action, raising HR productivity. The rise in HR productivity has direct impact on cost and profitability. UC is typically a software programme suite and technology infrastructure which enables an individual to send or receive message in one medium and receive it on another at the destination. For example, a mail message sent at a project site would be seen by the site engineer.

The software programme combines these communication mediums to transfer the message to another medium. The programme automates unification of all forms of human and device communications into a common user required medium. Such unification optimizes business processes and increases efficiency and effectiveness of human communications. It also reduces latency, simplifies the flows, and eliminates device and media dependencies. A very strong feature of UC is that it checks the Presence of the recipient and then allows the communication to trigger. The feature ‘presence’ identifies the recipient, the location and availability in real time before communication is pushed to the destination. Unified communications is different as opposed to UM (Unified messaging). Unified communications makes a real time delivery of the message to a preferred location on a preferred device, medium. Unified messaging system gathers messages from different sending sources but holds those messages for retrieval by the recipient at a later time. UC is in real time and UM is not in real time. Unified communications integrates all the communication systems and helps those systems to work in sync in real time. Unified communications is very useful for both knowledge workers and service workers alike. These personnel are required to work in collaboration to achieve some results. In today’s distributed business operations, knowledge workers and service supporters are at different locations. A customer requirement or query may not be satisfied from one location. It may call upon drawing the assistance from different sources through communication exchange. UC technology enables collaboration and process integration to meet customer expectations. UC capability helps in defining the requirement through collaborative interaction of experts, getting acceptance from the customer, changing and integrating the process change to deliver the new requirement. The service workers and process designers work in collaboration to satisfy the customer requirement. Employees, business partners and customers collaborate to conduct business operations with a combination of different communication modes across multiple workspaces, such as: • Their own desks • Conference rooms • Airports • Warehouses • Branch offices • Customer or vendor locations • Vehicles

Components of Unified Communications (UC) Unified communications includes a variety of communication elements or methods, such as: • Instant messaging • Telephony • Video • E-mail • Voicemail • Short message services • Video conferencing • White boarding

The immediate benefit of UC is seamless collaboration with the other person at a separate location. For example, the project manager can quickly locate the site engineer and engage in interactive communication session and then change the session to another medium, say video call, if required. In another example, Customer Support Manager receives a query from the customer. UC enables the manager to access a real time list of expert colleagues, and then make a call on the chosen expert, facilitating the manager to answer the customer faster in real time without lengthy rounds of e-mails and phones. While collaboration is important, UC capabilities can be used to transform business processes as well. This is achieved by integrating UC functionality directly into the business applications using development tools. For example, on UC integration, the workflow process application automatically identifies the required resource at the point in the process where it is needed and secures it through appropriate communication medium. UC enhances workforce and application productivity impacting on cost, time and delivery.

Unified Communications in Action The sophistication of unified communications technology enables generation of many applications in business. Suppose two persons want to collaborate to produce a contract document. UC helps to find the recipient’s current location (office, car site) and the choice communication, such as e-mail, voice or instant messaging, Then, they together seamlessly set up a real time collaboration event to create the document. Another example is, use of UC for retail price checking for the customer. A floor boy in the mall can do a price check on a product using a hand-held device or a cell phone, and consult the commercial manager to satisfy customer inquiry on the price. Many such situations can be found in all organisations, whether they are manufacturing or service, where parties are at different locations supported by different communication aids. In all such situations, collaboration and action is demanded instantaneously in real time, based on knowledge and information stored at different places. UC is best where action is needed. Unified communications helps businesses to streamline information delivery to desired location through chosen mode of communication in real time. Human delays are also minimised or eliminated, resulting in better, faster interaction. The service-delivery for the customer is faster, and results in cost saving for the business. Unified communications also allows easy direct collaboration between co-workers, and with vendors and customers. Together, they can set up a problem and solution design to handle a specific situation. This allows for possible reduction in business travel, cost and time.

Extended Unified Workspace Unified communications combines all forms of business communications into a single unified system. This combination creates a unified workspace for collaboration for customer, knowledge workers, designers, vendors and service personnel. It extends the work environment boundary beyond your desktop to any location. UC gives ability to the organisation to: • Collaborate across any workspace Organisations can quickly adapt to market changes and build competitive advantage. • Accelerate decision making Supported by faster information delivery to the right persons in real time at any location. • Innovate across the value chain Integration of UC into business process raises the value of the process.

Productivity Rise Across the Organisation Unified communications uses the network as a platform for integrating communications with business processes. Business productivity and profitability improves further with:

• Instant connections with the person • More effective communications • On-demand collaborations between employees using different technology platforms and checking the presence of the person • Easy and quick access to information • Reach people anywhere • Spontaneous communication Unified communications systems improve competitiveness of the business through reduced cost of operations and higher return on investment. A complete unified communications solution is offered by Microsoft and Cisco.

Communications Enabled Business Processes (CEBP) The goal of Communication Enabled Business Process (CEBP) is to optimise business process by reducing the human latency that exists within the process flow. UC enabled business process automates human side or aspect of the process execution. That is, recognising the problem, seeking information, analysing and resolving to put the process on hold back to track. All business processes operate on and manipulate data. For example, applications, such as Supply Chain Management and Sales Force Automation, are used to automate business processes. But automated processes can only do operational functions. People are needed in the process to make decisions and take action at key points, or when unexpected business conditions arise. UC technology handles human side of the process. CEBP is about improving the processes and systems that drive business. To make a process communication enabled a study of ‘Human – Process’ interaction is necessary. Human intervention in the process delays the progress and flow of information. The more intervention, the longer is the process cycle time. You may start by examining your current business processes, particularly the customer facing ones, or processes in key result areas. Look for gaps or delays in the flow between systems and people. Identify the processes where human intervention causes bottlenecks and delays due to lack of availability, missing data or indecisiveness. Most business processes are automated through software to reduce manual work and shorten cycle times. But, to function correctly, even these processes must still have people to provide and receive information, analyse data, and make decisions. The process owner’s involvement is latent. The process progress is dependent on the owner. It halts till the owner recognises the intervention need and acts on it. Unfortunately, in the vast majority of processes, the communications needed to coordinate an effective response are poorly automated, or are not automated at all. Business process reengineering efforts focus on optimising business applications and data management, but often do not address human interaction in processes. The largest single value in unified communications lies in its ability to reduce latent human intervention within processes and improve the business’ ability to respond and be agile. Let’s say, a manufacturing company has to shut down production due to a quality control problem. The shutdown triggers the production control system to send an alert to a supervisor, who would then engage team members to resolve the problem. But what happens if that supervisor doesn’t answer the alert immediately? The process stalls. CEBP solution to this problem integrates with the manufacturing system a automated communication process to call the supervisor through a variety of fixed and mobile devices. CEBP solution will locate and alert the supervisor and seek response to the problem. If the problem demands expert group

attention, communications could also be sent to the group members, even bringing them all together in a live conference call to work on the problem. This new way of UC application to interact with a process is a breakthrough for productivity. CEBP solutions even keep a full audit trail of such transactions. The result is efficient resolution of the problem and the process is restored quickly. Later, the situation can be analysed and the process revised or reengineered to ensure future smooth operating. For example, an insurance claim process and settlement is longer due to responses required at various stages from the Surveyor, Agent, Manager, and so on. These personnel may be on leave or may travelling or engaged in other tasks. The claim process waits for the response to progress towards settlement. The involvement of these three key people in the process is latent. The process experiences the delay due to human latency. To reduce this latency, the process leverages UC capabilities by embedding them into the business process flow. If any one of these persons does not provide the necessary response within a designated period of time then the business process would invoke a UC service, such as ‘notify and respond’ from an IP PBX, voice portal, conferencing application, etc. These embedded UC services would ‘notify’ the person that action is imminent. If the person does not ‘respond’ to the notification then it can be escalated to higher lowers in the same manner. UC services that could be embedded within a business process to reduce human latency are conference [on demand], alert, escalate, contact resident expert, etc.; all of which create measurable business value. The great thing about CEBP is that it can be applied horizontally across different lines of business and different industries. Virtually every business process is hampered by human latency. In claims processing, the organisation’s goal is to decrease claim close times and improve their closure rate. However, this process is often hampered by several inefficiencies—the paperwork process can be manually intensive, time-sensitive dependencies on member signatures exist, resulting in significant delays in the approval process. A CEBP solution would be implemented to automate all communications in claims process with embedded UC services, like reminders, alerts, notifications and escalations. Quantifiable business results of such automation are decreased cycle times, greater HR productivity, enabling them to spend more time adjusting claims rather than fielding calls on the claims, increased revenue, and customer satisfaction and retention. As described above, CEBP is much more sophisticated in its ability to automate business process flows; it is usually event triggered, providing a much stronger ROI to many lines of business and vertical industries.

WiMAX TECHNOLOGY WiMAX is a wireless broadband technology that takes internet connectivity, limited to home or office, anywhere and anytime on laptops and mobile phones. The internet is all set to expand its customer base, who are contemplating to do business online. As per Intel study, 100 million India as are required to be connected in the next five years. The connectivity through broadband is a major limitation. This is where WiMAX technology will come in handy. WiMAX is a proven technology for carrying multimedia content. It can work in the bands of 2.5, 3.5 MHz. WiMAX is a Mobile internet and revolution in computing. It acts as a bridge between telecom and Information Technology. WiMAX, meaning Worldwide Interoperability for Microwave Access, is a telecommunications technology that provides wireless transmission of data using a variety of transmission modes, from point-to-point links to portable internet access. The technology provides upto 75 Mb/s symmetric broadband speeds without the need for cables. It is based on the IEEE 802.16 standard (also called Broadband Wireless Access). The name

WiMAX was created by the WiMAX Forum, which was formed in June 2001 to promote conformity and interoperability of the standard. WiMAX is the next generation of wireless technology designed to enable pervasive high-speed mobile Internet access to the widest array of devices, including notebook PCs, handsets, smart phones, and consumer electronics, such as gaming devices, cameras, camcorders, music players, and more. As the fourth generation (4G) of wireless technology, WiMAX delivers low cost, open networks, and is the first all IP mobile internet solution enabling efficient and scalable networks for data, video, and voice. As a major driver in the support and development of WiMAX, Intel has designed embedded WiMAX solutions for a variety of mobile devices supporting the future of high-speed broadband on-the-go. (Source: Intel Corporation) WiMAX is a highly scalable, long-range system, covering many kilometres, using licensed spectrum to deliver a point-to-point connection to the Internet from an ISP to an end user. It can be used to provide a wireless alternative to cable and DSL for broadband access, and to provide high-speed data and telecommunications services. It can also be used to connect many Wi-Fi hotspots with each other, and also to other parts of the Internet. With WiMAX enabled handsets and laptops coming into the market, people could connect to the fast broadband internet from anywhere, without having to depend on the slow rate mobile network data transfer. You can work on broadband, call friends and colleagues and watch real time TV from the top of a forest hill station many kilometres away from the access point-without compromising on quality, speed or screen size. WiMAX can connect remote locations to the Internet using broadband. This would avoid hassles in cabling through the forests and other difficult terrain only to reach a few people in remote places. Maintaining such system would also be easy. WiMAX could provide Internet access, voice and IPTV to those areas. In contrast to WiMAX, Wi-Fi is a shorter range system, typically hundreds of metres, used by an end user to access own network. Wi-Fi, which stands for Wireless Fidelity, is a wireless networking technology used across the globe. Wi-Fi refers to any system that uses the 802.11 standard, which was developed by the Institute of Electrical and Electronics Engineers (IEEE) and released in 1997. In a Wi-Fi network, computers with Wi-Fi network cards connect wirelessly to a wireless router. The router is connected to the Internet by means of a modem, typically a cable or a DSL modem. Any user within 200 feet or so (about 61 metres) from the access point can then connect to the Internet, though for good transfer rates, distances of 100 feet (30.5 metres) or less are more common. Wi-Fi is technology designed to cater to the lightweight computing systems of the future, which are mobile and designed to consume minimal power. PDAs, laptops, and various accessories are designed to be Wi-Fi-compatible. There are even phones under development that would switch seamlessly from cellular networks to Wi-Fi networks without dropping a call. Wi-Fi is low cost and is generally used to provide Internet access within a single room or building. For example, many coffee shops, hotels, railway stations and bus stations contain Wi-Fi access points providing access to the Internet for customers. Wireless routers which incorporate a DSL modem or a cable modem and a Wi-Fi access point, often set up in homes to provide Internet access and inter-networking to all devices connected (wirelessly or by cable) to them. One can also connect Wi-Fi devices in ad-hoc mode for clientto-client connections without a router. Wi-Fi allows LANs to be deployed without cabling for client devices, typically reducing the costs of network deployment and expansion. Wireless network adapters are also built into most modern laptops. (Source: Sree Pillai, TECK. IN). WiMAX is similar to Wi-Fi but it operates at greater speeds, over a greater distance and for a greater number of users. WiMAX has the potential to bring internet connectivity to rural remote areas. WiMAX will bring web world within reach of the rural community. The main problem with broadband access are that it is expensive and it doesnot reach all areas. The main problem with Wi-Fi access is that the hotspots are very small, so coverage is sparse. WiMAX has the potential to do to broadband Internet access what cell phones have done to phone access. Many people have given up

their land lines in favour of cell phones. In the same way, WiMAX could replace cable and DSL services, providing universal Internet access just about anywhere you go. WiMAX will also be as painless as Wi-Fi, turning your computer on will automatically connect you to the closest available WiMAX antenna. The Figure 8.2 shows a model of how WiMAX works. How WiMAX WORKS

Internet Backbone ISP Network

Home Local Area Network

Fig. 8.2

WiMAX 802.16 Transmitter Line of sight Backhaul

Non Line of Sight Transmission

Model of how WiMAX Works

A WiMAX system has two components, • A WiMAX tower: Like cell phone tower, providing coverage to 8000 sq kilometres: • A WiMAX receiver: The receiver and antenna could be a small box or PCMCIA card to be fixed to laptop or desktop. A WiMAX tower station connects directly to the internet using a high broadband width connection, a T3 line. It can also connect to another WiMAX tower using a line-of-sight microwave link. This connection to a second tower is also called backhaul. Mobile Phone Network Backhaul WiMAX can provide point-to-point links of upto 30 miles. Therefore, mobile phone operators could use WiMAX as a backhaul instead of a wired alternative at a far greater expense. Wireless Service Provider Backhaul Even if WiMAX is not used as a ‘last mile’ solution it can be used as a backhaul for wireless service providers. Again, deployment of a wired solution would be far more costly and would take more time to install.

Applications and Benefits of WiMAX Speed and reach are the biggest advantages that WiMAX offers to its users. The potential capability can be used to build networks covering remote areas for communication, information sharing, spreading knowledge, and for e-learning. Deployment times would be significantly lower than for wired solutions as minimal construction is required.

Given below are some networks which can be tried out very easily:

Education Networks Taking knowledge to remote axes is a difficult task. Providing teachers in remote villages is impossible. Therefore, groups of schools could use WiMAX to connect them within a district and nearby rural areas. Classroom instructions could be delivered in real time between two or more schools using video link via a private WiMAX network.

Public Safety In a crisis, like a terrorist attack, fire or earthquake, communication is the weakest link hampering rescue operations. WiMAX networks could be used to aid response in emergency situations. Also, two-way voice communication and video communication could be relayed between the accident/disaster site and dispatch centre, allowing emergency teams to assess situation in real time. Additionally, mobile WiMAX could allow emergency teams to access databases of information from moving vehicles.

Offshore Communications WiMAX could provide a communications link between land based facilities and offshore sites to support remote operations. WiMAX networks are quickly and easily deployed, even when offshore sites are moved to a different location. Oil drilling sites in far away locations from the shore can use WiMAX for communications.

Campus Connectivity University, large public sector undertakings, research laboratories, government office complex are distributed in different buildings over a large area, called a campus. Multiple locations within campuses could be connected via WiMAX.

Temporary Construction Communications As constructions sites are temporary, wired solutions are impractical. WiMAX equipment is highly portable, therefore, can be redeployed and reused at other construction sites.

Strengths of WiMAX The strengths of WiMAX are many. Some of them could include:

Cost Efficiency The very fact that WiMAX is wireless technology means that the expensive procedure of laying cables can be avoided. This removes the cost of labour, materials, land, etc., and can be replaced with only the cost of installing a WiMAX tower. This could help bring internet connectivity to rural areas, without the cost of wires. WiMAX could easily be deployed in less densely populated areas.

Mobility of Data WiMAX makes data mobile, ready to move to many users, anywhere. If WiMAX connection is available and a user has appropriate WiMAX ready devices, internet connectivity would be readily available. This offers a potential of real time media streaming. There is also potential for using VoIP. WiMAX towers can be quickly and easily redeployed and reused in completely different locations, enabling WiMAX networks to be set up in different locations after they are no longer required in previous locations.

DATA WAREHOUSE AND DATA MINING, BUSINESS INTELLIGENCE Since the early 1990s, data warehouses have been at the forefront of information technology applications as a way for organisations to effectively use digital information for business planning and decision making. Hence, an understanding of data warehouse system architecture is important in our roles and responsibilities in information management and knowledge management. Data warehouse in KM plays an important role where knowledge is hidden and other tools and techniques are used to hunt and capture it for adaptation. The concept of Data Warehouses (DW) has emerged from several sets of information which users need. The needs have arisen from change in management style of different classes of end users, who now need organisation wide view of the information and knowledge. These needs are critical for the success of the business. The need for DW is felt due to quality and content requirement of information and knowledge of different kinds of end users in an organisation. There are three kinds of end users of information, the management, and knowledge workers and operations staff. The management needs holistic view of a situation predicting in to the future. It helps to know whether a critical change has taken place in the business, is the change showing any pattern, and which factors are affecting the change and its pattern? In order to control the change and use it to business advantage, the management requires analytical information support to make strategic decisions. The DW designed to meet these needs would satisfy such requirements. As business is becoming more competitive, business risk needs to be insured. The view of decision making situation is no longer atomic, local and functional, it is larger in scope and content. The view may vary between business functions, entire enterprise and the global environment. To meet such needs, data and information is sourced from within the organisation, and also from external sources. Data Warehouse is defined by Bill Inmon as, “A collection of non-volatile data of different business subjects and objects, which is time variant and integrated down various sources and applications and stored in a manner to make a quick analysis of business situation”. Data Warehouse is: • Subject oriented data organised by business topics, by functions/results, and not by customer, vendor, item code, and so on. • Integrated data stored in single unit in same structure or organisation. Distributed data in different files is rationalised and organised to one structure. • Non-volatile data which once stored is not discarded or over written. New data on the topic is added on scheduled basis. • Time-variant data stored with time dimension to study the trends and changes with times. DW is a special database containing large stocks of enterprise data and related meta data processed to a ‘ready to use’ stage for decision maker for operational and analytical business analysis. The conceptual DWH architecture is shown in (Figure 8.3). First step in building Data Warehouse (Figure 8.4) is to extract data from different sources. After this, data needs to be validated for coding structures, names and formats. It is rationalised to a common unit of measure through transformation or conversion process. Such data set is then consolidated to common reference level, such as end of month, region, zone, etc. The data so processed is then moved to DW. All these processes are handled by middleware, written to construct the DW. Middleware is a set of programmes and routines which pulls data from various sources, checks and validates, moves it from one platform to an other, and transforms to the DW design specifications, and then loads in the DW.

BI DWH Three Layer architecture: 2. Data Reconciliation System

3. Derived Data Generation System

BI Generation System

Operational Data Base

Reconciled Data Base

Derived Data Base

1. Operational Data Capture and Generation System

Real Time Data

Fig. 8.3

Real Time Data

Real Time Data

Conceptual DWH Architecture Data Warehouse (DWH) DWH Business Information

Metadata Extract

Production of BI with Meta data DWH Creation System Extract, Rationalise, Cleanse, Reconcile, Summarise

Extraction of Data

Database

Fig. 8.4

Extraction of Data

Functional Data Servers

Data Warehouse Creation System

Extraction of Data

Extraction of Data

Dedicated Servers

Distributed Data bases

Following are the characteristics of Data Warehouse which differentiate it from database. • The scope of Data Warehouse is the whole organisation. • It contains the historical record of business created from existing application. • It enables the user to take business view, application view and physical view at a point-in-time on any aspects of business situation. • Data Warehouse supports cross functional Decision Support Systems (DSS) to manage the business, as it provides detail, historical, consistent, normalised business data for further manipulation by the decision makers. Data Warehouse usage makes business decisions on facts and not on intuition. This is applicable to both tactical and strategic business decisions. It enables the user to get insight in key areas of business where information support for strategic decisions is necessary. If viewed intelligently and with imaginative mind, it helps the user to sense early warning on some aspects of the business, calling for business review and radical change in policy, rules and strategies. Business data assumes importance when it is useful to manage the business. The data, which is necessary to manage the business, has value from strategic point of view. The rest of the data is useful to run the business. All business data are candidates for the Data Warehouse. It is also true that the business data of one organisation would turn out to be routine information for an other organisation. For example, customer data has no business value in manufacturing organisation, but it has business value in a post-sales service organisation. The qualification for business data depends on the business, its current status the and business strategy need at that point in time. There are no thumb rules for deciding. Normally, operational data used to run the business and support short-term actions or decisions is not considered for Data Warehouse. For example, in inventory application, an item and its inventory related statistics is not considered for Data Warehouse, but the data related to consumption and its measure of application in the product is considered. Other important decision about business data is to decide its currency level in terms of time. The three currency features for business data are current data, point-in-time data and periodic data. • Current data is a view of the business at the present time. It is unto a second and changes with respect to time. • Point-in-time data is a snap shot of business data at a particular moment in time indicating the business status at that point of time. • Periodic data is a representation of business data by periods, such as last three years, last twelve quarters, etc. Broadly, current and point-in-time data are not candidates for Data Warehouse but extracted data and analysis of this data are candidates for DWH. This data is useful to show travel patterns, trends in hotel occupancy, direction of the business, and may reveal certain underlying business currents. Hence, this data has a case for being in Data Warehouse.

Data Warehouse Design Data Warehouse design process brings with the construction of the Enterprise Data Model is built keeping in mind its application to build Data Warehouse. The objective of this step is to obtain high level unified view of data required for strategic decisions. Enterprise data model may first begin with the help of a generic model of the business. In this model, all views on data required to manage the business are considered. It also takes into consideration a generic industry data model, if it exists, and customise it to enterprise requirement.

Building Data Warehouse design calls for bottoms up approach to use of data in Data Warehouse. The process flow of building Data Warehouse Model is explained in the following points: 1. Build Enterprise Data model which specifies the need for data in terms of form, content, period and its application to manage the business. The data in data model, therefore, is common to any business view across the levels in the organisation. 2. Locate operational systems which are more appropriate from where data can be sourced to build Enterprise Data Model. 3. Identify critical applications which are necessary to manage the business. 4. Select low-level data entities which, when processed, build the critical view of an application or function. 5. Identify related meta data which describes the data used in critical view of the function or business. 6. Map data and meta data to applications from where they would be sourced. 7. Get into the process of building reconciled data for subsequent generation of derived data. 8. Determine most sought queries from the organisation and process them to produce the results known as derived data, which would show instantaneous status of business based on preconceived view of the business. 9. Then clearly define the reconciled data and derived business data for storing into the warehouse. Use DBMS to put derived business data in Data Warehouse. 10. The design techniques used in Data Warehouse creations are essentially three, enterprise data modeling, reconciling on time scale, and data replication. • Enterprise data modeling technique defines the data which is common for all business and stipulates agreed view for common understanding of the end user. • The reconciling techniques using time dimension of data are useful for viewing the performance of the business on the time scale. • Data replication is a technology for taking data from one source with time stamp to other location. It is a set of techniques that helps to copy and transfer the data from source to target location without losing its consistency and integrity. The replication process is a scheduled one and, as far as possible, it is system triggered. • Populating the Data Warehouse, after capture, conversion and application of operation data, is done through DBMS. Archiving and retrieval are the basic processes used in managing the Data Warehouse. 11. Most important after data modeling is to decide on data capture from various sources. A static capturing method collects data once, which is time independent. 12. The process of putting data in warehouse at appropriate place is executed through a separate application. It is executed through the following steps. • Load the new data replace the old. • Append the incremental data to the last up-to-date. For example, monthly sales data is appended in month table of sales in Data Warehouse. • Merge new data into the old one either through constructive merger, where data gets added to the existing set, or through destructive merger where, when the data key matches, data is replaced. Where it does not match, it gets added.

Apart from increase in productivity of end users, the Data Warehouse, in a number of cases, has helped to find new ways of competing through building new and radical competitive strategies. With superior quality of business data in Data Warehouse, more correct and focused business view is possible, bringing along knowledge of changed business environment. This means better understanding of critical areas of business, forcing application of management effort into key result areas. Data Warehouse, normally, is justified in competitive business environment. The businesses, driven by customer expectations justify investment in Data Warehouse. All service industries where customer satisfaction is a critical success factor work with Data Warehouse to evolve different service strategies to please the customer.

Query and Reporting Tools These tools satisfy the need of viewing the subset of business data to meet a particular business information, such as market share, vendor performance corporation, cost and quality matrix for critical material, etc.

Data Analysis and Prediction Tools These tools are available in two varieties. One is statistical which helps to compute averages, standard deviations, curve fittings, and so on. The other set of tools are spread sheets which help to structure the data in tabular format using business rules, and also help to present in graphical form. Data analysis and prediction tools help to look for underlying pattern or trend in any business aspect. They also help to ask questions and then helps in to finding answers by going through different analysis of the same data for additional data. OLAP (On Line Analytical Processing) is a tool very handy for analysing data which has following characteristics. • Large volume of data • Consolidation upward and drill down is necessary to search for a meaning • Dynamic viewing and analysis of data from different perspectives using complex relationships OLAP is particularly useful when user wants multi-dimensionally business data analysis. For example, sales analysis is required on time, zone and branch organisation as dimensions. Data Warehouse is an information asset for the top management. Most of the Data Warehouse is of large size, storing business data for strategic use and multi-dimensional views. The query and reporting systems help to know the status of any business subject. OLAP systems provide multi-dimensional analysis of any business subject.

Data Mining of Data Warehouse Data Mining is a tool available to the top management to make impact analysis of the key business factors and the relationship among them. Data mining tools help to unearth underlying patterns in the business and the factors influencing these patterns. Data mining solution provides capability to build prediction model. It helps to discover association and sequential patterns in the business data. For example, through a data mining application we can discuss a pattern of sales linked to time and some influencing factor. It is not possible to see such a pattern unless we visualise the possibility and mine the business data from warehouse and test their association. Data mining tools help to research into warehouse data to confirm the pattern of trend and also, in some cases, help to discover the pattern itself. Such research adds to knowledge of the decision maker, making him strong in decision making. It also helps to get insight into underlying business complexities and their behaviour and, with this knowledge, decision maker’s knowledge gap is reduced.

There are three separate components of enterprise data warehouse, the Data Warehouse, Data Mart and Data Mine. Data mining focuses on business and on some aspects of business where knowledge about the business is lacking. During the course of analysis, viewing and querying, if some findings are unexplained, then data mining helps to unearth why and how the particular scenario has emerged (Figure 8.5). Data Mining Applications Data Mining

• DM Architecture

Mined Data

3 2

Business Information DWH

Marketing Data Mart

1

Analyze/query Modeling/ Forecasting etc.

Displays many BI views** Marketing Data Mart

**BI Veiws: 1. Revelations 2. Insight 3. Predictions Leading to knowledge for decision/action

Fig. 8.5

Data Mining for BI Views.

Business Intelligence Business intelligence involves the integration of core information with relevant contextual information to detect significant events and bring clarity to cloudy issues. It includes the ability to monitor business trends, to evolve and adapt quickly as situations change and to make intelligent business decisions. It relies on exploration and analysis of unrelated information to provide knowledge through relevant insights, identify trends, discover opportunities, take proactive decisions and create value. Business intelligence (BI) is all about converting a large amount of corporate data through processing and analysis into useful information and knowledge, thereby triggering some profitable proactive business action or decision. Business intelligence environment is made up of business models, data models, extraction, and transformation and loading tools (ETL Tools) needed to transform and organise the data into useful information and knowledge for storage and further analysis. To set up BI environment, skilled people are required who can understand business intelligence requirement at a point of time and know the right source of data and applications from where the data and information would be extracted to build business intelligence. The process leading to BI begins with application of ETL tools, which extract data, cleans it, and organise it in data model after checking for validity and referential integrity for storing in data warehouse. Data warehouse is a centalised repository of such data. The next step is to build data marts. Data mart is a section of data warehouse on subjects like sales, production, and others, for functional or subject analysis. Data warehouse and data marts are used further to view data in different dimensions, in the three dimensional (cube) to throw light on subject’s performance and behaviour. Once the data warehouse, data mart, knowledge base

Process of Data Mining for Knowledge Recovery BI

• Process

Selective Extract of BI

DWH

Data Mart Knowledge Search :Process BI With Context

Data Mine of Selective BI

Knowledge Search Process

Fig. 8.6

Searching Hidden Associations

Predictive Modeling

Developing Rules

Viewing

New Segmentation

Knowledge Process

Knowledge Process

Knowledge Process

Knowledge Process

Knowledge Process

Process of Data Mining for Knowledge Recovery

and data cubes are built, queries are built to see the contents of these bases, which are then termed business intelligence. Different views are obtained through query and OLAP tools. The quality of B.I, therefore, depends on the person who has the vision of views, and puts queries to extract data to get the view on the subject.

OLAP OLAP, an acronym for ‘Online Analytical Processing’, is a technique by which the data sourced from data warehouse; data mart, is visualised and summarised to provide multi-dimensional view of the subject. Popular OLAP tools are capable of rolling up the data. For example, product sales can be summarised by rolling up the data in product groups, then in families, by different dimensions, such as segment, market, and so on. OLAP provides information based intelligence. Business intelligence is based on knowledge from data mining processes, which are similar to OLAP, but these unearth the knowledge by finding patterns, trends, and behaviour of the subject providing an action. Besides OLAP kind of analysis, data mining uses techniques like memory based reasoning, link analysis, neural networks, and so on. OLAP records a view or a problem, while data mining helps to find the solution of the problem. For example, OLAP would reveal the customer class based on credit history and receivable performance while data mining would link it to knowledge whether the customer of the class is credit worthy, or the order should be rejected. There are a number of Data Warehouse applications which industry is using to get competitive business advantage. Some illustrations given here explain how top management uses Data Warehouse: • Cell phone industry analyses user call behaviour and evolve pricing strategies, discount schemes based on the pattern of call behaviour.

• National Stock Exchange (NSE) warehouse provides trade intelligence which discovers unknown trading patterns and unexplained price movement. This helps NSE in surveillance and other control functions. • RBI uses data warehouse to understand what influences money markets, and to study individual banks, their position in money market, and also to monitor changes in their position. This helps RBI to evolve more intelligent regulatory mechanism. • LIC has a data warehouse of millions of policyholders. The study helps them to analyse the business in terms of policyholders, their social status, duration of policies, popular policies, etc. This helps them to guide insurance agents about ways to concentrate an business. • Railways use passenger and freight data for strategic resource planning, attractive freight policy. On the basis of traffic pattern, railways are in a position to start holiday trains on selective routes. • Airlines analyse passenger data in terms of flight, destinations and in flight needs to offer fare discounts, and offer most liked beverages, meals and movies. • Consumer goods industry uses data warehouse for product movement, tracking and understanding cause and relationship between product, consumer and market segment to promote business in untapped market, and to get more market share in growth market. • Banks in credit card business offer variety of attractive schemes to card holders by analysing their buying pattern. This helps banks to increase their credit card business volume. • Entire service industry analyses customer data for ordering, delivery services demanded, etc., to organise internal resources to other quick responses to customer calls. It helps them to work out service strategy on three dimensions, price, delivery and response.

SEARCH ENGINES A web search engine is designed to search for information on the World Wide Web. The search results are usually presented in a list of results and are commonly called hits. The information may consist of web pages, images, information and other types of files. Some search engines also mine data available in databases or open directories. Search4i.com is another well known web search engine that acts as a rich resource of global information. Besides having distinct sections providing information on history, shopping, medicine, immigration, business services, social sciences, and so on, Search4i.com has a listing of featured websites that enable the user to have a quick look on sites of interest.

Directory.net Directory.net is dedicated to make their slogan—`Find what you need, when you need it’, a success. This search engine-cum-directory offers a vast category of subjects to make the search easier. The user can find anything related to arts, science, business, news, health, computers, games, sports, genealogy, shopping, society, sports and other important categories. There are two main types of search engines that have been evolved: one is a system of predefined and hierarchically ordered keywords that humans have programmed extensively. The other is a system that generates an ‘inverted index’ by analysing texts it locates. This second form relies much more heavily on the computer itself to do the bulk of the work. Most web search engines are commercial ventures supported by advertising revenue and, as a result, some employ the practice of allowing advertisers to pay money to have their listings ranked higher in search results.

A search engine operates in the following order: • Web crawling • Indexing • Searching Web search engines work by storing information about many web pages, which they retrieve from the html itself. These pages are retrieved by a web crawler, also known as a spider, an automated web browser which follows every link on the site. Exclusions can be made by the use of robots.txt. The contents of each page are then analysed to determine how it should be indexed, for example, words are extracted from the titles, headings, or special fields called meta tags. Data about web pages is stored in an index database for use in later queries. A query can be a single word. The purpose of an index is to allow information to be found as quickly as possible. The cached page always holds the actual search text since it was actually indexed, and hence so it can be very useful when the content of the current page has been updated and the search terms are no longer in it. When a user enters a query into a search engine, typically by using key words, the engine examines its index and provides a listing of best matching web pages according to its criteria, usually with a short summary containing the document’s title and sometimes parts of the text. The index is built from the information stored with the data and the method by which the information is indexed. Most search engines support the use of the Boolean operators, AND, OR and NOT, to further specify the search query. Boolean operators are for literal searches that allow the user to refine and extend the terms of the search. The engine looks for the words or phrases exactly as entered. Some search engines provide an advanced feature, called proximity search, which allows users to define the distance between keywords. The usefulness of a search engine depends on the relevance of the result set it gives back. While there may be millions of web pages that include a particular word or phrase, some pages may be more relevant, popular, or authoritative than others. Most search engines employ methods to rank the results to provide the best results first. How a search engine decides which pages are the best matches, and what order the results should be shown in, varies widely from one engine to another.

INTELLIGENT AGENTS An agent is anything that perceives its environment through sensors and acts upon that environment through actuators. Human being is an agent who perceives the environment through sensors, understands, interprets and acts to achieve a goal. Human being is an agent eyes, ears, and other organs are sensors and hands, legs, mouth, and other body parts are actuators (Figure 8.7).

Environment Sensory Input

Fig. 8.7

High Level View of an Agent

Actuator/ Effecter

Here human being is an intelligent agent. But, in KM, intelligent agent is a software programme built to act intelligently. An agent with ability to learn and adapt is autonomous if its behaviour is determined by its own experience. An intelligent agent (IA) is an autonomous entity which observes and acts upon an environment and directs its activity towards achieving goals. Intelligent agents may also learn or use knowledge to achieve their goals. They may be very simple or very complex, as is a human being, as is a community of human beings working together towards a goal. Intelligent agents are also closely related to software agents, an autonomous software programme that carries out tasks on behalf of users. The term intelligent agent is used to refer to a software agent that has some intelligence to perform to achieve a goal. Intelligent agent software may consist of embedded technology within the mobile device, servers on the Internet, and/or programmes within applications on/off the mobile network. Agent

Knowledge Database

Condition-action Rules

What the world is like now

What action I should do now

Environment

Sensors

Actuators

Fig. 8.8

Intelligent Agent Model

Agency scope of the IA is the degree of authority given to a programme, i.e., how much it is allowed to perform on its own accord, based on the instructions given by user. Intelligence is the degree of reasoning and independent learning enabled within the programme. A truly intelligent agent has the ability to adapt itself to its environment, sensing events and objects, evaluating circumstances and objects, and act over time in pursuit of a specific agenda and achieve specific goal.

Agent Environments Environments in which agents operate can be defined in different ways. It is helpful to view the following definitions as they refer to the way the environment appears from the point of view of the agent itself.

Observable vs Partially Observable In order for an agent to be considered an agent, some part of the environment—relevant to the action being considered—must be observable. In some cases (particularly in software) all of the environment would be observable by the agent. This, while useful to the agent, would generally only be true for relatively simple environments.

Deterministic vs Stochastic An environment that is fully deterministic is one in which the subsequent state of the environment is wholly dependent on the preceding state and the actions of the agent. If an element of interference or uncertainty occurs then the environment is stochastic.

280 280 Knowledge Knowledge Management Management

Episodic vs Sequential This refers to the task environment of the agent. A task environment is episodic if each task that the agent must perform does not rely upon past performance and would not affect future performance. Otherwise it is sequential.

Static vs Dynamic A static environment, as the name suggests, is one that does not change from one state to the next while the agent is considering its course of action. In other words, the only changes to the environment are those caused by the agent itself. A dynamic environment can change, and if an agent does not respond in a timely manner, this counts as a choice to do nothing.

Discrete vs Continuous This distinction refers to whether or not the environment is composed of a finite or infinite number of possible states. A discrete environment would have a finite number of possible states. However, if this number is extremely high, then it becomes virtually continuous from the agent’s perspective.

Single Agent vs. Multiple Agents Environment An environment is only considered multiple agents if the agent under consideration must act cooperatively or competitively with another agent to realise some tasks or achieve a goal. Otherwise, another agent is simply viewed as a stochastically behaving part of the environment. Intelligent agent technology provides a mechanism for information systems to act on behalf of their users. Specifically, intelligent agents can be programmed to search, acquire and store information on behalf of the wants and needs of the users. Intelligent agents are task oriented. Examples of intelligent agent tasks include data mining, profile management, privacy management, rules management and application management. Data mining agents seek data and information based on the profile of the user and instructions carried out by the rules manager agent. The profile management agent’s role is to maintain the user profile, constantly adding, deleting and modifying profile information based on new information. The privacy management agent’s role is to safeguard privacy of the user, including identity, location or other personal information. An application agent manages application(s) and interactions between the network, other networks, content and other applications.

Agent Attributes Agents possess following attributes in some mix, depending upon the environment they work upon: • Simple Reflex Agents • Model-based Reflects Agents • Goal-based Agents • Utility-based Agents • Learning Agents • Other Classes of Intelligent Agents

A simple agent programme can be defined mathematically as an agent function which maps every possible percepts sequence to a possible action the agent can perform, or to a coefficient, feedback element, function or constant that affects eventual actions. There are six classes of intelligent agents. Russell and Norvig put intelligent agents into six classes based on their degree of perceived intelligence and capability: • Simple reflex agents • Model based reflex agents • Goal based agents • Utility based agents • Iearning agents

Simple Reflex Agents Simple reflex agents act only on the basis of the current percept. The agent function is based on the conditionaction rule, ‘if condition then action’. This agent function only succeeds when the environment is fully observable (Figure 8.8).

Model Based Reflex Agents Model based reflex agent can handle partially observable environments. Its current state is stored inside the agent maintaining some kind of structure which describes the part of the world which cannot be seen. This behaviour requires information on how the world behaves and works. This additional information completes the ‘World View’ model. A model based reflex agent keeps track of the current state of the world using an internal model. It then chooses an action in the same way as the reflex agent. (Figure 8.9).

How the world evolves

Sensors What the world is like now

Environment

State

What my action do

Knowledge DB Condition-action rules

Agent

Fig. 8.9

What action I should do now Actuators

Model Based Reflex Agent

Goal Based Agents Goal based agents are model based which store information regarding situations that are desirable. This allows the agent to choose from among multiple possibilities of actions, an action which reaches the goal state (Figure 8.10).

282 Knowledge Management

Sensors

How the world evolved

What the world is like now

What my action do

What it will be like if I do actor A

Knowledge DB Goa Is

Agent

Fig. 8.10

Environment

State

What action I should do now Actuators

Goal Based Agents

Utility Based Agents Goal based agents only distinguish between goal states and non-goal states. It is possible to define a measure of how desirable a particular state is. This measure can be obtained through the use of a utility function which maps a state to a measure of the utility of the state (Figure 8.11). (source: swww.cs.berkley.edu/ Russel).

How the world evolved

What the world is like now

What my action do

What it will be like if I do action A

Utility

What happy will be in such a state

Knowledge DB Agent

Fig. 8.11

Sensors

Environment

State

What action I should do now Actuators

Utility Based Agents

A utility-based agent is similar to a goal-based agent but in addition to attempting to achieve a set of goals, the utility agent attempts to achieve utility value such as happiness of the agent or degree of success achieved or efforts put in achieving a set of goals.

Learning Agents Learning has an advantage that it allows the agents to initially operate in unknown environments and become more competent than its initial knowledge alone might allow (Figure 8.12). Performance standard

Sensors

Feedback Changes Learning Element Knowledge Learning Goals

What action I should do now

Environment

Critic

Problem Generator Agent

Fig. 8.12

Actuators

Learning Agents

Other Classes of Intelligent Agents • • • • •

Decision agents are geared to decision making Input agents process and make sense of sensor inputs Processing agents that solve a problem like speech recognition Spatial agents relate to the physical real world World agents that incorporate a combination of all the other classes of agents to allow autonomous behaviours • Believable agents exhibit a personality via the use of an artificial character (the agent is embedded) for the interaction • Physical agent is an entity which percepts through sensors and acts through actuators • Temporal agents may use time based stored information to offer instructions or data, acts to a computer programme or human being and takes programme inputs percepts to adjust its next behaviours In knowledge management, intelligent agents are designed and deployed for intelligent searches in database, knowledge base or other knowledge repositories to expedite the customer query resolution. The task IA should do needs to be programmed. IAs are software entities capable of performing wide range of activities, such as searching, comparing, learning, negotiating, and collaborating to achieve a goal. IA learns from own behaviour and from experience of previous situations. With knowledge bases all around, IAs can be designed and programmed to intelligent tasks, such as: • Customer profiling for market segmentation • Predicting customer requirements for product modifications

• Predicting customer behaviour and getting ready to respond • Customer assistance for decision making • Process selection for a new task never done before Intelligent agents are intelligent enough, limited by knowledge assistance available and act within the programmed scope of tasks. (Proceedings of the Americas Conference on Information Systems, New York, August 2004, Ira Rudowasky, Brooklyn College)

KNOWLEDGE PORTAL, KNOWLEDGE PRODUCTS The main objective of knowledge portal is to provide a single window service to knowledge seeker and user. It is a tool to deliver personalised service to the knowledge user. Knowledge Portal has following functionalities making it a powerful tool for KM: • Gathers knowledge in central repositories. • Provides categorisation to knowledge for ease of search and navigation. • Distributes the knowledge in structured form. • Capable of interfacing with other application needs through collaboration. It goes beyond the role of a single knowledge source. On identification, validation and creation, knowledge is stored in the organisation for use by knowledge workers. Knowledge can be stored in knowledge portal, knowledge data base, E-manual or documents dedicated for the purpose. The access to these mediums is given to the people in the organisation after considering all aspects of security and maintenance. Some have rights to use, some have rights to edit, and some have access to read only and so on. Functional view of a Knowledge Portal is given in Figure 8.13. Collaborate, Share and Author Knowledge • Subject Experts • Application Experts • User Experience Knowledge Engineer

State 1 Knowledge Create

Create Knowledge Assets

Web Publisher

Stage 2 Knowledge Portal: Assets

Knowledge Users

Fig. 8.13

Knowledge Element

Knowledge Assets: Documents, Manuals, Directories. Processes Guidelines, Policies

Functional View of Knowedge Portal

Application of Knolwledge Portal Three basic processes make knowledge portal efficent and effective for development and its usage for businress applications. The processes are:

• • • •

Cooperation and collaboration Search of information and knowledge Application support Cooperation and Collaboration The tools for cooperation and collaboration are formation of Virtual teams, Discussion forums, Community of Practices, Web conferences, Chat, Blogs, Workflow, Team calendar and Yellow pages. • Search of Information and Knowledge The tools for search are intelligent search, automated communication service, query search on knowledge database, E-mail integration, classification and categorisation, content management, organisation thesaurus, presentation of the delivery. • Application Enabling Tools These are project management, time management of experts, skill management of knowledge workers, link ups to ERP, and other business applications for providing knowledge input.

Process This process step includes number of things whereby identified knowledge elements turn out to be an ‘Asset’ to the organisation. Though experts and specialists identify knowledge, KMS must have a process to package these elements in proper user friendly mode. The packaging varies by type of knowledge and its most often, most likely use by knowledge workers. Let us take typical examples of knowledge assets which are common across the organisation in business and industry.

Instruction Manual These are developed by the organisation for multiple users for use in different problem solving requirements. The manual could be used while installing or implementing the system or plant and equipment. It could be useful when it is opened for routine or preventive maintenance. Such instruction manual contains technical knowledge details followed by Do and Don’ts’, procedural guidelines to open the equipment, things to observe, diagnostic routines, experienced guidelines to handle a problem revealed by diagnostic routines, etc. You will observe that at least four-five persons in the organisation contribute towards development of such manual. Each of them has some domain expertise and hence they are chosen to share their knowledge for development of this manual. Therefore, a process is needed to capture this knowledge, edit it for inclusion in the manual, organise it in user requirement mode and style and process it for presentation. Besides this processing work, additional process is required to create index, cross reference index, glossary of terms and vendor website reference for seeking on the spot data and information. Special attention is required towards language, sequence of contents, figures, diagrams and drawings. And last, but not least important, is the last minute contact persons references to seek online help in crisis management.

Help Desk Help desk is an interactive platform where problem solution is obtained by exchanging information and seeking guidance to resolve it. The person at the help desk has access to information about the customer and the problem when it is stated by the customer. The help desk person has access to backend databases and knowledge bases to solicit the assistance to resolve the problem. This person gives instructions regarding the action and the respondent implements and communicates the result. This interactive process continues till the problem is resolved.

Knowledge Database/Knowledge Portals These are dedicated knowledge repositories for help in the organisation. They are built over a period based on the needs of the people in the organisation. Knowledge portal is a powerful tool to share information and knowledge for support in the exercise of resolving something. Knowledge portals or databases could be exclusively of three types: • Information and knowledge portal to share • Application portal providing application knowledge • Problem and solution portal supported by search engine.

Enterprise Information Portals A web portal presents information from diverse sources in a unified way. Apart from providing information, web portals offer other services, such as e-mail, news, stock prices, infotainment, and other features. Portals provide a way for enterprises to provide a consistent look and feel with access control and procedures for multiple applications, which otherwise would have been different entities altogether. Two broad categorisations of portals are Horizontal Portals (e.g. Yahoo, Google) and Vertical Portals (or Vortals, focused on one functional area, e.g. salesforce.com). A web portal can be integrated with many systems of the organisation. It is designed to use distributed applications, different numbers and types of middleware and hardware to provide services from a number of different sources. Business portals are designed to share information and knowledge to support collaboration in workplaces. A further business driven requirement of portals is that the content be able to work on multiple platforms, such as personal computers, personal digital assistants (PDAs), and cell phones/mobile phones. In addition, most portal solutions, if designed correctly, can allow internal and external access to specific corporate information using secure authentication or single sing-on. Enterprise Information Portals are applications that enable organisations to release internally and externally stored information, and provide users a single gateway to personalised enterprise information needed to make informed business decisions. The benefit of enterprise portal is its ‘competitive advantage’ derived from providing access to distributed information stored in enterprise systems. Information access to all is convenient, reliable, and its delivery is inexpensive. Portals increase employee productivity as less time is spent searching the web because information is organized and available at one place. Their effectiveness is also increased due to fast information driven decision making.

Corporate Web Portals Corporate portals, besides displaying their profile, offer new value-added capabilities for businesses. Capabilities, such as managing workflows, increasing collaboration between work groups, and allowing content creators to self-publish their information, are added. Web portals are also designed to perform E-commerce, E-business transactions. As web portals have risen in popularity their feature set has grown to include hosted databases, document management, email, discussion forums, and more.

Domain Portals A number of portals have come about that are specific to the particular domain, focusing on domain information content. They also offer links to related companies and services. A prime example of this trend would be the growth in property portals that give access to services such as estate agents and removal firm, and solicitors that offer legal and document registration services. Along the same lines, industry specific news and information portals have appeared.

The global economy is currently undergoing a fundamental transformation. Market dynamics and business rules are changing at an ever increasing speed. The business management processes are now knowledge driven. The need is for high quality knowledge, sourced from inside and outside the organisation and stored at one location. The work culture is becoming more collaborative team work, pooling expertise from within and outside the organisation. Knowledge portals represent a solution to this challenge, as they provide a flexible knowledge environment to a potentially large number of users. The mission of a knowledge portal is not only to provide a library like pool of information, but to actively support the user in execution of business processes. Lew Platt of Hewlett Packard takes the view that “successful companies in the 21st century will be those who do the best job in capturing, storing, and leveraging what their employees know”. Knowledge portals are a web based solution for closing this gap. Currently, organisations rely on a set of diverse tools to meet their needs for a corporate portal, a document management system, and an aggregate search solution. SharePoint Portal Server is a flexible portal solution for knowledge workers to easily find, share, and publish information and explicit knowledge.

Knowledge Portals (KP) Architecture and Technology KP needs process service oriented technology platform to meet the users’ requirements. These requirements are three-fold: • Access to static organisation information about the business, products, different offerings, and important links to alliance partners, process manuals, brochures etc. • Knowledge created and stored in knowledge database about problems and solutions, case studies, templates and models, technical problem solving information, and links to other knowledge portals. • Functionality to conduct business transactions like ordering, tracking, billing, payment and support, and so on. Knowledge portals need to be flexible and easy to use and should provide almost any kind of content or functionality the user needs. To structure the architecture of a knowledge portal, the following five layer component model is being used (Figure 8.14). User Interfaces for Access and Navigation

Personalisation Process

Team Work

Document Mgt

Function Execution and Management

Subject Content, Information, Knowledge

Fig. 8.14

Access Layer

Personalisation Layer Support and Service Layer Execution Layer Data Layer

Architecture of Knowledge Portal

• Database Layer: Subject Content, Information, Knowledge • Subject content provides focused specific information on a topic of interest of the user. This information brings clarity to the user on the subject before any action is taken.

• Specific information used directly in the process invoked by the user. • Contains problem specific knowledge to resolve it. • Personalisation Layer This is for the user’s personal support. It includes services like Do list, directory, schedules, user manager for task management, history or personal notes, etc. • Support and Service Layer • Process Support Check lists, templates, process diagram PM tools, process application links. • Team Work Planning tools, message boards, e-mail, conferencing, expert profiles, community groups, conferencing and discussion facilitation. • Document Management Access and subscription, search and selection, editing, content sharing, content rating. • Execution Layer Processes to access database and seek support from support layer to execute a requirement: Query, downloading, process execution, verification, sharing and display of process output. • Access Layer It is a user interface and navigation layer. It should be user friendly and simple to operate. The general well accepted standards of user interface design should be followed. Web portals, information or knowledge portals have become an integral part of MIS of the organisation. They are used to share information and are a platform for transacting business with vendors and customers.

Knowledge Products They are a products built on data, information and knowledge inputs. All software products are knowledge products. For example, core banking product is a knowledge product developed to manage bank processes where account holders, branch managers, employees at the customer counters are users of this product. Knowledge product considers domain knowledge of banking industry, government and RBI rules and regulations, and best practices in executing hundreds of banking processes. The product so developed is generic and can be modified to suite specific local conditions of a typical bank. Knowledge products have flexible design so that they can be customised to customer requirements. All ERP, CRM, SCM packages are knowledge products designed and developed to manage organisation’s resources efficiently and effectively. The products mentioned here are designed for use in public domain. But, the same concept can be applied in developing knowledge products for internal purpose in private domain. Organisations develop spread sheet models, templates, system models, charts, and diagrams for use in the organisation. Such product usage saves time, brings approach consistency in solving the problem and communication on the subject matter is easy and clear to all concerned. E-learning products are knowledge products. Organisations develop these products using web, animation, Adobe Flash and XML engine gaming technologies, presentation tools for making the knowledge product a superior learning tool. The organisations recruit new employees who need induction, acclimatisation, subject training, product training, and awareness about the organisation’s business philosophy, values, and so on. Whether the number of new employees is small or large, this input to new employees is necessary. Organisations develop e-learning products and employees are told to use these products posted on the portal or the intranet.

GROUPWARE TECHNOLOGY FOR KNOWLEDGE TRANSFER Transfer is the process developed to move knowledge from development centre to work centre, or work place, where it is extensively used for application. The transfer process operates on network for movement and is used by network of knowledge workers. Having reached the knowledge at work centre, the process of sharing knowledge amongst its users takes over. The sharing of knowledge is achieved by following processes: • Conferencing • Direct access to repository • One-to-one interaction for learning and application • Handholding • Group meetings • Collaborative working In this list of processes, collaborative working needs further elaboration. In a network environment, Groupware is an enabling technology for collaborative working. Its focus is on helping knowledge workers share their expertise, skills with others in expediting the work flow or task. Groupware products like Lotus Notes devoted exclusively for this requirement. There are also web conferencing tools, such as Caucus and O’Reilley’ WebBoard. Groupware technology is powerful because of the following features: • Ability to handle multiple data types: any form of text, graphs, images, voice and video • E-mail and bulletin board combination • Messages are displayed in its order occurrence in the form of ‘Message and Reply’ in sequential order • Ability to move from one record type to other and coming back to original status • Announcement or communication about conferences or group meetings (public or private) directly or through central authority • Provides access to external information and knowledge • The technology is scalable in terms of group size The key to a successful groupware implementation, through products or intranet, is good content, good information and knowledge architecture and efficient information management. Groupware technology creates purposeful networks of people and knowledge centre. It overcomes limitation of location or geographical constraints. It provides access to information and knowledge repositories anytime, anywhere outside the formally defined group or team. Its benefit is highest because of virtual meeting possibility at times and places of their choosing. In short, Groupware Technology‘s capability of offering ‘collaborative services’ has many applications which can be termed under ‘transfer and share’ process of KMS. The capability provides ability to handle various steps in knowledge work, knowledge management and knowledge application. The typical high value applications are: • Ability to supervise, monitor, track the work of the group members. The members can share new developments, revelations, and key results just in time of their occurrence. • Strengthens the ability of group member to improvise tasks because of easy access to knowledge repository of best practices supported by case studies and illustrations.

• Improvement in design capabilities of group members because of they being the member of network or communities from different design organisations who share latest in design and engineering, creative and innovative ideas. • Improvement in customer services is expeditious because issues, requests, queries, complaints, modifications are addressed efficiently and effectively to customer satisfaction. The entire CRM application uses Collaborative Groupware Technology. While we are discussing groupware technology and its application, the underlying assumption is that there is a group or a team formally established with specific goal to achieve. This is largely true if the members are from the same organisation. But there is another form of group called Community of Practice (CoP) which, in principle, is different as compared to work group or team but uses groupware technology. The CoP comes into place because of common interest in a body of knowledge, motivated by common values and willingness to have a shared identity. Following table differentiates the difference between work Group and Team and CoP.

• • • • • • •

Particulars

CoP

Work Group/Team

Goal Membership Work culture Output Mgt style Process cycle Time to achieve

Unspecified and evolving On initiative, voluntary Not organised Not well defined Self managed Undefined Indefinite

Definite and well specified By authority, role demanding Governed by process design Defined, specified, measurable Mgt. by roles and rules Well defined Defined and controlled

Groupware technology essentially is a tool for performing collaborative activity. In the context of KM, it provides capability to people to work together in a coordinated manner to achieve a common goal. This collaboration could be synchronous or asynchronous. In synchronous collaboration, the partners work together in real time instantaneous mode. In asynchronous collaboration, partners collaborate without such time constraints. It can happen in stages on a time scale.

End Notes • ICT is defined as set of technologies and tools used to communicate, and to create, disseminate, store, and manage information and knowledge. These technologies include computers, networks, the internet, web radio, and television, mobile devices cameras and digital technology in general. • Information and Communication Technologies (ICT), with its proven capabilities, has been potentially considered a powerful enabling technology for knowledge management. • The limited experience of making KM ICT enabled reveals that the full realisation of its potential is not possible automatically. The ICTs need to be integrated in an overall KM system giving regard to organisational readiness, employee competencies and knowledge strategy. • The key to effective knowledge transfer, sharing and application is whether the delivery of knowledge is in Learner (Employee) centric environment. Learner centric environment is described by learner’s current level of knowledge, digital literacy, attitudes and beliefs, and access to ICT platform. • The full realisation of ICT capabilities is possible through effective integration of ICT in the KM system, institutional readiness, expert’s knowledge competencies, employee focused KM design.

• Unified communications technologies improve efficiency and effectiveness of supply chains by enabling stakeholders to collaborate located anywhere in different time zones. With integrated UC capabilities into business processes, employees can quickly and easily find the right person and communicate from within the software applications and business processes currently in use. • Unified communications (UC) systems bring together voice, video, data, and mobile applications in business to improve business competitiveness and profitability. Such integration of different communication technologies liberates employees from their desks and desktops, adding speed into decision and action raising HR productivity. • Unified communications technologies bridge the divide between computers and telephones with two integrated servers: Exchange Server and Communications Server. They integrated in organisation’s existing phone system and deliver complete communications services using existing data network. Unified communications technologies maximise existing infrastructure by integrating legacy PBX systems through a VoIP/IP-PBX gateway. • The goal of Communication Enabled Business Process (CEBP) is to optimise business process by reducing the human latency that exists within a process flow. UC enabled business dprocess automates human side or aspect of the process execution. That is, recognising the problem, seeking information, analysing and resolving to put the process on hold back to track. • WiMAX, meaning Worldwide Interoperability for Microwave Access, is a telecommunications technology that provides wireless transmission of data using a variety of transmission modes, from point-to-point links to portable internet access. The technology provides upto 75 Mb/s symmetric broadband speeds without the need for cables. • Speed and reach are the biggest advantages WiMAX offers to the users.The potential capability can be used to build networks covering remote areas for communication, information sharing, spreading knowledge, and for e-learning. • The Data Warehouse is defined by Bill Inmon as “A collection of non-volatile data of different business subjects and objects, which is time variant and integrated down various sources and applications and stored in a manner to make a quick analysis of business situation”. • DW is a special database containing large stocks of enterprise data and related meta data processed to a ‘ready to use’ stage for decision maker for operational and analytical business analysis. • The Data Warehouse normally is justified in competitive business environment. The businesses, which are driven by customer expectations, justify investment in Data Warehouse. All service industries where customer satisfaction is a critical success factor, work with Data Warehouse to evolve different service strategies to please the customer. • Data Warehouse is an information asset for the top management. Most of the Data Warehouse is of large size, storing business data for strategic use and multi-dimensional views. The query and reporting systems help to know the status of any business subject. OLAP systems provide multidimensional analysis of any business subject. • Data mining tools help to unearth underlying patterns in the business and factors influencing these patterns. Data mining solution provides capability to build prediction model. It helps to discover association and sequential patterns in the business data. For example, through a data mining application we can discuss a pattern of sales linked to time and some influencing factor. It is not possible to see such a pattern unless we visualise the possibility and mine the business data from warehouse and test their association.

• Business intelligence involves the integration of core information with relevant contextual information to detect significant events and bring clarity to cloudy issues. It includes the ability to monitor business trends, to evolve and adapt quickly as situations change and to make intelligent business decisions. It relies on exploration and analysis of unrelated information to provide knowledge through relevant insights, identify trends, discover opportunities, take proactive decisions and create value. • Business Intelligence (BI) is all about converting a large amount of corporate data, through processing and analysis, into useful information and knowledge, thereby triggering some profitable proactive business action or decision. Business intelligence environment is made up of business models, data models, extraction, and transformation and loading tools (ETL Tools) needed to transform and organise the data into useful information and knowledge for storage and further analysis. • OLAP, an acronym for ‘Online Analytical Processing’, is a technique by which the data sourced from data warehouse, data mart, is visualised and summarised to provide multi-dimensional view of the subject. Popular OLAP tools are capable of rolling up the data. • A web search engine is designed to search for information on the World Wide Web. The search results are usually presented in a list of results, and are commonly called hits. The information may consist of web pages, images, information and other types of files. Some search engines also mine data available in databases or open directories. • An intelligent agent is anything that perceives its environment through sensors and acts upon that environment through actuators. Human being is an agent who perceives the environment through sensors, understands, interprets and acts to achieve a goal. Human being is an agent, eyes, ears, and other organs are sensors, and hands, legs, mouth, and other body parts are actuators. • An intelligent agent (IA) is an autonomous entity which observes and acts upon an environment and directs its activity towards achieving goals. Intelligent agents may also learn or use knowledge to achieve their goals. They may be very simple or very complex, as is a human being, as is a community of human beings working together towards a goal. • The main objective of knowledge portal is to provide a single window service to knowledge seeker and user. It is a tool to deliver personalised service to the knowledge user. • Corporate portals, besides displaying their profile, are offering new value added capabilities for businesses. Capabilities, such as managing workflows, increasing collaboration between work groups, and allowing content creators to self publish their information, are added. Web portals are also designed to perform E-commerce, E-business transactions. • The knowledge products have flexible designs so that they can be customised to customer requirements. All ERP, CRM, SCM packages are knowledge products, designed and developed to manage organisation’s resources efficiently and effectively. • The key to a successful groupware implementation, through products or intranet, is good content, good information and knowledge architecture and efficient information management. Groupware technology creates purposeful networks of people and knowledge centre. It overcomes limitation of location or geographical constraints. • Groupware technology‘s capability of offering ‘collaborative services’ has many applications which can be termed under ‘transfer and share’ process of KMS. The capability provides ability to handle various steps in knowledge work, knowledge management and knowledge application.

• Groupware technology essentially is a tool for performing collaborative activity. In the context of KM, it provides capability to people to work together in coordinated manner to achieved common goal. This collaboration could be synchronous or asynchronous. In synchronous collaboration, the partners work together in real time instantaneous mode. In asynchronous collaboration, partners collaborate without such time constraints. It can happen in stages on a time scale.

Questions 1. The potential capabilities of ICT are: • Delivery anywhere • Presentation in any form • Demonstration in multi-media • Experimentation to test hypothesis • Interactive, collaborative through networks for knowledge exchange and sharing • Manipulation and creation of new formations of knowledge and its products • Seamless communication of knowledge in any format • Restrictive as well as open Identify the situations where these technologies can be used. 2. Explain the difference between e-learning, blended learning, and distance learning. 3. The full realisation of ICT capabilities is possible through effective integration of ICT in the KM System, institutional readiness, expert’s knowledge competencies, employee focused KM design. Explain how ICT can be integrated in KM system. 4. Explain how UCT can be used in following situations to improve the efficiency of operations. • Project office and project site interactions and exchange of documents • In logistics management 5. Explain the role of database, data warehouse and data mart in KMS. 6. Explain the meaning of agent and Intelligent agent. Identify how knowledge can be used in developing IA in following situations. • Retail store • Machine shop • Assembly line 7. What is a knowledge portal? How can it be used as a learning tool and a business processing tool? 8. Are you using any knowledge products in your organisation? Can you separate knowledge component and application component in the knowledge product? What advantages you do see in using knowledge products? 9. In synchronous collaboration, the partners work together in real time instantaneous mode. In asynchronous collaboration, partners collaborate without such time constraints. It can happen in stages on a time scale. Identify two cases where Groupware technology can be used in synchronous and asynchronous collaboration.

10. Identify from your environment following agents in use, or can be so used. • Decision agents: are geared to decision making • Input agents: process and make sense of sensor inputs • Processing agents: solve a problem like speech recognition • World Agents: incorporate a combination of all the other classes of agents to allow autonomous behaviours • Physical agents: an entity which percepts through sensors and acts through actuators • Temporal agents: may use time based stored information to offer instructions or data acts to a computer programme or human being and take programme inputs percepts to adjust its next behaviours.

9 Chapter

Case Illustrations of Knowledge Management

This Chapter Deals with • • • • • • • •

Data Warehousing and Data Mining Knowledge Portal Knowledge Products Intelligent Agents Groupware Technology Unified Communication Technology Solutions Business Case for Knowledge Management KMS Applications

Learning Outcome This chapter is devoted to give exposure to knowledge and how knowledge, and KMS are used by business and industry in forging their competitiveness. Through cases and examples key concepts of KM are understood. It helps to learn how technology is an enabler to make KM initiative a success.

s

“Successful companies in the 21st century would be those who do the best job in capturing, storing, and leveraging what their employees know”. Knowledge Portals are a web based solution for closing this gap.” —Lew Platt of Hewlett Packard

One approach to knowledge management places greater emphasis on the cultural and behavioural aspects of the organisation. This approach believes that organisations are process driven and technology is of little use if the organisation lacks knowledge-sharing culture. This approach is influenced by the management disciplines of total quality management, business process re-engineering, system engineering, optimisation techniques, benchmarking and best practices. Considerable input is taken from behavioural sciences and psychology. The other approach to knowledge management is more aided by technology which includes internet, network, and communication, database management, information systems, information technology, embedded technology and host of others. It relies on technology and technology tools and products. It concentrates on providing efficient tools to capture, organise and access knowledge as well as to facilitate its delivery to the right people at the right time. This chapter deals with all such important technologies and tools. The tools used for knowledge capture include the existing groupware applications like Lotus Notes, which facilitate collaborative working in a group. Document management software that helps index images of paper documents as well as to read them using optical character recognition technology also falls in the same category. The KM tools and technology suit contains, among others, tools to create a database of experts in the organisation and documents associated with them. When it comes to presentation of results of knowledge access, the KM tool set uses web technology to build knowledge portals for personalised access through the ubiquitous browser interface. Search engines, intelligent agents, data mining, data analytics and business intelligence are few other tools extensively used in knowledge management. KM technology is not a single solution but a group of tools based on groupware, expert systems, artificial intelligence, library science, document management, web, and so on. Notwithstanding this, KM tools are still a major step forward in our ability to manage the information glut. KM technology provides a mandatory knowledge management infrastructure to our businesses.

DATA WAREHOUSING AND DATA MINING Dramatic advances in data capture, processing power, data transmission, and storage capabilities are enabling organisations to integrate their various databases into data warehouses. Data warehousing is defined as the cess of centralised data management and retrieval. Data warehousing represents an ideal vision of maintaining a central repository of all organisational data. Centralisation of data is needed to maximise user access and

KEY TERMS • Data Mining • Portal, Enterprise Portal • Intelligent Agent • Business Case for KM • Sense and Respond • UCT

analysis. Dramatic technological advances in data analysis software are allowing users to access this data freely. The data analysis software is what supports data mining. Data mining, sometimes called knowledge discovery, is the process of analysing data from different perspectives and summarising it into useful information—information that can be used in DSS to increase revenue, cuts costs, or both. Data mining software is an analytical tool for analysing business data. It allows users to analyse data from many different dimensions or angles, categorise it, and summarise the relationships identified. Such analysis offers new perspective to the users about the business. Technically, data mining is the process of finding correlations or patterns among dosens of fields in large relational databases. New findings about correlations or patterns is a ‘kowledge’ revealing something new which otherwise may not be apparent. For example, summary information on retail supermarket sales can be analysed in light of promotional efforts to provide knowledge of consumer buying behaviour. Thus, a manufacturer or retailer could determine which items are most susceptible to promotional efforts. For example, one grocery chain used the data mining software to analyse local buying patterns. The patterns observed were: • Bread and butter are bought together • Soft drink sale is more on Friday and week ends • Green leaf vegetables are not preferred by lady customers • New campaign on certain new stock items has gone unnoticed • Billing between 1 pm to 3 pm is very low What can data mining do? Data mining is primarily used today by companies with a strong consumer focus—retail, financial, communication, and marketing organisations. It enables these companies to determine relationships among internal factors, such as price, product positioning, or staff skills, and external factors, such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction and corporate profits. Finally, it enables them to drill down into summary information to view detail transactional data. How does data mining work? Data mining provides the link between the transaction processing systems and other analytical systems. Data mining software analyses relationships and patterns in stored transaction data based on open ended user queries. Several types of analytical software are available: statistical, machine learning and neural networks. Generally, four types of relationships are prevalent: Classes Stored data is used to locate data in predetermined groups. For example, a restaurant chain could mine customer purchase data to determine when customers visit and what they typically order. This information could be used to increase traffic by having daily specials. The customers are put into classes: Time vs items ordered. Clusters Data items are grouped according to logical relationships or consumer preferences. For example, data can be mined to identify market segments or consumer affinities. The shopping cart data is analysed to search buying choices by group of items selected by customers. It reveals strong bias towards group of items in a particular segment. Associations Data can be mined to identify associations. Customers buy items in pairs as if they are packed together. A simple example is eggs – bread – ketchup. Sequential Patterns Data is mined to anticipate behaviour patterns and trends. For example, an outdoor equipment retailer could predict the likelihood of a backpack being purchased based on a consumer’s purchase

of sleeping bags and hiking shoes. Another example is that auto music accessories and equipments are sold as a consequence of auto sales. These sales lag behind the main item sales. Data mining consists of five major elements: • Extract, transform and load transaction data onto the data warehouse system. • Store and manage data in a multidimensional database system. • Provide data access to business analysts and information technology professionals. • Analyse data by application software. • Present data in a useful format, such as a graph or table. Different levels of analysis of data are available. The most widely used analysis are Decision trees, Rule Induction, and Data visualisation.

Decision Trees Tree shaped structures that represent sets of decisions. These decisions generate rules for the classification of a dataset. Specific decision tree methods include Classification and Regression Trees (CART) and Chi Square Automatic Interaction Detection (CHAID). CART and CHAID are decision tree techniques used for classification of a dataset. The decision tree model is a tool to predict the chance of the next event or action up coming if a specific state is reached. They provide a set of rules that can be applied to a new (unclassified) dataset to predict which records would have a given outcome.

Rule Induction The extraction of useful ‘if-then’ rules from data based on statistical significance. This analysis reveals a very close relationship between a condition and the most likely rule to overcome the condition.

Data Visualisation The visual interpretation of complex relationships in multidimensional data. Graphics tools are used to illustrate data relationships. (Source:www.anderson.ucla.edu/faculty/jason.../datamining.htm) Some successful application areas of data warehouse and mining include: • A pharmaceutical company can analyse its recent sales force activity and their results to improve targeting of high value physicians and determine which marketing activities would have the greatest impact in the next few months. • The results can be distributed to the sales force via a wide area network that enables the representatives to review the recommendations from the perspective of key attributes. • A credit card company can leverage its vast warehouse of customer transaction data to identify customers most likely to be interested in a new credit product. The customers can be cross checked for verification of unusual transaction just registered in the credit card account. • A real estate construction company with a large direct sales force can apply data mining to identify the best prospects for its offers in a new building complex. Using data mining to analyse its own customer experience, this company can build a unique segmentation identifying the attributes of high value prospects. • A large consumer durable goods company can apply data mining to improve its sales process to retailers to stock and promote new designs. Data from consumer panels, shipments, and competitor activity can be applied to understand the reasons for brand preferences and product switching. The

company can use the analysis for designing promotional campaign strategies that best reach their target customer segments. • With the Railway Application Package System running on IBM technology, Konkan Railway has significantly improved its ability to analyse, maintain and present passenger and train data, helping to reduce the likelihood of passenger delays and cultivating better decision making. Additionally, by automating the light switching at stations with train arrival-departures, the system has helped cut such energy costs by approximately 20 percent—Vijay Devnath, Chief Manager (IT), Konkan Railway. • Data mining can also be helpful to human resources departments in identifying the characteristics of their most successful employees. Information obtained, such as universities attended by highly successful employees, can help HR focus recruiting efforts accordingly. The competency mapping is more objective exercise for selection and positioning of a new employee. • Today’s grocery retailers face an increasingly competitive marketplace, where shopper loyalty to store is difficult to earn and even harder to protect. Competition from mega stores and convenience ‘Kirana’ stores on corners threaten their market share. Rising costs and difficult economic environment put pressure on prices and profits. Shoppers demand better value, excellent service and a convenient shopping experience. The consumer advocacy and loyalty can be ensured to a great extent by: • Providing best possible shopping experience • Delivering excellent customer service, leveraged on technology • Speeding up checkout process by evolving self service choices for consumers • Optimising your supply chain with the right products and promotions Taking an integrated approach to store technology can lower costs, provide scalability to grow and the ability to respond quickly to new business initiatives and opportunities. (Source: IBM Grocery Solutions)

KNOWLEDGE PORTAL Lew Platt of Hewlett Packard takes the view that “successful companies in the 21st century would be those who do the best job in capturing, storing, and leveraging what their employees know”. Knowledge Portals are a web based solution for closing this gap”. Currently, organisations rely on a set of diverse tools to meet their needs for a corporate portal, a document management system and an aggregate search solution. SharePoint Portal Server is a flexible portal solution for knowledge workers to easily find, share, and publish information. The need is for high quality knowledge, sourced from inside and outside the organisation and stored at one location. The work culture is becoming more collaborative team work, pooling expertise from within and outside the organisation. Knowledge Portals represent a solution to this challenge, as they provide a flexible knowledge environment to a potentially large number of users. The mission of a Knowledge Portal is not only to provide a library like pool of information, but to actively support the user in execution of business processes. Function view of a knoledge portal is given in Figure 9.1.

India Water Portal India Water Portal is a web based interactive platform for sharing water management knowledge amongst practitioners and the general public. The portal is an initiative of Arghyam, a foundation set up by Rohini Nilekani to promote sustainability efforts in water sector. The thought of a knowledge repository for the water

• Subject Experts • Application Experts • User Experts

Create

Create Knowledge Knowledge Engineer Assets Web Publisher

Stage 1 Knowledge

Stage 2 Knowledge Portal: Assets

Knowledge Elements

Knowledge Assets: Documents Manuals Directories Processes Procedures Guidelines Policies

Knowledge User

Fig. 9.1

Functional View of a Knowledge Portal

sector in India was felt at the first Arghyam conference held in February 2005. Endorsed by the National Knowledge Commission, the portal took shape in two years and was finally launched in February 2007. Features The portal covers topics closely related to the challenges in the water sector in India and the practical solutions for day-to-day water related problems faced in the country. The topics broadly covered in the portal include rainwater harvesting, agriculture, drinking water, urban water management, sanitation, wastewater management and water quality. For researchers in the sector, the portal offers a wealth of information and data in the field of water sector. The portal has meteorological data of India for over hundred years. Users can download the data based on the following parameters: • Precipitation • Minimum temperature • Average temperature • Maximum temperature • Cloud cover • Vapour pressure • Wet day frequency • Diurnal temperature range • Ground frost frequency • Reference crop evapotranspiration • Potential evapotranspiration The portal also has comprehensive data on the river basins of India, and the water policies and laws in India. There is a dedicated section on maps and statistics. The portal provides a free public service to cater to the needs of citisens. The questions are answered by an eminent team of water experts. The India Water Portal blog serves as a place for healthy discussion, and is also a mirror to the latest conferences/research papers/ jobs in the sector.

Accenture Is a global management consulting, technology services and outsourcing company. Committed to delivering innovation, the company collaborates with clients to help them become high performance businesses. Accenture needed to simplify access, improve search, and streamline content management for its consultants. Accenture Knowledge Exchange, a portal, is a corporate portal for publishing and sharing information and knowledge to authorised users.

B.E.A Systems Inc. The company manufactures sensors and door building products relating doors and windows. BEA Systems, Inc ensured that its worldwide sales force had ready access to all its internal tools, customer information and most current company and product information on design, quality, recommendations, and so on. BEA deployed a knowledge management portal, known as Knowledge Express,on a service oriented architecture, SOA. It is built on BEA WebLogic Platform.

Wipro Technologies It is a global information technology company offering world class solutions to its customers. Wipro needed a way to collate the knowledge gained by its employees so that other employees could access this information easily. Wipro wanted to provide a unified repository of various knowledge artifacts to its sales, marketing and technical personnel. Knowledge Management Portal saves time and money, improves productivity of developers, designers, and consultants at Wipro .

Microsoft Knowledge Portals These portals are more important to organisations today than ever before. More than 120,000 employees, contractors, and vendors at Microsoft create an increasing amount of digital information that pertains to their job responsibilities. Employees access much of this information through the Microsoft primary knowledge portal.

ICICI Bank It is a combination of information and knowledge portal offering online services to customers. The portal provides information on services offered by the bank and how to avail them. The portal provides total support on all queries, news and alerts, forms, information on different products, and so on.

Institute of Chartered Accountants of India Its knowledge portal, www.pdicai.org provides information and knowledge on opportunities, new circulars, news, judgment’s, forum for QandA, reckoner, tax information and guidance. Web portals, information or knowledge portals have become an integral part of MIS of the organisation. They are used to share information, and are platform for transacting business with vendors and customers.

Knowledge Portal at Cisco by John Schneble Cisco wanted to rapidly grow their new Service and Support Advocacy Group, from 20 to 120 people. To accomplish that goal, Cisco needed a way to capture and share the expertise of its more experienced service and support managers. Because this was a new group, training and ongoing support resources were limited. Although Cisco’s corporate intranet contained a portion of the needed resources, the time and effort required by new hires to locate them was costly. Cisco and their partner, VisionCor, designed, developed, and deployed a knowledge portal that provides service and support managers with a single source for learning, performance support and ongoing knowledge sharing needs.

The Business Objective With the goal of hiring 250 service and support managers in a period of 18 months, Cisco needed a comprehensive knowledge management solution that provided new service and support managers (SSMs) with immediate access to crucial resources as well as orientation and reference information. Fast access to this information would help reduce the time to proficiency in Cisco’s fast paced work environment. Cisco also needed to leverage the expertise of its experienced SSMs by capturing and sharing their knowledge. Vital to SSMs’ success was user friendly access to this information. The three key objectives of the new initiative were: • Minimise time-to-proficiency, orient new SSMs within 90 days of hire date by providing just enough of the right information about Cisco, its customer advocacy organisation, and the SSM role, in order for SSMs to become productive as soon as possible. • Maximise performance and sharing of knowledge assets. Provide information specific to the SSM role, such as best practices of how other SSMs handled certain customer situations, goal setting and advice on when and how to engage other departments within Cisco. • Foster ongoing learning and communication. Within Cisco’s geographically dispersed work environment, develop a communication vehicle for sharing information and experiences with other team members. This initiative of Cisco helped the specific requirement of educating 250 service support managers but also created an asset, a knowledge portal on customer and product servicing. Cisco achieved all the three business objectives.

The Portal Solution Because Cisco is an internet centered company, a web based resource was essential. Rather than build the resource itself, the company looked to a partner to speed the development process. Senior manager, Todd Griffin, wanted a partner with experience in researching, analysing, and organising complex environments. “There are plenty of Internet consulting firms out there, but we needed a partner with real knowledge management expertise and a proven methodology,” says Griffin. Enter VisionCor’s Integrated Knowledge Architecture (IKA), which is an object oriented approach to organising content, based on how the content is used. IKA provides a guide for organising information, learning and knowledge into smaller pieces, called knowledge objects, and building meaningful relationships between those objects. As a result, the end user can locate the critical information needed to improve productivity and performance more quickly and easily. IKA is technology neutral and can be used to leverage the capabilities of most major portal or knowledge management platforms. According to Griffin, “VisionCor understands how to determine what information to gather or build, and how to organise the information so it is useful.” To build Cisco’s solution, VisionCor assigned a team of consultants that included expert content developers, information architects and a project manager. The project plan was developed based on VisionCor’s development methodology in conjunction with its IKA methodology. The high level steps were: • Define the site’s purpose • Define the site’s content • Classify and organise the content • Identify and develop knowledge objects

• Define the site’s organisational and navigational schemes • Create a site maintenance plan • Create and rapidly deploy a prototype • Validate the site design by conducting a usability test • Make necessary changes based on the usability test • Continue to maintain, cultivate, and migrate knowledge • Conduct periodic value add measurements to ensure continued effectiveness Status reports, project schedules and conference calls kept the VisionCor team in Charlotte in synch with the Cisco teams in Chicago, New York, San Jose, California and Research Triangle Park, North Carolina. After a complete project and role analysis, the project was divided into four distinct phases. Phase 1: Quick Hits. With new hires already in place and looking for direction, there was an immediate need for a 90-day new hire roadmap. Because the initial portal would be text based, including rich detail and context was vital. Through interviews with existing SSMs and managers, the VisionCor team gathered, analysed, and organised the events and tasks required for a new SSM. The project sponsor and business leads helped select the best people to interview. A mix of new hires and experienced SSMs were consulted to determine the most useful and valuable information to include. However, any SSM who would use the portal was welcome to participate. To minimise the burden on people to contribute to the knowledge portal, interviewers maintained a reporter type position to solicit content and ensure consistent writing and formating, which varied based on the content type. Within 45 days, the most important new hire information was made available on a text based Website. Phase 2: Initial Development. Because the SSM role was a new and highly strategic one within Cisco, the VisionCor team conducted additional interviews to help build consensus within the company on some of the aspects of the SSM role. With a consensus in place, VisionCor built an overall site map and detailed content plan. The site look and feel was designed around content, audience analysis and the existing intranet. Information was then converted into a Web format. Once the site navigation, graphics and initial content were developed, VisionCor conducted usability tests to ensure that the site structure was intuitive and content was meaningful. Experienced SSMs tested specific scenarios to ensure maximised usability. Testers varied from new hires to experts and leaders. Usability tests also helped to determine what content should be linked to other content to help maximise the content’s value. The entire development process took approximately 90 days from start to finish. Phase 3: Core Development. With the initial content online and tested, development and coding of final site content began. To confirm that the team was still on target, VisionCor conducted additional analysis on the SSM role and reviewed content categorisation. The remaining content needed for a full service portal was gathered, developed and coded, with additional interviews conducted as necessary. Next, developers began integrating content so that navigation was intuitive, which required a thorough understanding of the audience and how they would use the portal. To do that, VisionCor employed its own methodology for organising content into knowledge objects and building relationships between them. Structuring content as objects based on how the information would be used gives developers an intuitive guide for building relationships and links between individual objects, what VisionCor calls chains of inquiry. Next, the knowledge portal was retested. Users were given varied scenarios or situations and asked to use the Website to find the information they needed to best respond the situation. Developers conducted analysis based on how SSMs used-and didn’t use-the portal. In addition to providing feedback, the usability tests also assisted in user acceptance of the site, which is vital to the success of any knowledge management initiative.

The team completed development and testing of the finished knowledge portal in approximately 120 days. Phase 4: Ongoing Knowledge Cultivation. Because the portal is a growing collection of knowledge and experience, ongoing development continues through periodic reviews and additions to the Website. It is important to note that although the project timeline was sectioned into four distinct phases, new content and iterations of the site’s design were migrated weekly.

The Results Cisco’s service and support advocacy intranet site was very well received within the SSM organisation. “Everything I need is in one place. I can find what I need when I need it without having to wait for an e-mail reply, walk around looking for someone, or search through gigabytes of information on the intranet. Plus, after working through difficult situations, I can post my lessons learned on the site so my colleagues can learn from my experiences”, says Mike Pusich, SSM for Boeing. Rob Dacey, SSM for GM adds, “It guided me through my first 90 days, helped me build a support team, and introduced me to other SSMs. Now I am using it to define my objectives. Basically, this site just makes my job easier and gives me more time to focus on serving my customer”. Currently, Cisco is working with VisionCor to leverage the knowledge and benefits gained from the SSM project into other areas of their organisation. Cisco’s record breaking growth and razor sharp focus on customer satisfaction could be problematic, but VisionCor’s knowledge management expertise coupled with Cisco’s commitment to customer satisfaction turned Cisco’s information overload into knowledge-ondemand.

Patni Computer Systems It is India’s sixth largest organisation that makes extensive use of knowledge in its business processes. The company has created a knowledge centre, which allows its employees to learn about new technologies, have discussions, get technical queries answered and even draft quick sales proposals. For Patni, this system has led to a reduction in training time and a boost in productivity due to better sharing of knowledge among its employees. Here are some of the features of the knowledge centre: • The knowledge centre contains information about the quality management system, information related to different projects, related best practices and lessons learned, technology related white papers and tutorials. • A searchable repository of reusable software components. • As it is based upon a web based model, information is accessible from all Patni offices. • Classification of content according to industry verticals and technologies. • A discussion forum for exchange of ideas and solutions. • A help desk for facilitating process consulting to projects. • A marketing centre which holds frequently asked questions by customers (the same is used by employees in sales and marketing). Additionally, case studies and templates for proposals and newsletters are also captured in the knowledge centre. • A role based access privilege model that ensures that every user has access only to information pertaining. (Source: Indian Express, Business Publication Division)

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Knowledge Management

KNOWLEDGE PRODUCTS A knowledge product is an artifact of information, a kind of persistent retention of the knowledge of one or more individuals. Knowledge products differ from other artifacts in that their relevant and useful aspects reside primarily in the content that can be extracted from them, and, as such, any physical manifestation, thereof, is usually at best a carrier medium. Examples of knowledge products include: • Text documents (books, journals, periodicals, essays, poetry, etc.) • Recorded music • Films and television programmes • Art (paintings, sculpture, installations, etc.) • Flags, logos, branding, trademarks, trade dress • Legal documents (contracts, acts, writs, etc.) • Software Of these, software is unique, as it is said to have behaviour. More specifically, it instills behaviour in computers when it is executed by them, causing tangible effects in the real world. It is a product built on data, information and knowledge inputs. All software products are knowledge products. For example, Core Banking Solution product is a knowledge product developed to manage bank processes of which account holders, branch managers, employees at the customer facing counters are users. The knowledge product considers domain knowledge of banking industry, government and RBI rules and regulations, and best practices in executing hundreds of banking processes. The product so developed is a generic one and can be modified to suite specific local conditions of a typical bank. The knowledge products have flexible design so that they can be customised to customer requirements. All ERP, CRM, SCM packages are knowledge products designed and developed to manage organisations resources efficiently and effectively. The organisations develop spread sheet models, templates, system models, charts and diagrams for use in the organisation. Such products usage saves time, brings approach consistency in solving the problem, Communication on the subject matter is easy and clear to all concerned.

A Case Study: ICT for Human Capital Development (Source: Aims digital, Pune, www.aimsdigital.com) Aims Digital is an organisation with a unique combination of services strategically positioned to provide customers with a complete range of integrated Information Communication Technology services. Aims Digital’s services include development of CBTs and WBTs covering myriad topics, including self paced e-learning, product knowledge, process training, sales and service training, simulations and soft skills training. Aims digital drives e-learning initiative with business impact, to improve organisational performance through human capital development. Their aim is to propel customers’ profitability by offering innovative knowledge solutions with cost optimised development and operations. The company had effectively integrated performance expectations with knowledge development and, in the process, improved the organisation’s training/learning fitness. To illustrate this, brief case studies of four projects covering a mélange of topics have been presented below:

BioTech Primer, Inc The client provides basic biotechnology education and training for non-science professionals. Engaging, credentialed instructors present relevant and timely information on the science, techniques, applications and issues that drive the biotechnology industry. Lectures combined with hands-on activities and small class size ensures a productive, relaxed learning environment.

The Requirement The client had perplexing and expensive issues to solve, viz., the logistics of travelling to learner sites, additional costs to maintain a good knowledge management base, deployment of their proven educational techniques worldwide, added benefits of self paced learning via cutting edge media, updating content and information easily without vendor support. The target audience involved, business professionals, administrators, marketers, legal professionals, financial professionals, and non-scientist education professionals.

The Solution Over 20 hours worth of instructional material in the form of notes, actual paperwork, e-mails, story boards and all sorts of media was converted into an intelligent, graphic intensive, and educational eight hour e-learning course.

Compliance and Delivery This graphic intensive interactive course was delivered using an Adobe Flash and XML engine. The courseware was made conforming to SCORM 2.4 standards that made it deployable on any standard LMS. The engine (or the GUI) acted as a cradle for the chapters, which were rendered as Shockwave Files (SWF).

Deployment The course was deployed on an Enterprise LMS and is capable of catering to upto 40,000 users by way of direct registration with the client, or registering with client’s sub-portals, thereby swelling its reach greatly. Biotech Primer needed a revenue generating model and Aims effectively helped them achieve that and more.

Demag Cranes and Components The client is one of the world’s leading suppliers of industrial cranes, crane components, harbor cranes and port automation technology.

The Requirement Since the client is into manufacturing of cranes and crane components, it needed the employees and contractors to have sound knowledge of the cranes, their components and types. Training under one roof was not an effective model to train every person associated with handling cranes, as most of the times contractors or employees would not be physically present. The challenge was not just to train the learners on various crane and types but also to impart the necessary knowledge of the working of other components, such as the wheels and hoists.

The Solution The course has an instructive approach to training employees and contractors the variations in the models, their working and the components used. The training is complete with objectives defined and knowledge assessed. Intensive graphics, such as animated exploded views of components, interactive exploration and animations are used to elucidate the complex content.

Delivery and Deployment The course was delivered using an Adobe Flash driven engine which was used to render the chapters. This was deployed on the company’s intranet for learners to gain access to it at any time.

The Result Tactical benefits such as cost savings are important considerations. Moving training from the classroom to Computer Based Training (CBT) can mean reduced travel costs, less learning time away from the job, and certainly lower delivery costs.

Nevis Networks The client provides identity based policy enforcement in network fabric, controlling who can access a company’s network the what resources they are permitted to use, as well as containing the spread of the most sophisticated malware.

The Requirement The client wanted a short, quick, engaging and informative solution to demonstrate the capabilities of its security appliance.

The Approach An analogical approach to depict the products capability was used. The modern day enterprise level data security system was depicted using medieval age back drop. High walls of a fortress depicted the organisation and intruders, such as barbarians, were used to depict the malware and untrusted users. This further showed the inability of the organisers to communicate with trusted users outside the fortress. Once the gates of the fortress are thrown open and fire walls installed showed part of the untrusted users and malware entering the fortress. The client’s appliance was shown to have made the walls of the fortress disappear, yet maintaining the security of data, thereby removing the constraints and having a free, boundless communication which was safe and secure.

Delivery and Deployment The demonstration was delivered using Adobe Flash and deployed on the company’s corporate website.

The Result Deploying such a product demonstration on the website has enabled prospective customers outing to its greater visibility. The understanding of complexity of installing such an appliance in an enterprise was made easy by this short learning module, which otherwise would have been delivered in the form of text and/or text and images.

British Pharmaceutical and Consumer Healthcare Company The company has its presence worldwide with customer relationship management centres and BPOs.

The Requirement The client needed an online and self paced induction programmes for the people joining the BPO. The course included information on the disciplinary and grievance policy, dress code policy, healthcare policy, sensitive information policy and working practices.

The Approach Aims Digital converted the information present in form of various PowerPoint slides, word documents, etc., and converted them into an online e-learning session. This training was imparted as a part of the process understanding and orientation module for all employees joining the company.

Scenario Based Learning The courseware had animated scenarios with dialogues, animated wisard and high quality illustrations to explain the processes in the company illustrating various circumstances in the organisation.

Delivery and Deployment The course was delivered using an Adobe Flash driven engine which was used to render the chapters. This was deployed on the company’s intranet for learners to gain access.

The Result The organisation has been able to discard the conventional PowerPoint presentations, word documents and PDFs and have an interactive e-learning environment for its employees. This has helped impart the HR related information to the employees in an engaging and interactive manner that is also self paced, which, in turn, has helped improve the retention of information by the employees. Some more knowledge products which are very common are Organisation Manual, Product/Service Manual and Process Manual. • Organisation Manual Includes vision, mission, organisation structure, business, and business activities, organisation history, basic information about employees (who is who), products, processes, policies, and so on. • Product manual Includes product description, information on specification applications, strengths, drawings, pictures, diagrams, installation guidelines. Also includes structured product information on assemblies, systems and their internals. It also briefly guides how to open the product and put it back after repair and maintenance. • Process Manual This manual describes complete process details, specifications, diagrams, process options. The guidelines help to handle deviating conditions.

INTELLIGENT AGENTS Intelligent agents (software agents) are programmess which carry out the requested tasks on behalf of users. The spectrum of capability of agents is wide, ranging from the basic level of automating straightforward routine tasks through to the ability to adapt to user routines and preferences, and even to negotiate on behalf of users. The feature which distinguishes agents from other programmess is their ability to automatically adapt their behaviour to the conditions they encounter, and to make decisions based on a set of inbuilt rules and criteria, without specific on-the-spot instructions from the user. Agents may possess this feature of autonomy to a greater or lesser degree, depending on their sophistication. The capacity for autonomous behaviour may extend to taking the initiative, for example, providing the user with information not specifically requested but likely to be of interest. Agents may also communicate with one another and with other programmess or people to obtain information or enlist help. ( Source: [email protected] © TERENA, Singel 466-468, NL-1017 AW Amsterdam)

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Applications highly suited for intelligent agent technology include: • Data filtering and analysis • Information brokering • Condition monitoring and alarm generation • Workflow management • Personal assistance • Simulation and gaming As a result, there is growing interest in intelligent agent technology from a number of blue chip companies, including IBM, ATandT, Apple, BT, HP, Microsoft, Lotus and Digital. Researchers from disparate disciplines are actively involved in developing or applying intelligent agent technology-including robotics, entertainment, knowledge based systems, human-computer interaction, databases, distributed systems, communications networks, cognitive science and psychology. Examples of commercial applications of software agents include: • Visual financial analysis agents-such as FourGen (agents perform data mining and analysis). • Infoagents-such as Verity (agents perform information filtering and document management). • System management agents-such as BMC and Eco Tools (agents support system managers by monitoring and reporting important events). • Workflow agents from Edify (where agents perform call handling-this is used by a major international carrier and a leading photographic equipment manufacturer). (Competing for the Future with Intelligent Agents, by Faramars Farhoodi and Peter Finga [email protected] . . . . . [email protected] org© 1997, Farhoodi and Fingar)

Personal Logic (www.personalogic.com.) Personal Logic, an agent tool, enables customer to obtain a short list of products using limited number of features from number of products having many more number of features. The customer wants some feature while some are not desired. The agent filters out the products which have features specified by the customer. It then displays the list of products satisfying the customer requirements. Another example of agent technology is the Product Finder (http://www.jango.com/xsh/index.dcg?) employing Jango agent software which was designed specifically for shopping on the Net. eWatch at http://www.ewatch.com/ is an example of an agent based alerting service available through subscription. It monitors mailing lists, news groups, forums, and web sites for information on insider trading, stock manipulation, rumors and anti-corporate activism. Naukari. com short lists the candidates on profile and uses IA to match clients’ requirements for best short listing of candidates.

Firefly (www.Firefly.com) This agent searches the opinions and product ratings of the other customers in the same customer segment. Then it searches customers in near about location and compares the rating of the product, and advises the customer to make appropriate decision. E-commerce has grown phenomenally over the last few years and so have the number of participants operators. Although web business models differ from the traditional brick and mortar models in many ways,

the fundamental needs of consumers and businesses remain much the same: consumers want to compare shop products and services side by side for the best price; businesses want to grow sales by driving the right shoppers to their sites. These needs give rise to a variety of intelligent agents working for buyers and sellers of products and services over the web.

Buyer Agents Rather than getting into a site the user never wanted, or playing a hit or miss guessing game regarding which keyword search result might match his needs, a variety of intelligent agents can be sent out by buyers to help locate stores, brands, product or service categories, products and services, and desired prices. These capabilities would drive a shift from a web centric to user centric e-commerce model, whereby buyers would be empowered to comparison shop even before going in to one particular seller’s site. Moreover, the buyer agents perform the work without user intervention, thereby simplifying life while improving the end results obtainable by the user. With more efficient and powerful search capabilities, agents are also expected to help further drive down e-commerce costs and make web shopping more transparent. These effects would make e-commerce increasingly attractive to reluctant consumers, since convenience, costs, and on-the-fly availability of peripheral information are the major hooks of the digital marketplace.

Seller Agents In turn, buyer agents affect how vendors on the web need to operate their online businesses. In a more competitive and transparent marketplace, vendors of products and services on the web would need to hone and logically organise their information so that buyer agents would be attracted. Sellers can use intelligent agents to track demand and market share changes, engage in competitive knowledge mining, and even learn through collaboration with buyer agents. Learning agents deployable by sellers are less obtrusive and typically receive greater acceptance than filtering agents that require users to make ratings and answer lots of questions. (Source: M.V. Sinmao, Intelligent Agents and E-commerce)

Digital Tutor An agent acts as a ‘Digital Tutor’. The agent infers the calibre of the student based on student learning profile and selects the delivery programme to teach the student. Digital Tutor is equivalent to human tutor. It is smart and selects appropriate learning tools and learning resources subject to student’s learning profile, pointing to strengths and weaknesses.

Groupware Technology Groupware is a software that facilitates a group of people working together within the same system or application, no matter where they are located. Such groupware applications are commonly e-mail, newsgroups, and chat. Common groupware applications tools that are commonly used include Lotus Notes, e-mail server systems, such as FirstClass and Microsoft Exchange, 24Seven Office, Livelink, and Workspot. Groupware applications are divided into three categories: • Communication tools for messaging • Conferencing tools for transfer and sharing knowledge • Collaborative work management tools Communication tools include e-mail, FAX and voice mail. Conferencing tools include data, voice and video conferencing, and message boards and chat rooms. Collaborative management tools include electronic calendars, project management systems and workflow systems.

When employees are using an application at the same time, it is synchronous groupware; workers using the same application at different times, however, are using asynchronous groupware. Businesses use groupware technology for a variety of reasons. One primary reason is to bypass the traditional problem of having employees in different places that need to work on the same application. By logging in to an intranet server, employees in different places can access the same application and benefit from the various perspectives and opinions of others. If they can log in to the company server from anywhere, then they don’t need to be in office in order to access certain groupware. Telecommuting can save on travel costs for both companies and employees. It can also enable real time communication when it would otherwise be impossible. This communication creates a greater understanding of the targets and goals of a business projects, through group discussion for each step along the way to achieving those targets and goals. Another use for groupware is group problem solving. Many times, some employees see things differently from others. If they are all working within the same application framework, they can solve problems collectively, saving company time and money. Without groupware, such real time cooperation would not be possible (Source: David White Conjecture Corporation, Adopted)

UNIFIED COMMUNICATIONS TECHNOLOGY SOLUTIONS Deutsche Bank selected Cisco to provide unified communications solution based on strategic assessment of their telephony requirements. Initially, Deutsche Bank installed nearly 1,000 Cisco 7961 and 7911 Unified IP phones at its branch offices in the U.S., with the potential to expand the voice services across all its U.S. operations. As part of this upgrade, Deutsche Bank also deployed Cisco’s Unified CallManager software, and Cisco Unity voice messaging system, an IP based solution that combines traditional voice mail functionality with a Web browser, allowing users to access and manage voice messages from a phone or from a PC. “With our new Unified Communications services from Cisco, Deutsche Bank is able to seamlessly integrate voice, video and data collaboration in one system,” said Reiner Bayard, managing director and global head of networks at Deutsche Bank. With this, “We are able to easily scale the network and services to grow over time and would also drive productivity through new mobility services, such as soft phones and extension mobility features.” With Cisco Extension Mobility, a built in feature of the Cisco Unified CallManager software, Deutsche Bank employees can log on to any Cisco IP phone, personalise it with their own telephone number, preferences and directories. For example, executives who attend meetings at another Deutsche Bank office can log on to a Cisco 7961 Unified IP Phone in a conference room and use their personalised message access button to retrieve messages from the Cisco Unity voice mail system, just as if they were in their own office. This allows employees to respond more quickly to urgent business. Cisco Unified Communications ensures that information and interactions reach recipients quickly, using the most effective medium. Designed for ease of use, it lets users quickly access the people, tools and content they need, wherever they are, according to their own rules and preferences. This new system is a solid example of how the network is the platform for powerful communications enabling the knowledge transfer and sharing with rest of the employees. Mobile groupware applications are becoming popular in industry in the area of communication and working together. Mobile applications with Groupware technology offer cost effective solutions and speed in execution of synchronous or asynchronous tasks. Mobile Meeting Scheduler (MMS) is an asynchronous Groupware application.

The main features of MMS are creating, sending, receiving, updating, accepting and declining meeting invitations. MMS enables users to compile and send meeting invitations concerning specific subjects, time and place of attendees by using a master list containing addresses and other references. It allows organisers to send query on ‘availability on particular time slot and at particular location’. MMS includes electronic mailing system and calendar system. These scheduling applications are asynchronous. The use case of MMS is given below. The entities in the use case are organisation, user, attendee and application server (AS). 1. Send Query for Prospective list of Attendees 2. Recieve List 3. Send Availability Query 4. Receive Availability Confirmation Data 5. Send Meeting Invitation

Application Server Supporting Query, Requests and Commands

6. Receive Invitation 7. Send Confirmation 10. Receive Acknowledgement

8. Receive Invitation Results 9. Send Appointment Confirmation

Fig. 9.2

Use Case of MMS

BUSINESS CASE FOR KNOWLEDGE MANAGEMENT In global business scenario, knowledge management has become an important function to become successful in the competitive environment. It is proved beyond doubt that the organisation has to become knowledge driven in its endeavour to beat competition. The organisations accepting this as paradigm shift need to make a business case justifying formal introduction of KM as an important function among many others. It is difficult to prove that knowledge, tacit or explicit, is directly linked to the positive impact on business outcome, making the job of justification of KM a simple and convincing proposition. To prove this link of KM to bottomline business performance,a framework is suggested. This framework is made of series of steps, jas prescribed by Albers’ framework for Implementing Knowledge Management Model (Albers, 2003), that would aid knowledge management implementations champions in establishing the business case for KM introduction as an important function. Alber’s framework has following critical steps, each with a specific goal to achieve in context of KM: 1. Business strategy assessment 2. Knowledge assessment and audit to support efforts gaining strategy sucess 3. Knowledge and business strategy alignment 4. Business opportunity identification 5. Value, business benefits and evaluation 6. Risk reduction techniques

Strategy Assessment As with most efforts, the initial focus needs to be at the top and be directed at assessing the role of knowledge within the business. Every business is unique and, therefore, the KM initiatives that each undertakes are also unique. Just because a certain methodology or approach worked well at one form is no guarantee that it will perform equally well at another. The organisiation going? The strategic assessment includes establishing/ reviewing the vision and mission, analysis of the firm’s competitive environment, analysis of internal strengths and weaknesses and formulation of strategic action. Once this has been clarified if needs to be determined how knowledge fits into the overall business strategy, objectives and value proposition of the company. The value proposition considers how the company specifically creates value and offers unique goods and services to its customers. Knowledge management can play a pivotal role in both defining what direction to take and implementing strategic actions.

Knowledge Audit A knowledge audit identifies what knowledge exists in the organisation and what is needed to move the organisation in a strategic direction. There needs to be a reckoning and accounting of the current status of knowledge practices already in existence within the firm. The audit identifies the expertise in the organisation, where it can be found, and how it can be is accessed. It identifies what knowledge is needed to make decisions and what knowledge assets are needed in the future. Sometimes, a full and comprehensive knowledge IT audit may not be practical. If this is the case, at least a basic knowledge overview needs to be performed to have an awareness of the current state the KM initiatives in place.

Knowledge snd Business Strategy Alignment The third step that needs to be undertaken is to align the firm’s knowledge strategy with its business strategy. In other words, identify what the company must know to implement its business strategy by identifying both strategic and knowledge gaps (Sack, 1999). The strategic gap is the difference between ‘what the firm must do’ and ‘what it can do’. The knowledge gap is the difference between ‘what the firm must know’ and ‘what the firm knows”. The alignment of the knowledge and business strategy should identify what knowledge really matters and what are the knowledge leverage points in the firm’s performance. It is important to realise that this is an iterative process that is constantly ongoing with continuous feedback through multiple knowledge life cycles (McElroy, 2003). The knowledge lifecycle includes both knowledge production and knowledge integration supported by the knowledge processing environment of the firm.

Opportunity Identification Having clearly established the organisation’s strategy, current knowledge capability and any gaps that may exist between its business strategy and knowledge strategy, one is now in a position to identify potential opportunities for knowledge development. This is the stage at which the challenge is met by defining and assessing those knowledge areas that would have the most impact on the business’ objectives, which, in turn, are linked to the firm’s well defined competencies. At this point, it would also be prudent to be mindful of some lessons garnered from previous KM implementations. First, the age old truisms ‘you can’t control what you can’t measure’ and ‘you get what you measure” most certainly hold true. While identifying opportunities for knowledge development it must always be remembered that some form of baseline, benchmark, and measurement system must also accompany each effort in order to be able to manage and judge its success. Also, the tendency to place too much emphasis

on IT technology must be tempered. IT is only an enabler to the KM efforts and not the whole process. A large amount of KM can be done without incurring enormous IT expenses. The oft quoted Pareto Principle provides a useful rule of thumb that the budget for the KM initiative should have only about 20% of its total devoted to IT/tools and 80 % reserved for organisational and human process factors.

Value, Business Benefits, and Evaluation Once one or more opportunities have been identified, the case in support of each needs to be established. As stated to previously, there are effectively only three viable approaches that may be invoked to justify a new initiative (Oldham et al, 1997): economic (break-even, ROI, IRR, NPV), analytic (value analysis, risk assessment, portfolio analysis) and strategic (business objectives, competitive advantage). All three have obvious benefits linked to business processes. David Skyrme has suggested the utilisation of a KM benefits tree to highlight the connections and relationships between asset value, benefits potential and cost effectiveness (Skyrme, 2001). A benefits tree is a tool that traces all of the branches of a given benefit from the origin to those outcomes that affect the firm’s bottomline. As pointed out by Skyrme, the benefits tree can usually be constructed with only a few main categories, often including: information and knowledge benefits, intermediate benefits, organisational benefits, and customer and stakeholder benefits. By using such a construct to identify the linkages between each category, some of the more abstract and intangible benefits of knowledge management initiative can be more easily and visibly highlighted to crucial stakeholders to whom the justification process is being addressed. Several additional factors should also be considered and taken into account in order to establish a convincing business argument in favour of any change in general, but specifically a new knowledge initiative (Keen, 1988). First, the risks involved in undertaking the effort must be highlighted. Obviously, the more innovative and radical the proposal, the fewer are number of precedents that exist to benchmark and compare against. Also, it needs to be remembered that greater the potential payoff, greater is the likely risk involved in the undertaking. Next, narrow the proposal down to three or four plausible alternatives: 1. Doing nothing (a real option) has consequences (lost opportunity) 2. Ideal case in which everything works according to plan 3. One or two intermediate cases between ideal and doing nothing It is then necessary to compare the value of the benefits of the proposal through a value-benefit analysis. This step is important since, until a value is established, any cost is disproportionate. Also, costs are typically quantitative, predictable, and realised immediately, whereas benefits are typically qualitative, uncertain and deferred until later. Therefore, the benefits need to be established separately from the costs. Once the benefit has been established, then the question that needs to be asked is: ‘What cost is acceptable for this benefit?’ or, ‘What is the cost threshold required to attain this benefit?’ Another valuable technique is to separate and rank order the hard and soft benefits of the programme. This is because people view these two categories in different lights and some executives may put more emphasis on one type over the other. The hard benefits of a KM initiative are fairly straightforward and directly related to financial performance, such as reduced costs, ROI, IRR, profit, etc. However, the soft benefits may be somewhat more elusive to articulate. Soft benefits may include enhanced synergies among business functions, SBU’s, accelerated path breaking innovation, achieving higher customer added value, reduced exposure to risks, quality improvement, increased teamwork, increased speed and responsiveness, and better decision making by frontline workers.

Other intangible benefits include increased employee retention, employees better connected to the experts, increased problem solving by front line workers, improved work routines, process improvement, and the organisation being more aware, involved, and focused on its strategic endeavours. Having now established a methodology to help identify the knowledge opportunities, their values and benefits, the last step in establishing a business case is to perform risk reduction techniques as discussed in the next section.

Risk Reduction Techniques Having developed a framework that may be followed in an effort to make business case for a knowledge management initiative, it is worthwhile to enumerate some thoughts that may aid both in the justification cause, as well as successful implementation of the KM programme. As stated above, in order to be successful, knowledge strategy needs to be aligned with the business goals and objectives. That issue not withstanding, it also needs to be ensured that the efforts undertaken target the investment and KM initiatives at the right problem/issue in order to realise a satisfactory ROI. There are three broad categories that all such efforts can be associated with (Swanborg Jr. and Myers). They are, in order of increasing dependency upon greater resources of time, money and infrastructure, as given below: • General or structured sharing. This is the knowledge required to perform and do business in a given industry or market. • Focused competence. This is the knowledge that keeps the organisation in step with its peers/ competitors. It is how a business achieves excellence in its work, including specific business processes or value added activities that they concentrate on. • Strategic competence. This is the knowledge that gives the organisation its specific source of competitive advantage. It is highly recommended that the knowledge programme be initiated with one or two relatively straightforward and quick projects to instil confidence and demonstrate success. This can then be followed up with a more extensive portfolio of projects that would undoubtedly include some from within each of the areas delineated above. Furthermore, the pilot group for the first initiative should not be the best or worst performing group or department in the company. Also, it should not be immediately related to the organisation’s core competency due to the heightened expectations and pressures to succeed, and the potentially disastrous outcomes, should it encounter difficulty. Hence, the most prudent choice would be a small group that is likely to succeed and show benefits on a rapid time scale. In other words, don’t try to solve all the company’s problems at once and don’t risk the attempt on one of the core competencies of the business in the unfortunate event that it does fail! Another technique that may be very beneficial for making the business case for knowledge management is to employ the use of an options approach toward the investment. The options approach is a viable alternative to aid in mitigating the risk associated with a given undertaking. This approach can be extremely valuable under any of the following circumstances • when an investment decision can be deferred • in helping managers strike a balance between waiting to obtain valuable information and foregoing revenues or strategic benefits from an implemented project • for prototyping investments • for technology-as-product investments (KM, to some extent, since it can be technology intensive). As pointed out by Dixit and Pindyck, the options methodology makes two important distinctions that can be extended to help justify a KM programme (Dixit and Pindyck, 1995). First, it highlights the issue that the common NPV acceptance rule is easy, but it makes the false assumption that the investment is either reversible or that it cannot be delayed. Secondly, the role of risk and uncertainty can be clarified by recognising that

Case Illustrations of Knowledge Management 317

an investment opportunity is like a financial call option. In this light, variables that affect the project’s (or option’s) value can be used in the well known Black-Scholes option Pricing Model (Sender, 1994). Factors, such as the initial capital investment, the present value of the expected cash flows from the project, the length of time of the option, the project volatility and an appropriate risk-free rate of interest, can be estimated and varied to aid in valuing the project. Furthermore, the options approach highlights the benefit that relatively small, initial investments are a way to establish the firm’s ‘right’ and ability to ‘leave the door open’ to any given opportunity for which the ultimate payoff may not be immediately obvious or calculable. Viewing and couching KM initiatives in this type of framework may be very beneficial to establishing adequate justification for the programme to get approval from its stakeholders. These three approaches were: to ensure that the initial KM effort is targeted at an appropriate knowledge area that will have quick success and highlight the positive aspects of the KM programmes. Following these guidelines and recommendations should result in successful justification of the business case for a knowledge programme as well as in providing the organisation with valuable insights into how to make the initiative a resounding success.*

KMS APPLICATIONS Airlines Corporation Airlines industry comprises competitive business where service and service delivery are the key result area. Passenger revenue is very sensitive to the quality of service offered by the airlines. Airlines rely heavily on data analysis to get insight into business behaviour. Extensive use of data warehousing and mining is made to find the meaning of the passenger behaviour. Pricing models are built for different seasons and different periods and have become part of the ticket reservation and booking system. Explicit and tacit knowledge is acquired through data analysis and experience about customer choices, patterns and trends in flight occupancy. The knowledge is used for strategic pricing. • Explicit knowledge comprises of Traffic data Load, peak load Passenger data Profiles, choices of services Route/Sector Statistics Cost and economics • Tracit Knowledge is built out of Patterns and trends in flight occupancy Passenger profiles of loyal passengers Service demanded and feedback on the overall experience Airlines use OLAP tools and data mining tools for • Projection and forecasting for passenger profiles, traffic pattern, i.e., Flight vs route vs occupancy analysis • Devolep creative ideas to design airfare strategies and test them on tacit knowledge • Identify reservation pattern and cancellations

* Source Journal of Knowledge Management Practice, August 2004, The Business Case For Knowledge Management, Eugene F. Yelden, Synrad, Inc., James A. Albers, Pacific Lutheran University

KMS Model is built to generate knowledge for use in various strategies. The goal is to maximise Airlines’ passenger recenue. Airlines Operations

Extract Data Analyse Learn, Innovate Formalise

Build Price Models, Forecasting Models

KDB

Fig. 9.3

Other Airlines Operations Other Events Information

Develop Explicit and Tacit Knowledge

Process

Pricing Strategy

KMS DIKAR Model

• Standard practice: Go for flat, across the board hikes in pricing • Knowledge driven practice of pricing: – Innovative structure of fares based on market conditions and strenght of damand – Dynamic face policy linked to trend in flight booking Pricing product Developed Automated Revenue Management Systems (ARMS) to structure fares with the knowledge of passenger profiles, route revenue, facilities offered and traffic density Passenger Profiles [Explicit Knowledge]: Passenger who plans ahead and books in advance Passenger who does not plan and need real time booking Passenger type • Family • Business Executives • Tourist and Groups, etc. Traffic Data: • Loss making routes • Low traffic routes • High traffic routes • Wait listed flights ‘ARMS’ is used for • Discretionary and Discriminating prices • Seasonal discounts, non-peak time discounts, etc. • Class and type booking schemes Figure 9.3 shows the KMS DIKAR model, which is used for KM applications in airlines.

IBM and Carrier Corporation (Sense and Respond KM Strategy) IBM and Carrier Corporation have joined hands to leverage on each other’s knowledge competency for business growth.

Internal Sources • Flight Data • Traffic Data • Passenger • Statistics • Schedules • Occupancy • Data, etc.

KDB Pricing Strategy Options

External Sources • Other Airlines Data • Information from Agents

Fig. 9.4

ARMS

Impact on Traffic Management

Airlines Knowledge Model

• Carrier Corporation Needs Ability to manipulate and set temperature, switch AC units, etc., from remote location ahead of time • Strategy Enter into alliance with IBM for web enabled air conditioners that can be controlled for performance • Solution Ability to set temperatures or switch units on or off wirelessly – Develop Web-enable air conditioner which can communicate in real time with mobile phones, PDA, PCs – Develop website to operate services • IBM supplies technology services, software and hardware to Carrier Corporation. – Carrier to design web-enabled air conditioners – Dealers, service providers, engineers to be trained for monitor and control of the new system – Develop knowledge database on key customer data, usage, performance, etc. – Software for automatic sending of fault codes and other diagnostic alerts instantaneously to mobile phone, or through e-mail or fax

Financial Institutions Providing Single Point and Single Location Integrated Services to Investors • Customer need Single point and Single location integrated services – Advisory : Counseling – Insurance : Stock broking – Loan : Depository • Strategy Built knowledge database to construct hard and soft strategies based on 27 years experience in the business of investment and other financial services Association with banks and FIs. Network of 100 branches 8,00,000 Investor Database

• Solution: Develop – Software solutions for services – Integrated back-end accounting system – Customer care and communication system for new developments – Develop group experts for each service and evolve solutions to keep individulals and partners updated for efficient service management

Ogilvy and Mather India • Traditional Business: : 85% Traditional Advertising : 15% Direct Marketing, PR, Event Management : Annual Billing – Rs.7500 million • What is sensed through knowledge? : Move from supplier/Ad agency to value adding services partner : Move from managing brands to managing of consumer needs and wants : Restructuring of traditional media, planning and creative departments organisation • Solution (Goal) Create an O&M of the future putting in place better knowledge driven processes, systems and structures : Creativity (knowledge) to be shared across the O&M : Move to networked communication with vendors, partners, associates, business partners • Solution Model: : Spend more time on knowledge acquisition, i.e., 20% to 50%, jby more emphasis on account planning : Restructure around knowledge-led need clusters, i.e., Group brands under consumer need-250 clients grouped into 14 clusters. For example, the grouping may be: – Health & Hygiene : Glaxo, Smithkline and Novratis – Transportation : Telco, Castrol, Amaron Batteries. : Build cross function teams for the cluster, i.e., Art Director, PR strategist, CRM and Media specialist. : Build knowledge acquisition cells for each cluster: – Search best practices from the world – Research on needs and want of consumer, and not market research – Search for board band of service providers and collect knowledge inputs

HLL Ltd Problems Data and information jalone about market don’t give effective results Solution (Goal): Move from brand focused research to research on lenitive consumer behaviour i.e., Switch to consumer interaction : Move from brand focused research to research on lenitive consumer behavior, i.e., switch to consumer interaction : Move from product and AD Testing research to consumer understanding, i.e., Move form ‘where, how much, when to why’ of consumer

Solution Model: Launch a Consumer Programme containing following four modules: Module 1 • Category Research To identify use of products and how they relate to product category, i.e., usage and altitudes, products, barriers and triggers for buying and triggers for buying and usage. • Holisticc Research Consumers life style, as a whole, in terms of each family member • Build Dockets (Dossier on consumer knowledge, experience and trends) • Build CAMERA An online database of knowledge for quick reference Module 2 • Interact with consumers directly. Managers and consumer interaction meeting are arranged to acquire knowledge on consumer behaviour, decisionmaking. Module 3 • Run consumer clinics to get first hand feedback on concepts, ideas, and so on. • Run sequential recycling programme where concept is implemented and comments are called. The process enriches the knowledge. Module 4 • Interact with experts in various disciplines and business from the fields of music, sports, consumer lobby, senior citizens, experts in social, education, research, etc, to gather knowledge on best practices.

Daimler Chrysler (DC): Engineering Book of Knowledge (EBOK) Daimler Chrysler (DC) adopted a new approach to automobile design, called Team approach, a deviation from earlier practice of designing by functional approach. The Teams become multi disciplinary focusing on one type of car, namely van, small car, and so on. The cars were designed by a single team, keeping in view the knowledge obtained about customer requirements and expectations. Though delivery cycle was reduced from 50 month to 39 months, it was observed that the same mistakes were being made and lessons were not being learnt, informal discussions on problems had almost stopped, and mentoring was a rare practice. Employees were not enriching their knowledge with new developments in theory and practice of design engineering. The collaborative spirit had reduced. The problems and solutions were not documented in systematic manner for sharing and for ready access. DC had organisational memory problem. To overcome this problem, DC made KM a vital condition in design and Engineering of automobiles. DC decided to create a Engineering Book of Knowledge (EBOK) containing buckets of knowledge such as Test data, CAD/CAM drawings and data, data bases, data from transactions of purchase, inspection and so on. DC formed ‘Techclubs’ of design engineers from different functional groups across the organisations where Design engineers and Engineers came together to exchange ideas and new learning. The cultural issues were overcome. The EBOK became DC’s intranet supported knowledge repository of best practices, technical know how, standards and most preferred practices. It also contained competition information. Thus EBOK of DC is a living real time online repository of knowledge for design engineers to refer, exploit for deployment, and share in collaborative spirit. DC leverages its design efforts on e-EBOK. It is central to DCs new way of working-knowledge driven working. The Techclub members follow KMDLC in keeping e-EBOK up-to-date and highly productive. The EBOK comprises several books devoted to different key areas of knowledge and problems and solutions. The EBOK also provides views of experts and peers for using a particular knowledge entity.

The KM frame work in DC of which EBOK is one component has the following structure. Key Competencies • People Leadership and ability to bring together and affect their behaviour. Low tolerance for imperfection and open ended approach with open mind. • Process KMDLC adoption. Continuous improvement through reengineering. • Technology Intranet and Extranet. Tools to transform and share knowledge. Deployment Approach • People Reliance on empirical evidence. Collaborative spirit and coordinated action. • Process Continuously being questioned and debated before use in practice. • Technology User friendly, encouraging involvement in selection and through training. Support • People Encouraged by reward recognition systems. Top management involvement. Culture of collaboration and sharing. • Process Internal support structure for mentoring, technology and tools very strong. • Technology Insisting on state of the art technology. No hesitation for sourcing from outside. KM works in Daimler Chrysler as it revolves around people and customer knowledge. The technology is understood as enabler or driver behind KM initiative.

KM in Pharma Industry (Extract) from Madanmohan Rao Report from the Pharma KM Conference in London Speedier Innovation, More Cost Savings Some questions discussed in the conference: • Can the pharmaceutical industry leverage knowledge management to reconfigure the pharmaceutical value chain and harness the fruits of research and development more effectively? • How can tools and technologies, ranging from portals to handheld devices, be efficiently used for communication, knowledge transfer, and sharing? • Does it make sense to talk of ‘knowledge factories?’ How should a company successfully innovate faster than its competition?

Industry Profile ‘Pharmaceutical companies offer a wide array of solutions on numerous platforms, bioinformatics, combinatorial chemistry, to a diverse range of customers, namely, pharmacies, hospitals, specialists, patients in several therapeutic categories. Thus, in the R&D process, KM challenges arise in each of the steps—basic research, target identification, lead discovery, pre-clinical research and registration’ said Thomas Schneider, senior manager of healthcare practices at Arthur D. Little. The consulting firm’s recent survey of 25 European healthcare companies revealed that their KM objectives included process integration and efficiency increases, but few companies had an overall clear KM roadmap. Deployed KM tools and activities include document libraries, mobile solutions, expert networks, KM scouts, job rotation and e-learning. Companies usually spend between 6 months to 2 years on conceptualizing and implementing a KM initiative. Success factors have included proper communication, expectation management, alignment with business needs and early involvement of the right and relevant people.

Quite a few notable successes have already emerged on the KM front in the pharmaceutical industry, particularly in terms of efficiency and innovation via methods like knowledge communities, portals, e-learning frameworks, and knowledge discovery. Some interesting success stories are mentioned below. “The speed of innovation is determined by experts’ awareness of new direction and opportunity, their ability to integrate knowledge into a teachable framework, and the organization’s ability to mobilise it,” said Victor Newman, CLO at Pfiser, and author of ‘The Knowledge Activist’s Handbook.’ “Companies should start thinking in terms of ‘return on experience’ and not just ‘return on investment,’ ” he advised. A learning database for e-learning is a good start for a KM system, but it should also intuitively and visually model the way experts pay attention and think about work. Pfizer’s Corporate University is structured to follow the ‘concept to commercialisation’ process, and not just aping traditional faculty structure. It has developed new learning techniques like ‘Baton Build and Passing’ and institutionalises new high value learning into orientation workshops. “If a company does not know what it knows, it has never had to explain it to anyone. If it knows what it knows, then this documented knowledge must be consistently renewed and reviewed. If the company knows what it does not know, then it must analyse knowledge lifecycles and capability gaps to expose it to new practitioner learning. And if a company does not know what it does not know, it must use techniques like intra-and inter-sector KM benchmarks,” explained Victor Newman, CLO at Pfizer. E-Knowledge building and e-Learning need to be put to work in tandem to create knowledge prototypes, stabilise knowledge assets, and mobilise acquired knowledge.” Solvay has set up an iterative audit of its KM initiatives based on the ‘5W + 2H’ rule (what, why, who, when, where followed by how, how much). The evaluation committee consists of different experts and is chaired by an outsider; the KM Steering Committee reports directly to the board. KM steering committee has classified KM projects into ten classes. KM projects fall into ten classes: • Benchmarking • Competitive intelligence • Workflow for sharing • CoPs • Organisational modeling • Organisation learning • Portals • Skills and Competencies • Knowledge based systems and idea box systems “From learning, I would recommend that KM practitioners work with motivated people, get top level support, and pay attention to individual learning issues. Technology is important, but should not be the first step. New technology + Old organisation = Costly old solution,” Vergison joked. Solvay has implemented an expert finder solution called X-Fert (cross fertilisation) for almost 500 employees. It has over 3,000 personal pages. 35 global communities of practice are connected to X-Fert, in countries ranging from the US and Thailand to Portugal and Argentina. Solvay has also implemented a KM-orientated document writing method to re-centre document creation on the strategic content of industrial processes, based on Robert Horn’s Information Mapping Method.

The Solvay Intranet (called Faros) was based on concepts developed by INSEAD’s Centre for Advanced Learning Technologies. Solvay’s Idea Box Portal has 250 facilitators in Europe alone. Awareness campaigns about KM were started in March 2002, with focused presentations, in depth training and mock-up exercises.

Communities of Practice Organisational communities can be of several types: personal networks, spontaneous communities, strategic communities, and centres of excellence. “Many leadership roles can arise in this context: community leader, thought leader, knowledge miner, subject matter expert, core group member,” said Richard McDermott, co-author of Communities of Practice. He advises, “It is important to align reward, recognition and career development.” A key role in this context is of the knowledge facilitator, according to Jonas Roth, Knowledge Manager at AstraZeneca. The facilitator must coordinate and catalyse knowledge creation, build a caring and stimulating climate, enable a sharing culture and be a guide to the company’s knowledge vision.

Internal and External Knowledge Strategies Knowledge driven drug development (KD3) can be used in clinical trial simulation to increase the chances of success and limit the number of clinical studies, according to Andreas Lohman, VP at Organon. KM can be used to optimise the RandD value chain with workflow management in areas like regulatory claim submission, said Rudiger Buchkremer, IT head at Altana Pharma, whose wide-ranging KM suite also includes news spiders, PDA-based content delivery, collaboration with external universities, and social knowledge activities like management development circles and experience exchange groups. “In the highly competitive pharmaceutical industry, speed and efficiency are crucial for drug development,” said Sven Vogelgesang, global head of clinical application services at Merck. Merck is a member of European consortia on management of corporate knowledge, and also conducts a KM Benchmarking Study with Berlin’s Fraunhofer Institute. It has a KM Competency Centre (km.merck. de) with members from different business units, and has implemented KM applications on its Intranet (“MerckNet”) like an Ideas Bank, Project Teams Databases, Blue Pages, Competitor Databases and Online Campus. “Our mission statement is to be number one through innovations created by talented, entrepreneurial employees, and KM helps in hiring the right people, training them, empowering them, and fostering innovation,” said Vogelgesang. The company has instituted a Merck Award Plan for inventions, a Merck Innovation Award, an employee suggestion scheme (20,000 improvement suggestions have been received since 1986). “Key barriers for implementing KM include inadequate awareness of information needs of colleagues, and missing overviews of the available knowledge sources” Vogelgesang observes. His key recommendations for other KM practitioners include, “Start with quick wins, choose measurable goals, conduct surveys on KM usefulness, communicate the benefits of KM and convey a sense of urgency”.

End Notes • One approach to knowledge management places greater emphasis on the cultural and behavioural aspects of the organisation. This approach believes that organisations are process driven and technology is of little use if the organisation lacks a knowledge sharing culture. • The other approach to knowledge management is more aided by technology, which includes internet, network and communication, database management, Information systems, information technology,

























embedded technology and host of others. It relies on technology and technology tools and products. It concentrates on providing efficient tools to capture, organise and access knowledge as well as to facilitate its delivery to the right people at the right time. KM technology is not a single solution but a group of tools based on groupware, expert systems, artificial intelligence, library science, document management, web, and so on. Notwithstanding this, KM tools are still a major step forward in our ability to manage the information glut. KM technology provides a mandatory knowledge management infrastructure to our businesses. Data warehousing is defined as a process of centralised data management and retrieval. Data warehousing represents an ideal vision of maintaining a central repository of all organisational data. Centralisation of data is needed to maximise user access and analysis. Data mining, sometimes called knowledge discovery, is the process of analysing data from different perspectives and summarising it into useful information-information that can be used in DSS to increase revenue, cuts costs, or both. Data mining software is an analytical tool for analysing business data. Technically, data mining is the process of finding correlations or patterns among dosens of fields in large relational databases. New findings about correlations or patterns is a knowledge revealing something new which otherwise may not be easily apparent. For example, summary information on retail supermarket sales can be analysed in light of promotional efforts to provide knowledge of consumer buying behaviour. Thus, a manufacturer or retailer could determine which items are most susceptible to promotional efforts. The need is for high quality knowledge, sourced from inside and outside the organisation and stored at one location. The work culture is becoming more collaborative team work, pooling expertise from within and outside organisation. Knowledge portals represent a solution to this challenge, as they provide a flexible knowledge environment to a potentially large number of users. The mission of a knowledge portal is not only to provide a library like pool of information, but to actively support the user in execution of business processes. The knowledge centre contains information about the quality management system, information related to different projects, related best practices and lessons learned, technology related white papers and tutorials. A marketing centre holds frequently asked questions by customers (the same is used by employees in sales and marketing). Additionally, case studies and templates for proposals and newsletters are also captured in the knowledge centre. A knowledge product is an artifact of information — a kind of persistent retention of the knowledge of one or more individuals. Knowledge products differ from other artifacts in that their relevant and useful aspects reside primarily in the content that can be extracted from them, and, as such, any physical manifestation, thereof, is usually at best a carrier medium. The organisations develop knowledge products, such as spread sheet models, templates, system models, charts, and diagrams for use in the organisation. Such products usage saves time, brings approach consistency in solving the problem and communication on the subject matter is easy and clear to all concerned. Intelligent agents (software agents) are programmes which carry out the requested tasks on behalf of users. The spectrum of capability of agents is wide, ranging from the basic level of automating



















straightforward routine tasks through to the ability to adapt to user routines and preferences, and even to negotiate on behalf of users. The feature which distinguishes agents from other programmes is the ability to automatically adapt their behaviour to the conditions they encounter, and to make decisions based on a set of inbuilt rules and criteria, without specific on-the-spot instruction from the user. Groupware is software that facilitates a group of people working together within the same system or application, no matter where they are located. Such groupware applications are commonly e-mail, newsgroups, and chat. Groupware applications tools that are commonly used include Lotus Notes, e-mail server systems, such as FirstClass and Microsoft Exchange, 24Seven Office, Livelink and Workspot. Groupware applications are divided into three categories: • Communication tools for messaging • Conferencing tools for transfer and sharing of knowledge • Collaborative work management tools Mobile groupware applications are becoming popular in the industry in the area of communication andworking together. Mobile applications with Groupware technology offer cost effective solutions and speed in execution of synchronous or asynchronous tasks. Mobile Meeting Scheduler (MMS) is an asynchronous groupware application. Key barriers for implementing KM include inadequate awareness of information needs of colleagues and missing overviews of the available knowledge sources. The key recommendations for KM practitioners include: start with quick wins, choose measurable goals, conduct surveys on KM usefulness, communicate the benefits of KM and convey a sense of urgency. Organisational communities can be of several types: personal networks, spontaneous communities, strategic communities, and centres of excellence. Many leadership roles can arise in this context: community leader, thought leader, knowledge miner, subject matter expert, core group member. It is important to align reward, recognition and career development. A key role in this context is that of the knowledge facilitator. The facilitator must coordinate and catalyse knowledge creation, build a caring and stimulating climate, enable a sharing culture and be a guide to the company’s knowledge vision. KM projects fall into the following types: • Benchmarking for ideal to achieve • Competitive intelligence to beat competition • Workflow systems for sharing knowledge • Evolving, forming CoPs • Organisational modeling • Organisation learning • Building portals • Developing skills and competencies, • Design knowledge based systems and idea box systems The speed of innovation is determined by experts’ awareness of new direction and opportunity, their ability to integrate knowledge into a teachable framework, and the organisation’s ability to mobilise it.

Questions 1. Data mining, sometimes called knowledge discovery, is the process of analysing data from different perspectives and summarising it into useful information-information that can be used in DSS to increase revenue, cuts costs, or both. Explain how DM can hunt the hidden knowledge in DWH, or in Data mart. 2. Consider a large medical shop of a very large hospital. Many times, it is observed that the patient’s prescription is not fully delivered in one stroke. Explain how DWH and data mining solutions can be used to overcome this problem. 3. A municipal corporation has a data of students of last five years. The data includes their performance in the school, family background, social standing, other members in the family, and whether they stay in own house or rented one and the size of the house. How can DWH and data mining technology be used to get insight into performance so that some strategies can be built to improve the same? 4. Why are knowledge portals important for the organisation? Explain the term Organisation memory. 5. What is the meaning of knowledge product? How it is used? What are the benefits of using knowledge product? Are you using any knowledge product? What benefits are experienced by you? 6. Digital Tutor is equivalent to Human Tutor. Digital tutor would be smart, subject to student’s learning profile pointing strengths and weaknesses, to select appropriate learning tools and learning resources. Identify the IA components in the Digital Tutor. 7. Alber’s Framework has following important steps, each with specific goals to achieve. If this framework is implemented, a business case for KM could be justified. Identify the goal set for each step. • Business strategy assessment • Knowledge assessment and its audit • Knowledge and business strategy alignment • Business opportunity identification • Knowledge value and its impact on business benefits 8. How is sense and respond strategy dependent on customer knowledge? 9. Can the industry leverage knowledge management to reconfigure the value chain? 10. How can tools and technologies ranging from portals to handheld devices be efficiently used? 11. Does it make sense to talk of ‘knowledge factories?’ How should a company successfully innovate faster than its competition?

Knowledge Management Vocabulary • Artificial Intelligence: A sub field of computer science which makes a computer behave like a human being. • Automated Knowledge: Explicit coded knowledge embedded in the system or device to act on conditions fulfilled. • Backward Chaining: This is a process or a system of decision making where “if-then” rule chain is used to move from one state to other. If the process hits a ‘then ‘condition the next step is guided by ‘if’ condition. The chain ‘then and if’ moving towards the goal is called backward chaining. For example, the goal is to offer a discount to the customer. Then, 5% discount is approved if ordered quantity is 100. Additional 5% discount is loaded if the customer is a special one. It is also called goal oriented reasoning. • Balanced Scorecard: A business model developed by Kaplan and Norton as a tool to measure organisational performance against both short and long-term goals. The balanced scorecard is designed to focus managers’ attention on those factors that most help the business strategy and so, alongside financial measures, it adds measures for customers, internal processes and employee learning. Some organisations have used the balanced scorecard model in setting and measuring knowledge management strategies. • Benchmarking: A process to compare where you stand with reference to the ‘best’ in another organisation or industry. The objective is to compare and make efforts to reach that level. • Best Practice: A process/method/ procedure tested and proven to give best results by known standards. • Case-based Learning: Approach to learning using “cases” (stories, scenarios, descriptions of real events, etc.) to illustrate the material to be internalised. Case-based learning is supportive of building mental reference models. • Case-based Learning: Learning from experience through case study and analysis to form models for reference and adoption. • Case-based Reasoning: A reasoning approach built from case experience for inference or judgment on the current state. • Closed System: A stand-alone system which is isolated from its environment. • Coaching: Mentoring through relationship to increase knowledge and improve performance in a limited time. • Cognitive Style: An individual’s mental approach and style of reasoning to select preferences. • Communities: People coming together informally to interact and share knowledge on a specific subject. Communities of interest or communities of practice are the example of communities who come together to share knowledge on a topic or practice. • Competence: The capacity and capability of a person to perform as effectively as desired. • Competitive Advantage: An entity or a factor that differentiates a person or a company from the others attracting more profit or better results. It is a differentiator. • Conceptual Knowledge: A mental model of abstract knowledge or an object. • Content Management: To ensure that content is relevant, up to date and complete, accurate and easily accessible. • Culture: An amalgamation of values, beliefs, biases, preferences of people influencing their behaviour, actions and decisions. Culture naturally gets reflected in policies, plans and strategies of the organisation.

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Knowledge Management • Customer Capital: It is the level of strength of relationship with customers built over a period of time, creating loyalty out of good service and support offered to them. It includes customer goodwill and willing obligation to be with organisation. • Data Mining: A technique to connect different data sets in a data warehouse revealing patterns and trends in the object under study. Data Mining is extraction of implicit, previously unknown, and potentially useful information from data bases. The process uses machine learning, statistical correlations, statistical analysis, and sophisticated search strategies to extract data in such a way that the information is easily comprehensible. Data mining is frequently used by marketing departments to learn more about customers and how to better market products and services. • Deductive Reasoning: In deductive reasoning you deduce background information, knowledge and premise from established hypothesis. It is the reverse of inductive reasoning. • Double-loop Learning: This is a process of solving the problem by questioning the assumptions, conditions and knowledge and change to solve the problem in a better manner. In this approach, learning gained by solving the problem updates the current knowledge base. • Episodic Memory: A memory which stores collections of events, impacts without integration. • Expert System: A computer based system where expert knowledge and intelligence is encoded into a process to solve a problem. It emulates human reasoning to solve the problem. It has knowledge base, inference engine and user interface. The expert system could be rule based or model based. • Explicit Knowledge: Explicit knowledge is the formal, recorded, or systematic coded knowledge in the form of scientific formulae, procedures, rules, organisational archives, principles, etc., and can easily be accessed, transmitted, or stored in computer files or hard copy. • Forward Chaining: This is a process or a system of decision making where “if-then” rule chain is used to move from one state to other. If the process hits an ‘if’ condition the next step is guided by ‘then’ condition. The chain ‘if and then’ moving towards the goal, is called forward chaining. For example, if a customer has ordered 100 pieces of a product, then discount is 5%. If customer is a business partner then an offer additional 5% discount is offered. This is also called goal directed reasoning. • Groupware: A software application suite where people work on network format in collaboration to achieve a goal. In the process they share and transfer knowledge. The groupware requires three networks—Computer network, people network and knowledge network. Groupware application is synchronous when the entire group completes the task in a few minutes and is asynchronous when group members play their role one after another to complete the task. In this application, information, knowledge, communication and documents are all shared among the group members. • Human Capital: Knowledge, skills, capabilities, expertise, functional knowledge of the HR is the human capital. • Inductive Reasoning: In inductive reasoning you generate a hypothesis based on knowledge and information such as premise, facts rules and so on. • Inference Engine: Inference engine is a software system which controls the reasoning of inference. Based on the knowledge in its repository, it assesses the situation, selects the rule, implements the rule and controls its outcome. • Intangible Assets: The non-physical resources of an organization, for example, brand name such as Mercedes or Microsoft, the loyalty of customers and vendors towards a company, the high ranking in the society. These assets are not generally accounted for in financial statements, but they are of great value to the organisation. • Intellectual Capital: It is the sum of an organisation’s human capital, structural capital and customer capital. • Intellectual Property: It is the patented licensed or trademark knowledge or products of an organisation.

Knowledge Management Vocabulary 331 • Knowledge Assets: Knowledge assets are of three kinds: human (people, teams, networks and communities), structural (the codified knowledge that can be found in processes and procedures) and technological (the technologies that support knowledge sharing such as databases and intranets). • Knowledge Codification: A process of converting people’s knowledge into some form whereby its transfer and sharing is easy. Models, structured procedures, manuals, diagrams, pictures, multimedia presentations are examples of knowledge codification. • Knowledge Codification: Knowledge codification deals with obtaining, characterising, and validating knowledge. The process of getting people’s knowledge into a form by which it can be communicated independently to the others. The most common method is writing things down and putting them into documents and databases. Other methods include pictures, and sound and video recordings. • Knowledge Economy: An economy where knowledge plays a dominant role. • Knowledge Engineering: The activities associated with acquiring, codifying, and encoding knowledge, conceptualising and implementing knowledge-based systems, and engaging in activities to formalise knowledge and its use in business management. • Knowledge Management Strategy: A plan of implementing principles and practices of knowledge strategy to achieve a business goal. • Knowledge Map: A map showing the storage of knowledge in the organisation and how to access it. It also shows how knowledge flows in the organisation. It identifies business-critical knowledge assets. A knowledge map is often displayed as a tree or graph, where the nodes are the names of knowledge assets or classes of assets. • Knowledge Repository: It is a storage where knowledge is gathered and made accessible to users. A knowledge repository could be an expert, a database, a folder or a portal. • Knowledge Representation: It is a structured representation of knowledge in the form of rules, semantic network, frames, schemas, templates, programs, models, diagrams, decision trees and so on. • Knowledge: Practically speaking, knowledge is “information in action” or “information transformed into the capability for effective action.” Taking action and building experience turns information into knowledge. • Learning Organisation: An organisation which is skilled in creating, acquiring, storing, transforming, sharing knowledge and improving it on a continuous basis based on the experience of its usage in business application. It modifies its behaviour based on renewed knowledge. Learning organisations advance and grow in a competitive environment. • Learning by Discovery: Searching new ideas and solutions by exploring a problem area. • Learning by Example: Acquiring new ideas and solutions by specially designed and constructed scenarios, models. • Learning by Experience: Finding new ideas and solutions; falling back on stored experience. • Open System: A system that is integrated with, and is continually influenced by its environment. • Organisational Learning: The ability of an organisation to gain knowledge from experience through experimentation, observation, analysis and a willingness to examine both successes and failures, and then to use it for innovation and business benefits. While organisational learning cannot happen without individual learning, individual learning does not necessarily produce organisational learning. Organisational learning occurs when an organisation becomes collectively more knowledgeable and skillful in pursuing a set of goals. • Single-loop Learning: This is a process of solving a problem based on the assumptions and knowledge currently available. It does not question the assumptions, conditions, models and knowledge. In single loop learning the present knowledge gets reinforced but does not change.

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Knowledge Management • Structural Capital: Structural capital is part of intellectual capital and includes all of the enterprise’s intellectual property and intellectual property rights. It includes technology, practices, organisational structure, patents, copyrights, and so on. It also includes an organisation’s “captured knowledge” such as best practices, processes, information systems, databases etc. This is the knowledge that remains in the organisation and is not mobile to leave the organisation with the employees. • Tacit Knowledge: Tacit knowledge is the personal knowledge resident within the mind, behaviour and perceptions of individual members of the organisation. It cannot be coded and stored in electronic media. • User Interface: The facility which supports bidirectional communication between the system and its user. Most user interfaces use natural language-processing techniques and bitmapped graphics. • Video Conferencing: A computer-based internet enabled system for face-to-face meetings without physically coming together in a room. It is supported by two-way full motion video and two ways audio. The members of the conference can see each other during the meeting.

References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.

Drucker, P.F. 1993, Post Capitalist Society, Butterworth-Heinemann. Davenport, T., Prusak L. (1998), Working Knowledge, Harvard Business School Press, Boston, MA. Krough, G., Ichijo K., Nonaka I. (2000), Enabling Knowledge Creation, Oxford University Press. New York. Nonaka, Ikujiro & Takeuchi, Hirotaka (1995), The Knowledge Creating Company, Oxford University Press, New York. Davenport, T. and Prusak, L., Working Knowledge: How Organizations Manage What They Know, Harvard Business School Press, 2000. Karl Sveiby, Strategy Formulation in Knowledge-Intensive Industries, International Review of Strategic Management, Wiley, 1992. Karl Sveiby, A Knowledge-based Theory of the Firm to Guide Strategy Formulation, Presented at ANZAM Conference, Macquarie University, Sydney, April 12, 2000. Yogesh Malhotra, Knowledge Management for E-Business Performance: Advancing Information Strategy to Internet Time, Executive’s Journal, V.16, No. 4, pp. 5-16, 2000. Newell, A., The Knowledge Level, Artificial Intelligence, No. 18, pp. 87-127, 1982. Michael Schrage, Inteview by Knowledge Inc, http://www.webcom.com/quantera/schrage.html Maturana and Varela, Autopoeisis and Cognition, London Riedl, 1980. Charles, M. Vest. (2001), MIT to make nearly all course materials available free on the World Wide Web, A press conference at MIT on Wednesday, April 4th. 2001. http://web.mit.edu/newsoffice/nr/2001/ocw.html Gundry, J. (1998), Knowledge Ability Ltd.: http://www.knowab.co.uk/km.html Laudon, K.C. and Laudon, J.P. (1998), Management Information System,. Prentice-Hall International Inc., New Jersey. Parlby, D. (1998), The Power of Knowledge: A Business Guide to Knowledge Management, KPMG Management Consulting: http://www.kpmg.com Robert S. Seiner, (2000), Knowledge Management: It’s Not All About the Portal, The Data Administration Newsletter, November 2000.

Index Acquisition, 168, 169 Agricultural Economy, 4 AOK, 17 Application, 48 Architecture, 287, 126 Area, 85 Asset, 209 Audit, 314 Barriers, 97 Benefits, 55,101 Business Case, 313 Business Intelligence, 40, 41, 275 Business Models, 9 Buyer Agents, 311 CEBP, 265 Challenges, 122 Codification, 197 Combination, 166 Competition Forces, 12 Components, 6 Creation, 35, 130, 160 Creativity, 37, 50 Customer, 50, 115 Customer Capital, 13, 53 Cycle, 75, 79, 80, 118 Data, 29, 33, 48 Data Mining, 43, 274, 297 Data Warehouse, 270, 272, 297 Delivery Model, 138 Digital Tutor, 312 DKCU System, 96 DWH Architecture, 271 Economy, 9-14, 19 Explicit, 44

Expression, 36, 37 Externalization, 165 Feasibility, 126 Fireplay, 310 Framework, 154 Generation, 90 Gilder’s law, 11, 9 Groupware Technology, 289, 311 Herbert Simon Model, 230 HRM, 247, 250 Human Capital, 13, 53 Human Capital Steward, 247 Human Learning, 39 IA, 278, 309 IA Model, 279 Iceberg Model, 147 ICT, 4, 11, 259 Identification, 149 Implementation, 74, 132, 135 Industrial Economy, 4 Industrial Society, 7 Information, 30, 33, 48 Initiative, 72, 216 Innovation Cycle, 70 Intellectual Capital, 13, 34, 210-212 Intellectual Capital Model, 214 Intellectual Property, 213 Intelligence, 38 Internalization, 166 Justification, 99 KAT, 177, 178 KMS, 112, 115, 148 Knowledge Management, 67, 71, 72

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Knowledge Management

Landscape, 68 Layers, 127-129 Learning, 137, 231, 260 Learning Organization, 229, 234, 241 Life Cycle, 123 Map, 153, 201 Mental Models, 238 Mentoring, 200 Metcalfe’s law, 9, 11 Model, 98, 111 Modelling business, 43 data, 43 dimension, 42 Moor’s law, 9, 11 Network Organization, 16 Networking, 15, 16, 82 New Growth Theory, 12 Oinas-kukk onen Model, 167 OLAP, 43, 276 Ontology, 43 OODA Loop, 165 Organization Knowledge, 245 Organization Learning, 243 Organization Structure, 233 PDCA Cycle, 230 People, 116 Personal Logic, 310 Philosophy, 33 Physical View, 121 Portal, 284 Process, 75, 77, 115, 136 Product, 51, 115, 288, 300, 306 Pull Model, 5, 14 Push Model, 4, 5

Relationship, 52 Search Engine, 277 SECI Model, 94, 165 Seller Agents, 311 Shared Vision, 235 Sharing 192,193, 195, 204, 205 Socialization, 165 Sources, 50 Strategic Approach, 14 Strategic Focus, 74 Strategic Resource, 52 Strategy, 206 Structural Capital, 13,53 SWOT Analysis, 150-152 Systems Thinking, 237 Tacit, 44 Team Learning, 236 Technology, 116 Technology Interaction, 120 Thematic Analysis, 86 Tools, 56, 57 Traditional Economy, 11 Transfer, 119, 189, 190, 195, 196, 208 Treatment, 91 Types, 40 UCT, 261, 312 Unified Communications, 262 Unified Workspace, 264 Validation, 156, 157, 161 Virtual Teams, 15 Wi MAX, 266, 268 WI-FI, 267 Wisdom, 38 Workers, 16, 18