Solving Managerial Problems Systematically [1 ed.] 9001887953, 9789001887957

Table of contents :
Cover
Title Page
Copyright Page
Foreword
Table of Contents
1 A Framework for The Best Solution
1.1 Characteristics of the Managerial Problem-Solving Method
1.2 Systematic or Creative Approach?
1.3 Phases of the Managerial Problem-Solving Method
1.4 MPSM Works Anywhere, Anytime
1.5 Tailored to Your Problem
1.6 The Language of Variables
1.7 Framework
1.8 Researching and Designing in One
Summary
Core Concepts
2 Untroubled Problems
2.1 Types of Problems
2.2 Problem as an Analytical Concept
2.3 Action Problems
2.4 Knowledge Problems
2.5 Linking Action and Knowledge Problems
Summary
Core Concepts
3 A Trouble-Shooter’s Log
3.1 The MPSM in Practice
4 In Search of the Core Problem
4.1 Reaching the Core Problem, Step by Step
4.2 Lining Up the Problems
4.3 Cause and Effect
4.4 Choosing the Core Problem
4.5 Making Problems Quantifiable
Summary
Core Concepts
5 D3: Do, Discover, Decide
5.1 Three Principles of a Plan of Attack
5.2 D3 Explained
5.3 Benefits of a Systematic Approach
5.4 Walking A Thin Line
Summary
Core Concepts
6 In Search of the Unknown
6.1 Looking Closely at the Problem
6.2 Locating the Problem
6.3 Researching Causes
6.4 Considering Earlier Solutions
Summary
Core Concepts
7 An Overview of Options
7.1 Seven Steps to a Possible Solution
7.2 Defining the Decision
7.3 Defining the Decision-Making Process
7.4 Establishing Criteria
7.5 Scaling Criteria
7.6 Weighting Criteria
7.7 Providing Alternative Options or Using Existing Possibilities
7.8 Evaluating the Attractiveness of Available Options
Summary
Core Concepts
8 The Client’s Move
8.1 Three Reasons for Deviating from an Advisory Report
8.2 Politically Charged Decisions
8.3 Considering Other Interests
8.4 Handling Risks
Summary
Core Concepts
9 A Systematic Approach
9.1 Two Principles of Implementing a Solution
9.2 A Brief Description
9.3 Realising an Idea
Summary
Core Concepts
10 Keep Improving
10.1 Three Principles of a Structured Evaluation
10.2 Evaluation as a Balancing Item
10.3 MPSM: Guiding Along the Path of Evaluation
10.4 Evaluating Systematically
Summary
Core Concepts
11 In Search of Knowledge
11.1 Gathering Knowledge Using the Research Cycle
11.2 Formulating the Research Goal
11.3 Formulating the Problem Statement
11.4 Formulating the Research Questions
11.5 Formulating the Research Design
11.6 Performing the Operationalisation
11.7 Performing the Measurements
11.8 Processing the Data
11.9 Drawing Conclusions (Reviewing the Problem Statement)
Summary
Core Concepts
Sources
Illustration Acknowledgements
Index
About the Authors

Citation preview

© Noordhoff Uitgevers bv

Solving Managerial Problems Systematically Hans Heerkens Arnold van Winden Translated into English by Jan-Willem Tjooitink Noordhoff Uitgevers-Groningen/Houten

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Cover design: G2K Designers, Groningen, The Netherlands Cover illustration: Stocksy

If you have any comments or queries about this publication, please contact Noordhoff Uitgevers bv, Afdeling Hoger Onderwijs, Antwoordnummer 13, 9700 VB Groningen, The Netherlands. E-mail: [email protected] The greatest care has been taken in the preparation of this publication. The authors, editors and publishers cannot be held liable in case any information has been pub-lished incompletely or incorrectly. If you feel that your rights as a copyright owner have been infringed, please contact Noordhoff Uitgevers bv. They will be pleased to receive any adjustments to the contents.

0 / 17 © 2021 Noordhoff Uitgevers bv, Groningen/Houten, The Netherlands Apart from the exceptions provided by or pursuant to the Copyright Act of 1912, no part of this publication may be reproduced, stored in an automated retrieval system or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior written approval of the publisher. Insofar as the making of reprographic copies from this publication is permitted on the basis of Article 16h of the Copyright Act of 1912, the compensation owed must be provided to the Stichting Reprorecht (P.O. Box 3060, 2130KB Hoofddorp, The Netherlands, www.reprorecht.nl). To use specific sections of this publication for anthologies, read-ers or other compilations (Article 16 of the Copyright Act of 1912), contact Stichting PRO (Stichting Publicatie- en Reproductierechten Organisatie, P.O. Box 3060, 2130 KB Hoofddorp, The Netherlands, www.stichting-pro.nl). ISBN 978-90-01-88795-7 (pbk) ISBN 978-10-32-02964-1 (hbk) ISBN 978-10-03-18603-8 (ebk) NUR 801

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Foreword

Problem-solving is part of all fields of study and all corporate sectors. Knowledge of the relevant subject or industry is indispensable, but can only get you so far. A systematic problem-solving approach can be an invaluable aid in dealing with problems. This book focusses on the Managerial Problem-Solving Method (MPSM), a tried and true problem-solving method which can be applied to various problems occurring in a multitude of situations in all subject areas. Solving Managerial Problems Systematically is a book for students, advisors, and managers who want to solve complex practical problems without the problem-solving method forcing them into a straightjacket. The MPSM provides a framework for problem-solvers, and lets them decide which tools from existing managerial theory they want to use. MPSM is a problemsolving method that provides a path to a solution, step by step. It helps trouble-shooters arrive at solutions by ticking the boxes on a methodological checklist, and teaches them to differentiate between knowledge and action problems. The Language of Variables ensures that researchers remain concrete, helping them to consciously weigh up alternatives and obtain answers to questions they had not yet thought to ask. The MPSM encourages its users to take advantage of their intuition. The MPSM combines knowledge obtained through thorough research with systematic problem-solving. Creative techniques are used as an aid in coming up with solutions to problems. The first two chapters of this book cover the MPSM as a whole. Chapter 3 is a stand-alone, a fictional story that uses the notes in a trouble-shooter’s log to describe the way the MPSM is used to solve a managerial problem. The next seven chapters discuss each of the method’s particular phases, followed by Chapter 11 which covers the research cycle – a recurring element found throughout the use of the MPSM. This book does not go into a scientific or philosophical justification of the method. The MPSM’s usefulness and underlying logic become apparent to the reader without discussing theories posed by other authors. But there are several literary references – so pick up a book from the bibliography if you are interested in certain components of the problem-solving approach. They may help by sparking new ideas for dealing with something that is not going the way it should. As you read, you will find that much of what is discussed in this book is based on existing knowledge. Not all of the individual parts of the MPSM are brand new. This book is a way of combining theories and methods into a practical reference work for dealing with all sorts of managerial problems, from the seemingly easy to the truly complex.

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Our thanks go out to Business School Netherlands (BSN), Buren, the Netherlands, one of the driving forces behind this book. Several years ago, BSN invested in our book ‘No problem, an approach to all managerial questions and mysteries’, which was used as a basis for this book. Enschede, Nieuwegein, the Netherlands, Summer of 2016 Hans Heerkens, Arnold van Winden

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Table of Contents

1

A Framework for The Best Solution 9

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8

Characteristics of the Managerial Problem-Solving Method 11 Systematic or Creative Approach? 11 Phases of the Managerial Problem-Solving Method 12 MPSM Works Anywhere, Anytime 13 Tailored to Your Problem 13 The Language of Variables 13 Framework 14 Researching and Designing in One 15 Summary 16 Core Concepts 17

2

Untroubled Problems 19

2.1 2.2 2.3 2.4 2.5

Types of Problems 21 Problem as an Analytical Concept 21 Action Problems 21 Knowledge Problems 23 Linking Action and Knowledge Problems 23 Summary 26 Core Concepts 27

3

A Trouble-Shooter’s Log 29

3.1

The MPSM in Practice 36

4

In Search of the Core Problem 39

4.1 4.2 4.3 4.4 4.5

Reaching the Core Problem, Step by Step 41 Lining Up the Problems 41 Cause and Effect 42 Choosing the Core Problem 43 Making Problems Quantifiable 46 Summary 50 Core Concepts 51

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D3: Do, Discover, Decide 53

5.1 5.2 5.3 5.4

Three Principles of a Plan of Attack 55 D3 Explained 55 Benefits of a Systematic Approach 56 Walking A Thin Line 57 Summary 58 Core Concepts 59

6

In Search of the Unknown 61

6.1 6.2 6.3 6.4

Looking Closely at the Problem 63 Locating the Problem 63 Researching Causes 63 Considering Earlier Solutions 67 Summary 69 Core Concepts 70

7

An Overview of Options 73

7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8

Seven Steps to a Possible Solution 75 Defining the Decision 75 Defining the Decision-Making Process 75 Establishing Criteria 77 Scaling Criteria 78 Weighting Criteria 79 Providing Alternative Options or Using Existing Possibilities 84 Evaluating the Attractiveness of Available Options 86 Summary 88 Core Concepts 89

8

The Client’s Move 91

8.1 8.2 8.3 8.4

Three Reasons for Deviating from an Advisory Report 93 Politically Charged Decisions 93 Considering Other Interests 94 Handling Risks 95 Summary 97 Core Concepts 98

9

A Systematic Approach 101

9.1 9.2 9.3

Two Principles of Implementing a Solution 103 A Brief Description 103 Realising an Idea 103 Summary 105 Core Concepts 106

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10

Keep Improving 109

10.1 10.2 10.3 10.4

Three Principles of a Structured Evaluation 111 Evaluation as a Balancing Item 111 MPSM: Guiding Along the Path of Evaluation 112 Evaluating Systematically 112 Summary 114 Core Concepts 115

11

In Search of Knowledge 117

11.1 11.2 11.3 11.4 11.5 11.6 11.7 11.8 11.9

Gathering Knowledge Using the Research Cycle 119 Formulating the Research Goal 119 Formulating the Problem Statement 120 Formulating the Research Questions 122 Formulating the Research Design 123 Performing the Operationalisation 125 Performing the Measurements 126 Processing the Data 127 Drawing Conclusions (Reviewing the Problem Statement) 128 Summary 129 Core Concepts 131 Sources 132 Illustration Acknowledgements 133 Index 134 About the Authors 135

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1

1

A Framework for The Best Solution

Which is more effective: tackling a problem systematically or doing so creatively? Using the MPSM, an acronym of Managerial Problem-Solving Method, you can apply a systematic approach to your work while still retaining creativity. This chapter addresses the following questions: * How can a creative and a systematic approach complement one another? * What types of problem can the MPSM be used for? * At what point in your problem-solving approach do you start conducting research? * Why does the MPSM work?

Managerial Problem-Solving

The Language of Variables 14

Method 11

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How to Find a New Violinist 1

After 43 years of loyal service, violinist Albert closes the lid on his violin case for the very last time. The regional symphonic orchestra will have to start looking for a new violinist. But the members of the strings section are divided on how to proceed. A number of musicians prefers a systematic approach, with a list of prerequisites for potential new recruits. Others would rather focus on finding a virtuoso artist, someone who plays from the heart; they are less interested in credentials. The chief conductor asks both sides to come up with a well-founded proposal. Those favouring the systematic school of thought feel that a new violinist should be a graduate of an academy of music. Applicants should have at least five years’ experience in a large orchestra. Neither famous violin concertos by great composers nor more obscure works by lesser giants should hold any secrets for them. The requirements are to be published in an advert. A selection commission, consisting of the conductor, a first violinist, and a cellist, will be reviewing new applicants based on an established checklist of requirements. Whoever meets these requirements demands best will get the job. The second group opts for a different approach. These musicians aim to publish an announcement in a major national newspaper. They are looking for a violinist who plays ‘from the heart’. Any musicians interested in being part of the orchestra can come by next Wednesday afternoon to present their performance. The strings section will then decide which applicant would best fit the orchestra.

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Which approach should the chief conductor go for? The systematic approach has a high chance of yielding a performer capable of handling the work. The creative approach, on the other hand, may uncover some homeschooled musical marvel – a passionate violinist who would have otherwise been overlooked. Put it like that, and the creative approach would seem to have the most benefits. But it does come with some risks. What if the ‘brilliant’ violinist plays a soulful and touching rendition of a piece by Vivaldi at the Wednesday afternoon audition, but then utterly butchers a sonata by Bach during an official recital? Are they familiar enough with the violin score? Are they fast enough when it comes to reading musical notes or rehearsing for new performances? The final decision is left to the chief conductor. Both options have their own advantages and disadvantages. So he chooses a third option: a combination of the two methods. Any interested violinist is invited to demonstrate their skill on Wednesday afternoon, on one condition: they have to be a graduate of an academy of music. Based on performance, the orchestra will choose the most passionate violinist who, happily, also meets the minimum prerequisites for playing in an orchestra. For a while, the chief conductor considered inviting all comers, and having them take an academic level test. But that approach would take up a lot of time – time the chief conductor does not have.

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§ 1.1

A FRAMEWORK FOR THE BEST SOLUTION

Characteristics of the Managerial ProblemSolving Method Some people refuse to enter a supermarket without a grocery list. If a job needs doing well, they will swear by using an established plan of attack or a solid script. Others rely on their creativity and adaptability. They tend to work based on circumstances. They need some elbow-room to arrive at better solutions. So how can you work systematically without losing out on creativity? This chapter introduces the Managerial Problem-Solving Method (MPSM). These are the characteristics of the MPSM: * The MPSM is a method in which the creative and the systematic complement each other * The MPSM is divided into seven phases * The method can be used anywhere and at any time * Problems are handled in their organisational context * Problems are expressed in terms of variables * The MPSM is an adaptable framework * There MPSM is a method in which investigating and trouble-shooting meet

§ 1.2

11

1

Managerial Problem-Solving Method (MPSM)

Systematic or Creative Approach? The MPSM is not stringently rigid, but a framework for you to fill in as you need. Without requiring too much complicated prior knowledge, it allows you to reach solutions to managerial problems in a variety of situations. But you do need to know how you can apply the MPSM’s methodology in a meaningful manner. Which is best: a systematic or a creative approach? Think of it as a choice between putting your money into investments, or into a savings account. Investing money can help you increase your funds more rapidly than saving money at a bank. But the reason not everybody has fully poured their own capital into investments is because investing comes at a greater risk. This is similar to using a creative approach to solve a problem. You may come across imaginative solutions, frequently better than what a systematic approach could have yielded. But there’s a relatively greater chance that your inventive idea will not be practical, or simply does not work. So should you revert to the systematic approach? A systematic approach is one that looks for a good, practicable solution in a stepwise manner. But that solution is not necessarily the best possible answer to your problem. A company that wishes to excel needs something more. If all companies in a certain field were to use the systematic approach, they could all arrive at the same solution, with the same advantages, using the same strategies. In that case, a systematic approach has done nothing for a company in terms of profiling, of distinguishing itself from the competition. A competitive advantage cannot be achieved by a systematic approach alone – if it could, the systematic approach would be all anyone would use. A creative approach has major potential rewards, but a relatively greater risk of failure. There are rarely any brilliant strokes of luck involved in the outcome of the systematic approach, but it will generally yield acceptable

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results. It is not always possible to say which of the two approaches will work the best beforehand. In some specific cases, there may be a clear preference. In practice, it is often convenient to opt for a systematic approach while also applying your creativity during certain stages. Think, for example, of developing a name for a new model of car. You start with a list of requirements – as systematically as possible. Using books on marketing and brand management, you establish your demands, i.e. what you expect from a car’s name. Then, you select whatever criteria you feel are relevant. For example, the new name should follow a similar pattern as earlier models by the same manufacturer. Once you have established you list of demands, it is time to start thinking of names – time to get creative. In a brainstorming session, you come up with as many names as you can. Then you switch back to the systematic approach. You verify your potential names against the list of established requirements. You pick whichever best fits the bill. Following this line of reasoning, it should come as no surprise that Vauxhall produces a car called the Cascada. That name fits in perfectly well with Vauxhall’s established range of seemingly Latin names ending in -a used for their other cars: Corsa, Astra, Meriva, Insignia and Zafira. The Managerial Problem-Solving Method allows you to embark on necessary creative jaunts within a systematic approach to a problem. Those excursions can be essential for reaching quality solutions. The creative approach is most prevalent in phase 4 of the MPSM; the phase where you look for alternative solutions. The systematic approach and the creative approach are not contradictory; instead, they are complementary. Depending on the situation, use either a systematic approach, a creative approach, or a combination of the two. The MPSM lets you do whatever best serves your purpose.

1

§ 1.3

Phases of the Managerial Problem-Solving Method The MPSM is one of several systematic problem-solving approaches. Developed by the University of Twente, the MPSM is based on several different problem solving methods. The MPSM consists of the following seven phases: 1 Defining the problem 2 Formulating the approach 3 Analysing the problem 4 Formulating (alternative) solutions 5 Choosing a solution 6 Implementing the solution 7 Evaluating the solution When using the MPSM for problem-solving purposes, you follow the seven phases sequentially – but you may have to backtrack on occasion, too. It is quite possible to find that the problem you established in phase 1 does not manifest itself as you thought it did once you reach phase 3. This could mean you need to return to phase 1, and review your initial diagnosis. All in all, this approach looks neither very new nor original. The MPSM does not appear to deviate substantially from existing problem-solving methods.

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13

Investigating, analysing, concluding, implementing and evaluating; they are all there. And yet, the MPSM is different from other, often more limited problem-solving models.

§ 1.4

MPSM Works Anywhere, Anytime

1

There are methods which only apply to a certain field or area of expertise. Look at Van den Kroonenbergs technical problem-solving model, for example. Building a bicycle becomes a piece of cake using this detailed method for designing tools or equipment. But it gets you nowhere if what you want to design is an organisation. Another example: Strategic management uses a variety of models designed specifically for a single purpose. Think of the SWOT analysis, Porter’s five forces model, or a fishbone diagram. Each is a very convenient tool for a specific situation – but they all have their limits in terms of applicability. The MPSM is a more general method, applicable for various problems encountered in various situations in all areas of expertise. It has helped a waste management company solve an issue with working hours which did not fit with garbage truck routes; mathematics alone was not enough to solve this logistical puzzle. MPSM’s consistent approach helped make an airport better suited to certain types of aircraft. It has improved productivity of packaging machines. The MPSM can be used anywhere, anytime.

§ 1.5

Tailored to Your Problem Many problem-solving methods are only concerned with whatever solution technically solves the problem. Established powers and concerns in an organisation are not investigated. Who has access to what information? What does the decision-making process look like, and how does it work? What is going on behind the screens? There are many and frequently unclear aspects involved, many or all of which may, to some greater or lesser extent, be responsible for the problem. Power factors are not explicitly covered by the MPSM - these are already touched upon when defining the problem. Using the MPSM, you will find that no problem is an isolated issue. Any problem is a problem in the context of an organisation. The MPSM takes that into account, thereby guiding you to a tailored solution.

§ 1.6

The Language of Variables In some models, the same arrow indicator is used to describe a causal link here or a sequential order there, before suddenly representing a hierarchical relationship between different employees. As a result, objects, activities, and variables can become muddled. The MPSM does not suffer from this problem. Using the MPSM, reality is expressed in variables – and variables only. Formulating these variables carefully allows you to establish inconsistencies in your analyses quite easily. Even the most intricate problem-solving approaches become easy to untangle.

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Language of variables

1

Reality is more than variables. This is also true for the harsh reality of any problem. Nevertheless, the MPSM restricts itself to the so-called language of variables. Both problems and reality itself are only expressed in terms of variables. The reason for that is simple: if you cannot express something in terms of variables, then it cannot contribute to a solution… nor can it be a problem. Restricting yourself to variables lets you structure a problem clearly, which helps you visualise it in a model. If you then use arrows to connect individuals - actors, as the jargon has it – to the variables, discerning the actual problem becomes rather difficult. Figure 1.1 is an example of a scheme in which we see both variables and actors. Relationships are depicted between actors (management and employees) and variables (productivity and profit). This makes identification of problems (causes and effects) difficult. What does the relationship between management and employees mean? Employees are not a cause of productivity; instead, a characteristic of employees is that they attain a certain level of productivity. So, in this case, productivity is a characteristic (variable) of employees. The arrow that should be there between productivity and profit is actually nowhere to be found. This means it has become difficult to identify the problems. Hence, this scheme is not a good model. If there were an arrow between productivity and profit, it would be clear that productivity was the cause of profit. Then, we would have identified two problems and the scheme (without the objects) would have been a good model.

FIGURE 1.1

§ 1.7

Connections between actors and variables

Employees

Productivity

Management

Profit

Framework Many problem-solving methods require thorough and dedicated study before you can use them to go anywhere near an actual problem. For example, getting to grips with Mintzberg’s configurations, complete with their coordination mechanisms, feedback loops, and design parameters can take a while. And by the time you do, you will not yet have made any progress with the problem itself. The MPSM, on the other hand, sets itself apart by its simplicity. You do not need to know the seven phases by heart; a global idea is all you need - as long as you have this book at hand. The phases of the MPSM are the basis for you own problem solving approach. You should look at this approach as a framework, a grid for you to fill in as you want. Each of the phases allows you to use different models, techniques and methods to your hearts content. This lends itself to

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A FRAMEWORK FOR THE BEST SOLUTION

methods used in project management. If you are looking into connections and causes (phase 3), McKinsey’s 7S-model (Athos & Pascal 1982 and Peters & Waterman 1982) can be a useful tool. If you are trying to come up with alternative solutions (phase 4), you may benefit from creativity supporting techniques such as brain storming sessions or mind maps. Every phase in the MPSM lends itself to the use of convenient tools and instruments from the various management theories. It is a general approach which allows enough room to use different, specific instruments as needed.

§ 1.8

15

1

Researching and Designing in One Most books on methodology are concerned with research methodology, which centres on how to acquire knowledge and information. A minority of methodological literature is concerned with designing, with solving practical problems. In this book on the MPSM, research and design go hand in hand. You are unlikely to research a problem for the sheer joy of it. The goal of nearly all research is to contribute to resolving a situation you are unhappy with. In order to come to grips with a problem, you need knowledge. In order to get knowledge, you conduct research; you investigate. Using existing literature, you can certainly go some way when it comes to researching or designing solutions. But getting the two to mesh can be quite a hassle. It starts with formulating complex situations in an organisation in terms of problems that are both relevant and manageable. What sort of knowledge do you need for your research? If you are able to come up with a suitable problem definition, you will soon be faced with new obstacles: how are you going to use your new-found knowledge? Why did you conduct research in the first place? The MPSM helps you ensure that your research is useful and lets you assist in solving problems for companies and non-profit organisations.

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Summary 1

▶ The Managerial Problem-Solving Method allows you to embark on necessary creative jaunts within the systematic approach to a problem. These excursions are a requirement for reaching quality solutions. ▶ The MPSM is one of several systematic problem-solving approaches. When using the MPSM, you follow the steps described in these seven phases: * Defining the problem * Formulating your approach * Analysing the problem and asking questions. What is the nature of the problem? What is causing it? Why are any existing solutions not used? * Formulating (alternative) solutions * Choosing a solution * Implementing the solution * Evaluating the solution: did it work? ▶ The MPSM is applicable to various problems encountered in various situations in all areas of expertise. ▶ The MPSM takes into account that no problem is an isolated issue. A problem is embedded in the context of an organisation, and needs a fitting solution. ▶ Using the MPSM, you express a problem in terms of variables. Formulating these variables carefully allows you to establish inconsistencies in your problem-solving work quite easily. ▶ The MPSM should be considered a framework, a grid for you to fill in as you need. Each of the phases allows you to use different models, techniques and methods for a custom problem-solving approach. ▶ In this book on the MPSM, research and design go hand in hand. The goal of nearly all research is to contribute to resolving a situation you are unhappy with. In order to come to grips with a problem, you need knowledge. The MPSM helps you ensure that your research is useful and lets you assist in solving problems for companies and non-profit organisations.

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Core Concepts 1

Managerial ProblemSolving Method

A problem-solving method for managerial problems that uses both creative and systematic approaches, such as investigating and resolving. There are seven phases to the MPSM, which you follow step by step: 1 Defining the problem 2 Formulating your approach 3 Analysing the problem and asking questions. What is the nature of the problem? What is causing it? Why are any existing solutions not used? 4 Formulating (alternative) solutions 5 Choosing a solution 6 Implementing the solution 7 Evaluating the solution: did it work?

The Language of Variables Expressing problems in terms of variables. You untangle an issue and define it as a series of variables, measurable attributes. Some variables can only be measured using indicators.

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2

Untroubled Problems

2

What exactly is a problem? And how can it be solved? By using a systematic problem-solving method or by conducting research? The MPSM bridges the gap between action and knowledge problems. This chapter addresses the following questions: * What is an action problem? * What is a knowledge problem? * What is the link between action and knowledge problems?

Action problem 21

Knowledge problem 23

Discrepancy 22

Research population 23

Problem owner 22

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Lacking in Drive

2 Mr Stark, general director at a production company, has come to feel that his employees are insufficiently motivated. The reality deviates from the norm; in other words, there is a discrepancy. However, Mr Stark is unsure as to the size of this discrepancy. He has reached out to an expert in the field, who has been given the task of coming up with measures that will increase motivation all-round. During the initial brief between the director and the advising consultant, Mr Connoté, the following conversation takes place: Director Stark: ‘I am not satisfied. The staff is not properly motivated. We need to get that motivation up.’ Consultant Connoté: ‘How low is the level of motivation?’ Director Stark: ‘Lower than it should be.’ Consultant Connoté: ‘And how high would you like it to be?’ Director Stark: ‘Higher than it is now.’ So what is Mr Connoté to do? There is not a scrap of hard data available. He has been tasked with solving a problem which is based on nothing but someone’s gut feeling. That hardly qualifies as evidence. Mr Connoté’s brow furrows, but he resolves not to ignore the perceived ‘problem’. ‘Where there is smoke, there is a fire,’ he

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thinks. Connoté sets to work. His first order of business is to establish how low (or high) levels of motivation currently are. That is a knowledge problem. He needs to find a way to measure motivation. One way would be to check to what extent employees are willing to work overtime, and compare those figures to surveys taken at competing companies… if similar surveys even exist. Connoté can also check employee absenteeism or turnover figures. Together with the director, Connoté establishes a ‘motivation benchmark’ using the indicators of absenteeism, turnover, and overtime. Connoté rounds off his investigation. His conclusion? Based on the benchmark established in consultation with the director, employee motivation levels are, in fact, not below par after all. The indicator values do not deviate from those found at competing companies. Which means there is no action problem after all. Mr Connoté reports his findings to the board. Job done. The solution to the knowledge problem has made further action unnecessary. But it could have gone a different way. If Connoté had concluded motivation levels were indeed too low, there would have been an action problem after all; one for him to solve.

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UNTROUBLED PROBLEMS

Types of Problems Problems mean worried faces, tear-stained pillows, and general misery. Problems keep people up at night. Problems are bothersome, complicated, inconvenient, and occasionally slightly mysterious. There are many faces to ‘the unsolvable’. Our language has numerous synonyms for the word ‘problem’: an impediment, an obstruction, a complication, a difficulty, a dilemma, a matter, a puzzle, an issue, or a question. Solving a managerial problem does not involve feelings of sadness, or other emotions for that matter. It is simply to do with not liking or not knowing something. This chapter considers the problem to be a purely analytical concept. You will become more acquainted with both action and knowledge problems, and with how the two are connected.

§ 2.2

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2

Problem as an Analytical Concept All problems share a common denominator: Once you have one, you will want to get rid of it. It does not matter whether the problem refers to someone’s (love) life, laptop, or production line. Some people are skilled at passing off their problems onto others. Some people try to sweep their problems under the rug. Whoever you may be – nobody enjoys being a problem owner. One small comfort: there have been others before you. Take heart in the many witticisms and profundities left to our troubled world by a great slew of pundits, poets, and philosophers, such as: ‘Problems are only opportunities in work clothes’ (Henry J. Kaiser, quotes.net), ‘No problem can be solved from the same level of consciousness that created it’ (Albert Einstein, quotes.net), ‘All progress is precarious, and the solution of one problem brings us face to face with another problem’ (Martin Luther King, Jr., quotes. net), or: ‘If a problem has no solution, it may not be a problem, but a fact not to be solved, but to be coped with over time’ (Shimon Peres, quotes.net). Philosophical discussions about problems tend to pass many people by in favour of the real thing. Students, advisors, or managers, for example, can actually see something going wrong. Think of a negative cash flow, declining returns on investments, or underutilisation of production capacity. Whatever it is, it is not what they want or expect it to be. And, importantly: They are looking for a solution. To their minds, a problem is not some tragic happening, but an adversary to be faced head on. They sink their teeth into the matter, looking for unknown causes and not letting go until all ‘mysteries’ are unravelled. That includes (re)investigating the illogical and the easily explicable; whatever it takes to make the problem go away. A neutral and carefree approach turns any problem into an analytical concept. Something you do not like or do not know; an action problem or a knowledge problem, as they are known in the jargon.

§ 2.3

Action Problems Anything or any situation that is not how you want it to be, is an action problem. It is where reality deviates from your norm. An action problem is having a fiver in your wallet when you actually need a twenty. You are only a quarter of the way towards your goal. And you may want to do something

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Action problem

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about it, for example by looking for a job or borrowing money. You take action in order to solve your problem. Alternatively, you can choose not to do anything at all. You let things lie. You settle for your fiver, in effect lowering your norm by 75%. As a result, there is no longer a difference between your norm and reality; there is no longer a problem. Doing nothing is still doing something; it is adjusting your norm to reality. No muss, no fuss. 2 The definition of an action problem is as follows: Discrepancy

An action problem is a discrepancy between the norm and the reality, as perceived by the problem owner. Action problems occur whenever things do not go your way. You expect your sales people to realise a 40,000-euro turnover every month. But figures for the first half year show a monthly turnover of barely 25,000 euros. There is a discrepancy between your 40,000-euro norm, and the actual 25,000-euro turnover per employee per month.

Problem owner

The problem owner is whatever entity, be it a person, a group, or an organisation, feels that a certain problem exists. Action problems express both the norm and reality in terms of variables. Variables are characteristics of people or organisations. In the turnover example, you are the problem owner and the variable is expressed as the monthly turnover per employee. These observations seem obvious. In practice, though, they may lead to uncertainties. How did you decide on your norm? Why did you select this variable? And how do you quantify your variables? These are all difficult, practical questions. Chapter 4 discusses the concept of variables used in phase 1 in greater detail. An action problem never occurs on its own. Sales can be low while productions costs are high. The one may be connected to the other. A useful tool to establish whether problems are connected is the problem cluster, sometimes known as problem bundle (see chapter 4, figure 4.1), a model which uses arrows to indicate existing connections between problems in terms of cause and effect. Connections established, you can choose which problem to solve. Whichever problem you select (note that how to do so will be explained later in the book) becomes the ‘core problem’. You can deal with multiple core problems at once, provided you have the time and resources you need for your approach. But make sure you set your priorities; each core problem must receive enough attention at the right time. Managerial Problem-Solving Method Action problems can be solved using many different methods. This book focusses on the Managerial Problem-Solving Method (MPSM), which consists of seven phases: 1 Defining the problem 2 Formulating your problem-solving approach 3 Analysing the problem 4 Formulating (alternative) solutions 5 Choosing a solution 6 Implementing the solution 7 Evaluating the solution

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Knowledge problem

UNTROUBLED PROBLEMS

Knowledge Problems Something is not right. You encounter a situation you want to change – you want to improve it. In this case, you are faced with an action problem. In other cases, the problem may have to do with information: something you do not know or do not understand. That means you will have to conduct research in order to obtain knowledge. You are looking to solve a knowledge problem. The definition of a knowledge problem is as follows:

Research population

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2

A knowledge problem is a description of the research population, the variables and, if necessary, the relations that need to be investigated. A knowledge problem concerns learning something about the world around you. It involves a part of reality. For example, you want to find out monthly turnover figures per sales employee. Or you may want to investigate relationships between variables, such as the connection between monthly turnover per sales employee and sales employees’ current length of employment. The research population consists of the person(s), group(s), or organisation(s) that are the subject of the investigation; the subjects you wish to know something about. In the previous example, the sales employees are the research population. Monthly turnover per sales employee and length of employment are the variables. The relation you are investigating is the possible connection between monthly turnover and length of employment. Knowledge problems can be descriptive or explanatory in nature. You may want to know the what, without needing to know the why – for example when looking to find out monthly employee turnover. For other knowledge problems, the why may be just as important as, or even more important than, the what – for example when investigating what factors influence monthly employee turnover. Research Cycle Knowledge problems are not about changing a situation. You are only interested in information. Your knowledge is gathered through research. The procedure for solving a knowledge problem is known as a research cycle. This cycle consists of eight phases: 1 Formulating the research goal 2 Formulating the problem statement 3 Formulating the research questions 4 Formulating the research design 5 Performing the operationalisation 6 Performing the measurements (gathering data) 7 Processing the data 8 Drawing conclusions (reviewing the problem statement)

§ 2.5

Linking Action and Knowledge Problems This book is about dealing with action problems: the Managerial ProblemSolving Method is a guide to solving action problems. Yet you will frequently encounter knowledge problems along the way. Knowledge problems crop up

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during virtually all phases of the MPSM, except during the phase where you choose a solution. Knowledge problems should be resolved according to the research cycle procedure. There are many books on the art of research. This book only covers the research cycle (see Chapter 11) in the broadest of terms.

2

When you are dealing with an action problem, you will nearly always need a certain amount of knowledge. As soon as you find that there is knowledge you need and do not already have available, you move away from the MPSM and enter the research cycle. Once you have completed the cycle (and your investigation), you re-enter the MPSM at the phase where you left it. Using the knowledge you have obtained, you proceed to deal with the action problem. As such, the approach to your knowledge problem becomes a means of solving your action problem. One example would be mending a punctured tyre. You start with an action problem: one of your tyres is flat. That leads to a knowledge problem: you need to know where exactly the tyre has been punctured. So you move to investigate. Once you have established the location of the puncture, you proceed to solve your action problem: you fix the puncture. Note that you should never stick the ‘knowledge problem’ label onto just any old issue. Not every instance where you need information is by definition a knowledge problem. In some cases, the knowledge you need may already be present elsewhere, for example in annual reports or records. Obtaining the required knowledge would just be just a matter of searching, not researching. In other cases, you may not even need to know all the ins and outs, as long as you have a global impression. You may be best served by using your common sense and making well-founded assumptions. Say, for example, that other parties have already conducted research into the problem earlier, but you are unable to obtain the information from their reports. It would be enough to talk about the earlier research using a representative sample, or interviewing individuals involved in earlier research. You might learn that motivation levels were low enough to warrant some form of action even back then. That means you do not need to know exactly how low those levels were for your new problem-solving approach – and as such, no additional research is needed. If you cannot obtain the information you need and are unable to provide an educated guess, you will need to formulate a knowledge problem. Not everyone is always immediately clear on the difference between action and knowledge problems. Action problems deal with unique and concrete norms. For example: what would be the best way of improving employee motivation levels? That would appear to be a knowledge problem, a question which needs an answer in the form of information. In fact, however, it is an action problem posing as a knowledge one. The problem is not concerned with an actual, measurable situation, but with what is the accepted norm; a norm is not something that exists in reality, but something that has to be established based on preference. The so-called ‘best way’ is nothing but a norm. And you are looking to ‘improve’ motivation. Also a norm. Improving means that motivation levels would be higher than they are now once you have finished implementing a solution. For a knowledge problem, the norm is that the answer has to be correct. That is a general norm, which applies to all knowledge problems. But the level of exactness of the knowledge you

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are looking for may differ from one problem to the next. Table 2.1 is an overview of the characteristics of both action and knowledge problems.

TABLE 2.1 An action problem involves an undesired situation. A knowledge problem involves a lack of knowledge.

Description

Action Problem

Knowledge Problem

Definition

An action problem is a discrepancy between the norm and reality, as perceived by the problem owner.

Appearance

Things are not as you want them to be. Problem Identification Perception (There is a fiver in my wallet; I need a twenty!) Specific Managerial Problem-Solving Method (MPSM)

A knowledge problem is a description of the research population, the variables and, if necessary, the relations that need to be investigated. You require knowledge.

Formulation Problem Description

Norm Problem-Solving Approach

2

Problem Statement Question (How much money is left in my wallet?) General Research cycle

Tip: Limit Yourself to Important Knowledge Problems In the problem-solving approach to an action problem, there is often a solid need for knowledge. Knowledge problems lurk around every turn; and you will soon become completely turned around if you expect to deal with each knowledge problem individually. On top of that, you will generally not have enough time to deal with all of them via the research cycle anyway. The advice, therefore is this: Limit yourself to the largest, most important knowledge problems, and be thorough when taking them on. Whatever slew of smaller knowledge problems is generally undeserving of your attention; answers you find hardly tend to have any impact on the solutions in your problem-solving approach. Think of buying a new car. If what you want is the most fuel-efficient car available, looking into built-in accessories is pointless; the only relevant information concerns fuel-efficiency.

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Summary

2 ▶ ‘Problem’ is an analytical concept. It is something you do not like or do not know. ▶ An action problem is when the problem owner perceives a discrepancy between the norm and reality; the existing situation is not as it should be. ▶ A knowledge problem is when the problem owner does not have the information required to deal with the problem. Some form of research is required. A knowledge problem involves a description of the research population, the variables and, if necessary, the relationships that need to be investigated. ▶ An action problem is resolved using the MPSM (Managerial ProblemSolving Method). The MPSM consists of the following phases: 1 Defining the problem 2 Formulating the approach 3 Analysing the problem 4 Formulating (alternative) solutions 5 Choosing a solution 6 Implementing the solution 7 Evaluating the solution ▶ A knowledge problem is resolved using the research cycle. It consists of eight phases: 1 Formulating the research goal 2 Formulating the problem statement 3 Formulating the research questions 4 Formulating the research design 5 Performing the operationalisation 6 Performing the measurements (gathering data) 7 Processing the data 8 Drawing conclusions (reviewing the problem statement) ▶ The MPSM is where action and knowledge problems meet; where a problem-solving method and research go hand in hand. When dealing with an action problem, you always need a certain amount of knowledge. As soon as you find that there is information you need and do not already have, you move away from the MPSM, and enter the research cycle. Once you have completed the cycle (and your investigation), you re-enter the MPSM at the phase from which you left off. Using the knowledge you have obtained, you proceed to deal with the action problem. As such, the approach to your knowledge problem becomes a means of solving your action problem.

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Core Concepts

2 Discrepancy

A deviation, a situation where two things do not match. Problem-solving involves dealing with a discrepancy, a deviation, between the norm and reality.

Action Problem

A discrepancy between the norm and reality, as perceived by the problem owner.

Knowledge Problem

A description of the research population, the variables and, if necessary, the relationships that need to be investigated.

Research Population

The person(s), group(s), or organisation(s) that are the subject of the investigation you are performing.

Problem-Owner

The person(s), group(s), or organisation(s) who are (or perceive themselves to be) responsible for a solution to a problem.

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3

A Trouble-Shooter’s Log 3

Things are looking pretty grim at Lock Plastic Production in Wolverton. For the third consecutive quarter, the company finds itself in the red. You have been recruited as their trouble-shooter, a problem-solver tasked with investigating and solving ‘the problem’. But what, exactly, is ‘the problem’. And how are you going to deal with it? You set out to solve the problem following the seven phases of the Managerial Problem-Solving Method. This chapter addresses the following questions: * How does the MPSM work in practice? * Which activities are involved in the different phases? * What are the results of the different phases?

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Substantial stagnation in the plastics plant

A trouble-shooter’s log 3

Things are looking pretty grim at Lock Plastic Production in Wolverton. For the third consecutive quarter, the company finds itself in the red. You have been contracted to help the company find a way out. You set out to work along with a project team. You approach the issue according to the MPSM (Managerial Problem-Solving Solution). Using a log, you keep a record of your findings for each of the phases of the MPSM.

Phase 1 Identifying the Problem Thursday, January 6th, at Lock’s Drafted a list of identified problems: many colleagues leaving; old, frequently broken machinery; new materials apparently too hard to properly process; revenue from loyal clients fading; barely any new clients; sales team hardly leave the premises; poorly trained sales team; education levels of production staff (too) low; cost figures increasing; ‘competitors are more innovative’. Friday, January 7th, headquarters Had a closer look at the issues indicated. Some questions unanswered: Are the new materials actually too hard to process, or are they not properly treated before processing? Do Sales stay away from clients, or is that just Marketing’s perception? Are competitors really ahead in terms of new products, or is that just a feeling resulting from Lock’s own people being very familiar with their products? Focussed on the missing information. Created insight into the cluster of problems. And looked for and identified the most likely cause: Lock will not be able to go on using their antiquated and worn machinery.

Phase 2 Formulating the Approach Wednesday, January 12th, at Lock’s Advised director to attack the problem at the root. He needs to free up funds and invest them in new machinery. Director was less than thrilled. Still managed to convince him of the urgency. Received go-ahead for formulating the problem-solving approach. Required machines unlikely to be found at a local hardware store. Director to give final verdict on the investment later. Made the rounds on-site, talked to several people there. Got some ideas concerning requirements for new machines, and some issues to keep in mind in case of a switch-over. Surprisingly, not all employees feel new machines are necessary; a thorough revision of current machines should be enough. Added advantage: Investment could be spent on next generation of machines due in two years, expected to be superior to currently available models. Additionally: New machines will not help with Sales agents just hanging around on-site…

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Friday, January 14th, headquarters Compiled an overview of all activities. Still some ambiguities left. Made a list of things to look into, and a ‘to do’-list. Many people somehow involved in the problem. Supervisors very willing to assist, but often lacking in technical expertise. Tech Support only available on demand. Found four employees willing to take part in project team. Drafted division of labour. Competitor with modern machinery supremely uninterested in receiving visitors. Some of Lock’s employees expressed fear of being replaced by new machines. Emailed detailed plan of attack to Lock. Lots of work to be done, but at least there is the prospect of a solution.

Phase 3 Analysing the Problem

3

Tuesday, January 18th, at Lock’s A day in the life of Tech Support. Meticulously investigated the entire production line. Found frequent stagnation during many stages of production. Fabricating building materials, e.g. cement trays, buckets, seems effortless. However, found significant underutilisation in the production of garden chairs, crates, and window sills. Was told that problem had been looked into earlier. Advice back then was to switch over to softer plastics. Why was that advice ignored? Was it even ignored? Took home a stack of Tech Support logs. Logs include overview of all malfunctions reported and repairs performed over the past two years. First impression: seems no single malfunction occurred more than once. Rules out an all-encompassing cause. Are the old machines really the problem? Or is it the people using those machines? Wednesday, January 19th, headquarters Planned initial meeting with project team. Drafted agenda and sent out invites. Anticipated on upcoming research. Looked for explanations. Why do the old machines keep falling apart? Matter of age, of wear and tear? How are breakdowns related to low levels of education among production staff members? According to the existing logs, only very few malfunctions occur during injection moulding of plastics. During finishing, cutting machines frequently fail when processing new, harder plastics. Similar failures occur when finishing thermoplastics which soften when heated. But for those types of plastics, fewer instances of stagnation seem to occur. What is the connection between the hardness of the materials and machine failure? Should allocate some time to ‘materials science’ during next week’s project team meeting. Thermoplastics, polymers. What types of materials does Lock use? What happens during the chemical processes those materials are subject to? What are the properties of those materials? Thursday, January 27th, project team meeting Project group seems like a good bunch of people. Made progress on the research design. Luckily, one of the members is a chemical engineer. He will draft a list of the properties of the various plastics and other materials used. We will cross-reference his list with the list of stagnations. What is the relationship between materials used and frequency of machine failure? Scheduled (interim) research report for mid-February. Friday, January 28th, project team meeting Tech Support to approach suppliers of possible new machines; going to look into what types of materials can be processed in a new production line. Chemical engineer Peter Wall discussed hardness and usability of the ‘plastics’. Quality info. Loses Tech Support once he reaches ‘non-interlinked linear macro-molecules’ and

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‘Van der Waals interactions’. Some of the materials used by Lock are indeed rock solid, harder than the materials used when the machines were first bought 15 years ago. Research group present the cross-referenced table of materials and failures. Hardness of materials seems hardly of influence on production errors. Only differences occur during the finishing stages. Calculations show a link between hardness of plastics and cutting machine failure. Data is quite rough. Researchers still looking into a way of obtaining more accurate figures. Final report due in 14 days.

3

Thursday, March 3rd, at Lock’s Research group asking for more time. Talked to Sales. New, harder materials mean tougher products. ‘Market demands solid, quality plastics.’ Plastic window frames and sills need to be rock solid. Even the smallest amount of give or elasticity, as found in softer materials, is unacceptable in the construction industry. Garden furniture requires similar durability, on top of design quality. Main competition of outdoor plastic chairs, benches, and tables is in the form of durable, hardwood equivalents. Wednesday, March 9th, headquarters Received the requested research data. Staggering amount of info! Lots of detailed figures for each type of plastic. Earlier impression confirmed: The harder the plastic, the bigger the chances of cutting machine failure… and the bigger the chances of stagnation. Hardness of materials plays no role during earlier parts of the production process. But those are not without failure altogether. What causes the issues there? Results should be sent to project team. What is next? Use softer materials? Sharper, stronger cutting blades? Boost cutting machine power output? Need to invite project team for creative session. How is Lock going to decide on a working solution? Have to think about decision-making process. What is required of the solution? And who will have final say?

Phase 4 Formulating (alternative) solutions Monday, March 14th, headquarters Informed directors of research results by phone. Gone through decision-making process. Entire board of directors needs to be involved in important investments. Consensus required. But Lock needs several options to pick from. Company expects several alternative solutions which all meet certain established criteria. Not all criteria equally important. A question of weighting criteria. One key focus is on efficiency. Lock wants to be rid of underutilisation during the production process. The most important issue is not the cost; it is solving the problem. Drafted and weighted a list of criteria. Sent to project team for comments. Buried under an avalanche of argumentation for the weighting. Assigning own weights proves impracticable. Weighting is subjective – impossible to please everyone. Asked several key players to weight criteria instead. They divided 100 points across all criteria. Method proved acceptable. Individually assigned weights seem surprisingly evenly matched. Averaged the weight for each criterion. End results not that different from initial set-up. Difference: Lock employees assigned greater weight to importance of machine noise. Legitimate difference. They will be the ones working with these machines every day. Would this change have led to a different final outcome? No way of knowing until after… when it will be too late. Friday, March 25th, project team meeting Inspiring meeting. Made inventory of ideas. Opted not to look at problems during earlier stages of production for now. Focus is on the finishing stages, cutting the plastics. Many ways of cutting possible: punching, sawing, laser-cutting, ‘water-cutting’, and die-less crimping (without die-cut). Alternatively: Outsourcing, contracting out to third party. There

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are companies who specialise in CAD-driven cutting, managing complex shapes to exceptional levels of accuracy. Cross-referenced solutions with materials used. Thickness could be an issue when using laser cutters. How to clean and dry materials once cut using water/sand method? How much would outsourcing cost? Agreed to gather additional information. Drafted division of labour. Information deadline is end of next week. Project group will get overview of all options with scores per criterion. After that, establish advice via conference call. Thursday, April 7th, project team conference call Water-cutting and laser-cutting less practical for Lock’s production process than initially assumed. Three types of cutting tools and outsourcing option remain. Machine no. 2 came out on top, followed at some distance by machines 1 and 3. Outsourcing is wildly expensive and finishes last. Project team decides on cutting machine 2.

3

Monday, April 11th, headquarters Articulated final recommendations. Sent report to Lock via letter and email. Brief talk with management. Board of directors to make a decision next month. Have been invited to provide short presentation. Wednesday, April 20th, headquarters Finished up presentation for board.

Phase 5 Choosing a Solution Tuesday, May 10th, board of directors meeting Board of directors chooses not to follow suggested advisory report. Lock has opted for outsourcing instead. Specialised company to be put in charge of the cutting stage. Board has different considerations regarding risks. New cutting machines are more advanced and appear more reliable than current models. Unfortunately, operating them is not easy. This poses a real danger of poorly finished products. And new machines still have a risk of failing. Would place Lock back at square one. Also, possible to establish well-defined supply terms. Outsourcing does appear more expensive, but board feels increase in costs can be offset by reduction in staff. Expectations are that price negotiations can also be struck in Lock’s favour. Have been tasked with executing the plan: begin the search for a ‘plastics cutter’ along with the project team.

Phase 6 Implementing the Solution Wednesday, May 1st, headquarters Tried to bring project team up to speed over the phone. Two members on holiday. Sent them a thoroughly detailed email. Did manage to talk to two others. Their response: resigned, but understanding. Will be meeting next week to discuss next steps. Drafted initial plan for implementation. Requested quotes from three potential cutting companies. The information picked up studying cutting machines still proves useful: we know exactly what criteria the possible partners need to conform to. Friday, May 20th, project team meeting Continued fleshing out the implementation plan. A lot of work needs to be done before Lock can successfully outsource the finishing/cutting stage. Now faced with the first logistical problem. Currently, finished products are neatly packaged and sent to wholesalers,

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sometimes to construction companies. Under new situation, intermediate products will first need temporary packaging before being sent to the cutting company. Following cutting, should they be sent directly to the wholesalers or clients, or first be returned to Lock? Will the cutting company (be able to) provide packaging? Is there a possible role for wholesalers to play? We have received quotes from the various companies. Drafted and weighted a list of criteria with the project team. Johnsons’ in Swindon rates highly in terms of reliability and craftsmanship, and is also the cheapest. The distance is a real drawback. Several trucks of plastic intermediates would need to travel 100 kilometres back and forth every day. Johnsons’ has confided they would be willing to set up a branch at Lock’s. Seems an interesting possibility, deserves to be looked into. Drafted a division of labour. 3

Tuesday, May 31st, Johnsons’, Swindon Went with Lock’s management to meet with Johnsons’. A fine business. Collaboration onsite at Lock seems a real possibility. Johnsons’ will be crunching numbers to come up with a proposal. Friday, June 10th, project team meeting Johnsons’ proposal currently with management. Drafted a detailed plan of implementation, emailed to Lock management. Included separate communications plan. Rumours concerning disposal of Lock’s cutting department already circulating. Company needs to provide openness and offer perspective. Employees from that department will be posted at Johnsons’. Need to be told they will still be working at Lock’s, though wearing Johnsons’ overalls. Suggested calling a company meeting as part of the communications plan. Next week seems prudent. Tuesday, June 14th, at Lock’s Discussed implementation plan with Lock management. Company will be in charge of executing implementation. Starting September 5th, Johnsons’ will be taking care of Lock’s in Birmingham. Agreed to evaluate sometime spring. Time to send out the invoice.

Phase 7 Evaluating the Solution Thursday, February 16th, headquarters On the phone with Lock management. Company has been out of the red for the past six months! Collaboration with Johnsons’ is proceeding perfectly. Barely any stagnation during production. Outsourced finishing costs are higher than for finishing in-house. Revenue only modestly increasing. Have yet to attract new clients. Lock does not seem overly keen on evaluating. Wonder why? Possibly anxious that further evaluation will refocus on problems occurring at earlier production phases – problems which are as yet unsolved. Managed to convince management of the need for evaluation. Invited project team to discuss evaluation method. Friday, February 24th, project team meeting Nice to see the gang again. One new face, Jim’s successor (following Jim’s retirement). Mood is characterised by satisfactory collaboration with Johnsons’. Barely any problems in production. Some questions as to the need for evaluation. Following a discussion, team agrees that evaluation is necessary. Should make sure staff fully understand the need for evaluation. Otherwise, they will not bother filling in evaluation forms. Some time spent on matter of ‘over-capacity’. Using Johnsons’ new cutters, the finishing stage has been sped up rapidly – meaning the production line is no longer occupied full time. Possibility for

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increase in revenue there. But how? A lot of input for a questionnaire. Agreed to email concept to project team next week. Monday, February 27th, headquarters Drafted questionnaire, emailed to project team. Friday, March 5th, headquarters Not a bad turn-out on the questionnaire. Staff filled in 33 forms via online link, 48 using pen and paper. Hardly any surprises in finishing or production. Staff is satisfied overall. Hardness of materials is no longer an issue. A lot of criticism involving Sales – apparently not doing enough to reel in new clients. Account managers are good at maintaining existing contacts, but cannot hold their own as representatives – not skilled at setting up meetings or convincing new clients. Business canvassing course in order? Or recruit expertise from elsewhere: new Sales agents? Drafted evaluation report with findings, advice and recommendations; sent to project team for review.

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Friday, March 14th, headquarters Processed project team’s notes in the evaluation report. Sent in report to Lock management. Red figures have been fully dealt with. Time to solve a new problem. Suggested the problem of ‘over-capacity’ should be dealt with structurally in an accompanying letter. Scheduled a call for Tuesday.

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§ 3.1

The MPSM in Practice During each phase of the MPSM, you, the problem-solver, have to take several different steps. What does each phase involve, exactly? What is the result of each phase? And how does that work in practice? The following table describes what has to be done during each phase and what each phase results in. By way of example, the same has been described in practical terms using the case example of the plastics plant at the start of this chapter.

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TABLE 3.1 A schematic overview of activities and results of the seven phases of the Managerial Problem-Solving Method, plus a practical description of the same using the Lock Plastic Production case.

THE MPSM (MANAGERIAL PROBLEM-SOLVING METHOD) MPSM Phase

Activities

Results

Lock Case

Phase 1: Defining the Problem

- drafting inventory of problems - make problem cluster - select core problem - express problem in variables

- global problem identification

- insight into cluster of problems - company cannot continue with worn machinery

Phase 2: Formulating the ProblemSolving Approach

- draft problem-solving approach - use D3 (Do, Discover, Decide) to describe the activities and knowledge required, and choose from the various options available within your approach

- plan for the problem-solution process

- activities outlined - established need for investigation - plan of attack established

Phase 3: Analysing the Problem

- re-examine problem identification and problem cluster, and fill in missing details - look for causes - review why any earlier solutions have not worked - use research cycle to solve knowledge problems - use a model to document relationships between problem and cause

- definition and analysis of both problem and problem identification

- reviewed logs detailing failures - researched connection between hardness of materials and machine failure - hardness is important for finish

Phase 4: Formulating (Alternative) Solutions

- describe a solution - establish decision-making process - draft list of criteria - scale criteria - weight criteria - invent alternatives or use existing possibilities - evaluate alternatives

- report on alternatives and their desirability

- board of directors to decide - board wants to be able to choose - project group to weight criteria - cutting machine 2 is the best option

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A schematic overview of activities and results of the seven phases of the Managerial Problem-Solving Method, plus a practical description of the same using the Lock Plastic Production case.

TABLE 3.1 (cont.)

THE MPSM (MANAGERIAL PROBLEM-SOLVING METHOD) Phase 5: Choosing a Solution

- select one of the possible solutions

- solution to the problem

- company to outsource cutting stage

Phase 6: Implementing the Solution

- draft an implementation plan - provide brief and step-bystep description of activities - detail approach to possible resistance

- change

- filled in details of plan - came to agreement with Johnsons’ - openness regarding outsourcing - September 5th: cutting now outsourced

- convince participants of the need for evaluation - evaluate all phases of the MPSM - perform structured evaluation

- comparison of effected situation to desired situation

Phase 7: Evaluating the Solution

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- company not desperate for evaluation - convinced board - sent questionnaire - processed info - out of the red - deal with new problem using MPSM?

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4

In Search of the Core Problem 4

Among the many possible things an organisation may feel are not going as they should, it is important to find the one thing that really matters. Something that will make a real difference: the core problem. You identify the core problem during phase 1 of the MPSM, defining the problem. This chapter addresses the following questions: * What types of problems are there? * Which are causes and which are effects? * Which core problem do you deal with (first)? * How do you make a problem quantifiable?

Problem Context 41

Problem Cluster 42

Quick and Dirty 41

Concretising Variables 47

Problem Identification 42

Decomposing (or Splitting) Variables 47

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Inventory First; Research Second

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Mattress manufacturers Sleep-So-Well have to deal with the facts; their machines are old, their production staff is virtually untrained, their sales team performs below par, their margins are low, their turnover is poor, and their profits are appalling. Problems are mounting. You cannot deal with all of them at the same time. You have to make a choice. ‘We have a problem. Figures for this quarter are disappointing. Would you please investigate?’ Easier said than done. It is not clear what exactly is going on. It could be a number of things: from aging machinery to poorly trained staff to unskilled salespeople to low profit margins. The reason for the investigation, disappointing results, is known. You are an advisor to Sleep-So-Well, and you have been advised to look into the problem. Where do you start? What problem do you focus on first? Do you look at one of the bottlenecks, or do you focus on an underlying cause?

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You can only choose a problem if you know which ones are available to solve. First order of business: making an inventory. You underline all potential problems in the company’s documentation. You draft a list of all problems you encounter, using established information and interviews with employees who have some insight into the company’s issues. You use the information you gather as part of your inventory of knowledge. Common sense will help you establish connections between causes and effects. That will tell you a lot, without any need for dedicated research. You can establish the age of the machines, and the staff’s training levels: both things which can be classified as problems. Which means there could be more than one problem. During this phase, you inventory all problems you encounter. You are not yet concerned with acquiring new knowledge. You systematically make an inventory of the knowledge that is already available.

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IN SEARCH OF THE CORE PROBLEM

Reaching the Core Problem, Step by Step Problems come in twos. Or threes. Or even more. For any company, there is generally more than one thing going less than well. This overarching mess of problems is called the problem context. There is usually not enough time or money available to solve all problems at once. So which problem do you deal with first? For every-day problems, the choice tends to be easy. What is the first thing you do if you really need to fix a bike that has several defects? Fix the tyre or fix the bell? The tyre, no doubt. Organisational problems can similarly be classified in terms of urgency. You can arrive at the core problem in four steps. Core problems are those whose solution will make a real difference. You can identify them step-by-step by: * Making an inventory of existing problems; * Indicating the causes and effects, and use them in a problem cluster; * Choosing which core-problem to deal with; and * Making your problem quantifiable.

§ 4.2

41

Problem context

4

Lining Up the Problems For your inventory, your sources are both interviews with staff and existing written information; for example, earlier reports on stagnation along the production line, or problems in other departments. Your work should be quick and dirty. There is no need for real research just yet. First, you make an inventory of existing data and perspectives. This creates a list of problems both perceived and actual. You examine that list critically. Remove any overlap. Formulate the problems in the most concrete possible terms. If something is not a true problem, you remove it from the list. The result is a cleaned up list of problems.

Quick and dirty

Gathering problems often seems easier than it is. You can easily tell whether machines are old when you give them a once-over. But it is possible they may still work just fine. You can establish that their age means they have become unreliable. But even that does not mean they should be replaced outright. It may be possible to resolve the problem by simply having staff take better care when handling the old timers – better care than they needed to take when the machines were originally installed. In this example, you can completely untangle the question and express it in terms of variables, or characteristics. You use the language of variables. There are three variables in this case: * the age variable: Is the problem due to the machines’ age? * the reliability variable: Are the machines unreliable? * the operational quality variable: Are the employees careful enough when handling the machines? Those three variables are all part of different problems. A problem can have only one variable. If there is more than one variable, that means there is more than one problem.

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§ 4.3

Cause and Effect The problems in your inventory may or may not have any relation to each other. To establish whether or not they do, you will first need to know the relationships between the variables. Is reliability a result of age, and not of employee usage? Or has usage always been a factor, even when the machines were brand new? If so, why has this never been an issue until now? Has staff training quality dropped? Asking questions like these will help clarify matters during problem identification. Questions to consider during this stage of the problem-solving method are: * Why is this a problem now? And why was it not doing so before? * Who are causing or influencing the problem? * Who are experiencing hindrance as a result of this problem? * Is this problem also found in other offices or similar companies? If so, does it occur in the same order of severity?

Problem identification

4

Problem cluster

FIGURE 4.1

Problem Cluster Which problems are related? Which are not? It is time to find out the connections between problems. The tool you use for that is called a problem cluster (see figure 4.1). A problem cluster is used to map all problems along with their connections. It serves to bring order to the problem context, and to identify the core problem. Additionally, a cluster is a helpful tool in communications with a client. It helps you discuss problems in context and verify your impressions. Even an outsider can use a problem cluster to identify and differentiate between cause and effect at a glance. There is little use in trying to deal with all problems at once. Focus on one or just a few problems whose solution would contribute greatly in improving the problem context. Try to determine causes and effects. If you do not end up dealing with causes, you may just be combatting symptoms instead of underlying issues. Suffering from a headache? Take an aspirin for instant relief. But what caused your headache in the first place? Was it stress? Excessive drinking? If you do not fix the cause, you will have a sore head again soon enough – too much overtime or too many drinks, and you will be back where you started. A problem cluster is a tool used to create insight. It is a model in which you indicate connections in a cluster of causes and effects. You visualise the causal links between the various problems. Figure 4.1 shows a problem cluster of problems at a production company. It illustrates that problems are not isolated events.

Problem cluster of problems at a production company

Old machines

Unreliable machines

Low occupancy

High production costs

Poor quality sales staff

Poorly trained staff

Low profit margins

Low sales figures

Low profits

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Low profits tend to be indicative of other problems in a company. Ageing machines, for example. Unschooled or poorly trained staff. Mediocre sales agents. Production costs turn out to be high, and profit margins too low. And sales figures are struggling as well. The problem cluster brings order to the problem context and indicates the connections between problems. A problem cluster is a relatively easy model for indicating causally connected problems and bottlenecks. Other models do exist, such as the relationship diagram, and the fishbone model or Ishikawa diagram (Ishikawa, 1985). Filling in one of these fishbone models is often tricky, since all factors are linked through the central spine. It shows you that matters are connected, but not exactly what the nature of these connections is. A problem cluster is different in that is shows you the connections between problems at a glance. The core problem is instantly identified. The same is not possible with a fishbone model. Figure 4.2 shows a fishbone model of problems at a production company. The causes of the low profits are clear. But how are these problems connected? What should you deal with first? Is low occupancy the major issue? Or should you deal with the ageing machinery?

FIGURE 4.2

4

Fishbone model of problems at a production company

Low sales figures

Poor quality sales staff

Poorly trained staff

Low occupancy

Low profits

Old machines

§ 4.4

Unreliable machines

High production costs

Low profit margins

Choosing the Core Problem Your next step is to look for a core problem to deal with. In practice, companies often deal with several core problems at once. If possible, the sensible thing is to limit the number of core problems; better to deal well with one issue than half-handedly with several. Choosing your core problem should take some serious deliberation. You use the following four rules of thumb: 1 The problem cluster shows all problems you have identified as such. Not all unwanted situations are problems for you to solve. A problem is only recorded in your cluster if you are sufficiently sure it actually occurs. You should be convinced that there is a relationship with other problems. If not, leave it out of the problem cluster. If you end up dealing with a situation that does not turn out to have been a problem, you will have spent a lot of energy and goodwill. Additionally, you will have delayed the solution to the actual problem.

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4

Nevertheless, you should make sure to write down those ‘problems’ you are unsure of. They may end up being relevant after all. Even problems you were initially unsure about can end up being the cause of your core problem. 2 Follow the chain of problems back to these problems which have no direct cause themselves. Initially found problems tend to be the result of other problems. The problem cluster in figure 4.1, for example, shows low occupancy as the cause of high production costs. Low occupancy here is itself the result of unreliable machinery – which is due to the age of the machines. In this case, the machines’ age is the problem furthest removed along the cluster from the problem you started with. It has no cause in itself, and is therefore possibly a core problem. This example does not stipulate, for example, why the old machines have not been replaced. And that probably does not matter either when it comes to solving the problem. At this time, there is no need to speculate why the machines were not replaced earlier. 3 If you cannot influence something, then it cannot become a core problem. Say you deal in inflatable rubber dinghies. It has been a poor spring, and a poor summer as well. Lots of rain, nearly every day. And bad weather means few customers. You could, in that case, conclude that the cause of your profit margins is due to the poor weather. Yet there is little using in labelling the quality of the weather as your core problem. How are you going to fix the weather? But it is a different matter if you redefine the problem. For example: Revenue depends on the weather. Fluctuations in weather conditions lead to fluctuations in profits. Poor weather leads to reduced sales figures. That is a problem you would be able to solve by looking for markets elsewhere; preferably somewhere with nicer weather all-round. If you cannot solve a problem, you should take one step forward in your problem cluster, and deal with the next problem in line – provided that problem is one you can deal with. 4 If more than one problem in the cluster remains, you should choose to fix the most important problem. The most important problem is whichever one whose solution would have the greatest impact effect at the lowest cost. You should base your decision on a global impression, an educated guess, since you do not yet know what the solution is going to be. It is generally possible to say whether a solution is going to cost in the order of millions or tens of millions, for example. And it is also generally possible to have a stab at the effect a solution will have on the overall situation, on the problem context. At this point, you can perform a global cost-benefit analysis. That will tell you what will have the most effect relative to efforts or costs. In figure 4.1, for example, additional schooling for existing sales staff would be cheaper than a long-term loan used to invest in new machines. Extra staff training sessions may improve productivity as long as the machines keep working, but will not do much good should the machines fail: the problem will remain unsolved. In the long term, replacing the machines will probably lead to greater profits that retraining the sales department. And so you end up choosing to buy new machines, even though they may come at some cost. However, once you have solved the core problem – here: buying new machines – you may still choose to deal with another (core) problem, such

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as staff training. You may even have to solve a new problem in some cases, if the solution to the first problem you dealt with did not work, or only worked partially. In the example, the unschooled staff may still need additional training before they can handle the new machines properly. You are advised to involve your client in your selection of the core problem. That way, they will not be caught off guard by a solution to a problem they were not even aware existed. Additionally, solving a managerial problem does involve certain costs, for example in case you need to do research. For that reason, you are generally required to submit your choice of core problem to your client anyway. Carefully Choosing Variables Now that you have established a core problem to deal with, it is time to turn to the discrepancy between the norm and the reality of your problem. The first step is to accessibly formulate the problem. You should preferably use a single sentence containing both the norm and the reality. For example: customers have awarded our service over the past six months 7.5 out of 10, while we are after 8 out of 10. Exact figures, such as the 7.5 average, are not always known. But you may have picked up some signals from complaining customers instead. That may still leave you with enough information to assume that satisfaction is below the norm of 8 out of 10. Now you can deal with the problem, whatever its size, before it gets worse. But if you are completely unsure if the problem falls below the norm – in other words: whether a problem even exists – it is better to focus on a different problem. What you can do in that case, is establish a baseline, e.g. perform a customer satisfaction survey. The results of that baseline can later be compared to new survey results.

4

In order to describe your problem, you have to express both the norm and reality in terms of variables. It is important to keep the following three things in mind: * Be careful when selecting your variable. Whatever variable you use for the norm and for reality should be defined carefully, even if you do not yet have any relevant data. For example, it is important to understand that there is a difference between a problem of insufficient profits or insufficient profit margins. Insufficient profits may lead you to lower your prices, thereby increasing your revenue. That is not possible if it is your profit margin that is the problem. In that case, lower your prices would lead to even lower profit margins. * Express both the norm and the reality as the same variable. Do not say: Last month’s profit share should have been 25%, but we only sold 1,500 products. That would not be a problem if 1,500 conformed exactly to a 25% market share. But if those 1,500 items only account for 10% of products sold overall, you have a genuine problem. So in order to make an insightful comparison between the norm and the reality, you should use the same variable. Choose either market share in percentages, or number of products sold per month. * Use only one variable per problem. Trouble-shooters tend to want to solve more than one problem at the same time. Or they focus on causes and effects simultaneously. The result? They cannot choose between employee motivation and productivity, and formulate the problem as: ‘Because motivation is down, productivity is down as well’; a statement

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that is difficult to express as a variable, essentially being a combination of two problems! Which variable should you choose? In this example, productivity is probably being affected by motivation. In that case, you should deal with the cause, the core problem, of poor motivation.

§ 4.5

Making Problems Quantifiable Next, you need to be able to come to grips with the problem. This means expressing the norm and the reality of your action problem as a concrete, quantifiable variable. That can often by quite tricky. It is easy to measure revenue per employee per month; but how do you measure staff motivation? Does it come in kilogrammes? As a concept, motivation is difficult to express in measurements.

4

Variables that cannot be measured must first be made quantifiable. We call this process ‘operationalisation’. Operationalisation is often a multi-step process. The ‘loyalty to the company’ variable is first translated into, for example, the ideas of ‘motivation’ and ‘work-involvement’. Then, you proceed to step two: the actual operationalisation. For the concept of motivation, you would use indicators: willingness to work overtime, amount of absenteeism, turnover figures. These indicators can often be expressed in units you can measure or count, such as: ‘Employees are willing to pull two shifts of overtime per month’, ‘Absenteeism is at 4.3% of FTE’, or ‘Employment length is three years and four months on average’. An indicator, in other words, is a variable you have made measurable. This use of indicators in measurements is also common in the field of physics. One example is a mercury-based thermometer. You observe the level of the mercury to determine warmth or cold. You are not actually measuring heat. You are using an indicator of heat, instead. By heating a substance, in this case mercury, the vibrations or kinetic energy of the molecules change. This leads to an increase in the volume of the mercury filling, and that increase is what you actually measure. In physics, one indicator tends to be enough to provide accurate and precise, replicable measurements. This does not tend to hold true for other sciences or fields. You are generally recommended to use more than one indicator. But do not go overboard. One indicator can be not enough. Using two or three will get rid of most accidental disruptions. For example: absenteeism can be a fine indicator of motivation. But if the figures you use were recorded during the outbreak of a seasonal flu, you will be looking at a substantial increase in absenteeism which is not necessarily related to motivation at all. But why should you be conservative when it comes to the number of indicators? Indicators may end up disagreeing with one another if too many are used. For example: You have opted to measure motivation levels using the indicators of absenteeism, willingness to work overtime, and involvement in staff outings. The absenteeism and overtime indicators may indicate high levels of motivation; meanwhile, however, people cannot be bothered to take part in the outings. Does that mean their motivation levels are low? The staff outings do not relate to the work itself, but they do have something to do with whether employees enjoy being part of the company. The more

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indicators you use, the bigger the chances that you begin to stretch the meaning of the variable. In the example, you have stretched the meaning from ‘labour-related motivation to ‘labour- and company-related motivation’. Little wonder the indicators have started disagreeing with each other. An indicator does not always work in all circumstances or in the same manner. As mentioned, absenteeism may be an indicator for motivation. But not in this example: The staff of an agrarian company calls on their management. The employees work in a warehouse which, at times, is cold and damp. The rain tends to get in. They want a location which is water- and windproof. ‘Cannot be done,’ replies management: ‘Warehouses are susceptible to draught. It comes with the territory. A little wind or rain is inevitable.’ The employees beat a disappointed retreat. One month on, the warehouse has been equipped with a new computer used to keep track of supplies. In no time at all, the draughty building is sealed hermetically in order to protect the computer from the elements. Management is confident this will also improve motivation levels. As it turns out, motivation levels do not improve at all. Even though the improvements in climate control mean people call in ill less often, the resulting reduction in absenteeism has no influence on motivation levels. The indicator has failed. In fact, motivation levels appear to be dropping. The staff feels they have been had. ‘They take better care of their machines than of their crew’, people grumble. Because humans are emotional creatures, the laws of physics do not always apply to their thoughts or actions. For example, the status of an employee in many companies is directly proportional to the size of their company car. But this same indicator, car size, will probably backfire if applied to an organisation like Greenpeace. There, the status of an employee who purchases a large, environmentally unfriendly vehicle may actually be lowered as a result.

4

Concretising and Decomposing In managerial problems, indicators are used to quantify variables. But there is one condition: you have to be able to motivate the connection between the indicator(s) and the variable(s). This means that, if you use indicators for the variable of motivation, you have to find arguments using existing literature or research which prove, for example, a connection between increased absenteeism and low motivation levels. If that connection checks out, you will have chosen well-founded indicators for your variable. Using indicators, you highlight several aspects of your variable. Together, these indicators may or may not exactly encompass the variable. The motivation variable, for example, may be quantified using the indicators of absenteeism, willingness to work overtime, and employee turnover. Together, these indicators will not account exactly for 100% of motivation levels. This method is called concretising variables.

Concretising variables

Some variables can be split up into separate parts. Say you use revenue and costs as indicators of profit. Combined, these two aspects add up to your variable exactly. If you want to find out the output capacity of an electrical machine, you will need to split up the output variable. That requires the formula of power in watts, which is: power = current x voltage. Or, in terms of units: watts = volts x amps. In these examples, the combined indicators are exactly equal to the variable. This method is called decomposing variables.

Decomposing variables

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Tips for Using Variables and Indicators

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Indicators help you quantify a problem. But how do you choose the right indicators? And how many do you even need? Here are some tips for using indicators: * Do not use too many, and do not use too few. Use too many indicators, and you risk contradictions between indicators. You will often also be measuring something you did not intend to with your original variable, because you are measuring another variable as well. In addition, you run the risk of losing track of indicators. On the other hand, one indicator is almost never enough. Use three or four. Any possible deviations which occurred when you measured the various indicators can then be used to offset one another. * Take all circumstances into account when choosing your indicators. What makes sense in one case may be pointless in another. * When selecting an indicator for an effect, your best choice is a direct consequence of the problem. Whatever you do, make sure you follow the chain of cause and effect closely. Here is what not to do: you select motivation as an indicator of profit in the chain ‘Motivation levels are high, leading to increased efforts. The result is higher production levels for better quality products. In turn, that leads to a higher price per product and, as such, increased revenue. Eventually, that revenue will lead to an increase in profit since costs have not gone up.’ Certainly, in this case motivation is a yardstick of profit. But there are many other steps in between the two that also have an effect on profit. As such, the actual role of motivation is quite unclear. * Never use a cause as an indicator. Doing so will mean you will not be able to measure the effect of your solution. Think, for example, of using working conditions as an indicator of motivation. Providing helmets, safety goggles and protective clothing improves working condition in a quarry. Your working conditions indicator increases, and so you know that motivation levels increase as well. But the problem is that poor working conditions were (part of) the cause of poor motivation levels. If you change the working conditions, motivation levels will change by definition. As such, you cannot use working conditions to measure motivation levels. You need other indicators for that. * You do not always need to express variables as numbers. If you want to establish the perceived quality of a cinematic film, you can also use the indicators good, medium, and bad. Those will tell you enough about the quality without expressing it as a number.

Setting a Norm Indicators make variables quantifiable. Those variables are used to concretise the action problem. You indicate exactly what the difference is between the norm and the reality. For example, this year’s increase in revenue is only 7% instead of the 10% you are aiming for. Your variable is revenue increase in percentages. The norm is 10% per year.

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A norm for annual increase in revenue, employee absenteeism, or turnover does not simply pop up out of the blue. Setting a norm should be preceded by an analysis. In this case, the increase in revenue of 10% may be needed because the company has a position in a growing market. Substantial growth will ensure that the market share, and hence a competitive advantage, are maintained. A norm must be set in a certain context. Manufacturing companies have to follow applicable legislation. The implications of that legislation are taken into account when setting the norm. The same applies for consumer demands regarding product quality. High norms can lead to high priced products. Hypodermic syringes, for example, are relatively expensive. Their price is a result of the cost of their sterilised packaging. The effectivity norm (here: sterilisation) is high, which means the price is, too. Here, base-norms are at loggerheads. There is a dilemma between two base-norms: costs and effectivity. Whatever the problem, there will always be certain base-norms at odds with each other. Keep an eye out for these incompatibilities to make sure you prevent setting unrealistic or unattainable norms.

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Summary

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▶ When identifying a problem in an organisation, you proceed step by step. You make an inventory of existing problems. Your work should be quick and dirty. You do not perform any real research. You inventory existing data and perspectives. You use different sources for your inventory, such as available documentation and information from interviews. ▶ Next, you look for causes and effects. You draft a problem cluster in which you map the different problems and their mutual relationships. Doing so structures the problem context, allowing you to identify the core problem. You use the following rules of thumb for this process: * You only include a problem in the cluster if you are sufficiently sure it is an actual problem. If you are not, you do not add it to the cluster. * Proceed down the chain of cause and effect until you reach the cause which is furthest removed from your initial problem. That cause is no longer the effect of another cause. * If you cannot influence it, it cannot be labelled a core problem. ▶ Then, you choose which core problem to deal with. That will be the most important problem in the problem cluster. At this time, you can choose to first perform a global cost-benefit analysis for the approaches to the different core problem. If you do, pick the most appropriate problem – lowest costs, highest reward. ▶ The last step is to make the problem manageable. You express the norm and the reality of your problem in a concrete, measurable variable. You may need to use indicators in order to actually measure anything. When using indicators, consider the following tips: * Use more than one, but not too many, indicators, preferably three or four; * Consider all circumstances when choosing your indicators; * Preferably use only direct consequences when using indicators to measure effects; * Never use a cause as an indicator.

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Core Concepts

Concretising Variables

A method of quantifying variables. Using indicators, you highlight one or more aspects of your variable. You may choose to use more than one indicator for the same variable. Together, these indicators may or may not exactly encompass the variable.

Decomposing Variables

A method of quantifying variables. Variables can sometimes be split up into separate parts. Combined, these parts add up to your variable exactly. The variable for profit, for example, is made up of the indicators of revenue and costs.

Problem Context

The full scope of existing problems, which may or may not be related.

Problem Identification

Systematically establishing a quantifiable core problem.

Problem Cluster

A model used to map different problems and their mutual relationships. A problem cluster serves as a means of structuring the problem context, and is used to identify the core problem.

Quick and Dirty (Identification)

A rapid, uncomplicated inventory of existing inventory of existing data and perspectives made without performing actual research.

Language of Variables

Expressing a problem as a variable. You untangle an issue and define it as a series of variables, measurable attributes. Some variables can only be measured using indicators. There is only one variable for any problem.

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D3: Do, Discover, Decide

What activities should you undertake in in order to deal with your problem? Who do you involve in the process? How do you know when you are done? You set down your problem-solving method on paper. You draft your plan of attack in phase 2 of the MPSM, formulating the approach.

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This chapter addresses the following questions: * What do you need in terms of capabilities, knowledge, and choices? * How do you arrive at a systematic approach? * What level of accuracy and detail does your plan need?

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The Best Financial Expert for the Project Group

Your project group needs some financial expertise. But who to choose? The controller, the financial analyser, or the head of administrations? Who would be the most useful?

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The company is expanding rapidly – and it is not yet showing any signs of stopping soon. It is time to take action. How about moving to a new location? Opening up a second branch? Building a new story onto the existing building? Plenty of ideas, for sure. But whatever the best short and long term answers for dealing with the exceptional growth rate, they need to be financially sound. Without a financial expert, the project group is headed for failure. The project leader is certain of that. Now that he is drafting his plan of attack, it is down to a matter of doing, discovering, and deciding. Doing is for what actions need to be taken: Ask someone to join the team. But who? The controller, with his helicopter view? The financial analyser, known for his solid approach? Or the chief admin, who has exceptional knowledge of the company?

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Best thing for it is to gather some information – in other words, discovering. The group leader picks up pen and paper, and starts listing the pros and cons of all three financials. The controller is not a typical accountant, and keeps a broad perspective. He is always busy. Everybody seems to need his attention and financial advice. The financial analyser is a young guy, but he is a competent professional. He does occasionally need some direction. The chief admin is an all-round financial expert. He knows the company back to front. He is somewhat known for his rigid conser vativism. After much deliberation, the project leader has to discount the controller; he simply does not have the time. The chief admin is not flexible enough for this project. So now the choice is easy: The younger financial analyst is the best match for the project team, despite his occasional need for direction. The project leader picks up the phone and makes a call.

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Three Principles of a Plan of Attack How do you set to work on a problem in a company? How do you begin your approach if, say, the Czech specialist in seals, valves, and taps has not yet reached the expected sales growth in Eastern Europe? With whom do you take up the issue? Do you restrict yourself to the Sales department? Are you sure that the sales concerns are shared by the entire company? Is there enough money available to work with? A complex problem has many sides. Should you review all of them? Where do you even start? If you just jump in the deep end, you run the risk of overlooking something. You may keep coming across new aspects that need to be highlighted. If you are not careful, before too long you will not be able to see the forest for the trees. What you need is a plan of attack. You formulate your approach using the following three principles: 1. Use D3: Do, Discover, and Decide 2. Proceed according to a systematic approach 3. Describe your plan in detail

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§ 5.2

D3 Explained When approaching an action-based problem, you go your own way. You venture out to come to a solution. You research and investigate until you have the information you need. That requires the use of the research cycle (see Chapter 11). Your approach and your investigative research will often involve making choices. These choices involve the principle of D3. Here, D3 is not Dichlorodiphenyldichloroethane, a breakdown product of DDT; nor is it a rather unimpressive anagram of the commonly used abbreviation of threedimensional stereoscopic vision. D3 refers to the three aspects of Do, Discover, and Decide.

Research cycle

The first aspect, Do, encompasses all activities you need to perform. That includes things both easy and hard. It can be as simple as writing a ‘to whom it may concern’ introduction of who you are and what your role as investigator of employee absenteeism is going to involve. Basically everything you need to do from drafting a problem-solving approach to proposing a budget to requesting support for your investigation. The second, Discover, is everything you need to know and understand. An important part of that is asking questions with the goal of obtaining knowledge. There are things you have to figure out. Formulating your questions so that their answers give you the information you need, is part of Discover. The third and final aspect, Decide, is about selecting the proper options. Who do you involve in your investigation? Who do you leave out? Similar choices are made in your problem-solving approach. What do you do if working conditions are poor? Do you focus on the quality of the old machinery, or the climate control system along the production line? What do you take into account, and what do you ignore? If there is more than one alternative, you choose the winning option based on a comparison of criteria you have weighed up.

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Do, Discover, Decide. Other phases of the MPSM will also involve you having to perform several different actions. You may not know where to start, what to ignore. If you find yourself in that position, turn to D3. It will help you get your affairs in order.

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Benefits of a Systematic Approach You generally deal with managerial problems alongside others. Working in project teams is the norm. In addition to your team, you need people from various divisions in the company: IT, finance, executive decision-making. You will deal with the owner and the victims of the problem, and with people assisting you in solving the problem even though it does not affect them. You need to establish everyone’s position clearly. Here, a systematic approach is your friend. You ask questions, and make sure to take at least the following steps: 1 You find out which parties are forced to deal with the problem, aside from the problem owner. Who are being troubled by the problem? Those are the victims. 2 You establish which parties will be important in investigating the problem. Will you need permission from certain people? Are they allowed to free up time for you? Who is in charge of financial support, of manpower? Are you free to approach clients for interviews? 3 You determine what information you need to deal with the problem. Where can that info be found? 4 You track down the people you will need at later stages in advance. Whose help will you need to analyse the problem? These are your helpers. 5 You set up a division of labour for your assistants. Who does what? How do you put the right people in charge of the right tasks? You may need to split up the problem. This will allow you to assign specific project team members (and their skills) to different parts of the problem. 6 You formulate a list of conditions. Are there any limitations? Is it possible to provide a solution without having to deal with legal complications? Are redundancies on or off the table? When does the problem need to be resolved? This approach will give you an insight into what people to recruit for your project team. It generally also sheds light on any parties that still need convincing, and indicates people who will not be of much use – either actively or passively. People not affected by whatever bottleneck you are looking into, tend not to be desperate to work on its solution with you. They will be too busy doing what it is they are doing. Some employees may simply not feel like participating. This phase tends to be where, you, the trouble-shooter, come across sensibilities or hidden agendas that may hinder an effective approach; useful information when it comes to determining who you should count on in your project team, and who you can expect to help pave the road to a solution. Think, for example, of managers who free up funds or employee time to assist in your approach.

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Walking A Thin Line Some plans of attack are described down to the last detail. Every individual activity during every individual phase has been fully worked up. You might read: ‘Project member Young to interview product line staff in week 1. Interviewees: Johnson, Rudd, and Williams. Young to ask members 12 questions (see appendix 3.2) each. Information from interviews to be processed according to model found in appendix 3.3 …’ As plans go, this is quite a detailed example. The particular situation to which it is applied may require this level of detail. In other cases, it may be more useful to limit the description of your planned activities to broader terms. Note that there is no fixed rule regarding level of detail of a plan of attack. But there are some guidelines: * Accuracy is key. Depending on the situation, activities should be described broadly or in detail. Your description should be able to serve as your fall-back during the problem-solving process. The level of required detail of your approach tends to become clear as you are formulating it, since that is when you become aware of what exactly the job requires. * Avoid obligatory descriptions such as: ‘This is required in order to involve all employees in the approach’. Be selective! You do not always need to involve everyone in all aspects. Focus on the people who have to deal with the problem. And avoid creating expectations you may not be able to live up to. If people are asked for their input, that does not necessarily mean they get a say in the decision-making process. Be sure they understand that. Make sure there are no false impressions. * Demonstrate that you are able to solve the problem. Among other things, your capability will be demonstrated by a carefully and accurately projected final result. A solid approach and a capable project team will do the rest.

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Summary

▶ When formulating your problem-solving approach, you describe you planned actions as precisely as possible. You review all actions needed to successfully resolve your approach. You need D3 (Do, Discover, Decide). Do is everything you need to undertake; Discover is everything you need to know; and Decide is selecting the appropriate options.

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▶ The next step is systematically mapping your problem. This starts with asking the question you need answered, including at least the following: * Which parties have to deal with the problem? Who are the owner and victims of the problem? * Which parties are in charge of the required resources? * What information do you require? * Whose help will you need during which phases of your approach? Who are your helpers? * What is the division of labour in your project team? * What are the possible or existing limitations? ▶ Once you have the answers to your questions, you can begin formulating your approach. This requires precision. When formulating an approach, consider the following pointers: * Be accurate in describing your activities. You should be able to rely on your descriptions later. * Be selective! Only write down what you need for your problem-solving approach. Do not overstate or embellish matters. * Demonstrate that you are able to solve the problem.

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Core Concepts

D3: Do, Discover, Decide

A method used for bringing order to a problem-solving approach. D3 stands for Do, Discover, and Decide. Do is everything you need to do for your approach to work; Discover is everything the parties solving the problem need to know; and Decide is selecting the appropriate options from the multitude of aspects of an often complex problem.

Research Cycle

A systematic approach to research performed in order to obtain required information. Allows the researcher to arrive at a conclusion through a stepwise process, thereby answering a previously formulated problem definition.

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In Search of the Unknown

You have established what the problem is in broad terms. But this may not have answered all of your questions. You may still be wondering what exactly is going on, and what is causing it. You need hard data. The information you need may already be known, or at least available. Often, your next step will be to conduct research. You deal with knowledge-based problems in phase 3 of the MPSM, analysing the problem.

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This chapter addresses the following questions: * What exactly is the bottleneck? * What is causing it? * Why have earlier solutions not worked?

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Sequential Order 67

Measurement Levels 64

Statistical Relationship 67

Causality 67

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Pimp My Production Line

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Monday morning, a vase of flowers on the desk. Location director Brown’s first day at work. He checks his watch. Nine o’clock. Brown opens the meeting. He tells everyone a little about himself, and suggests the managers to briefly introduce themselves and what it is they do. He also asks everyone: What do you feel is the company’s most significant problem, what do you think is causing it, and how do you think it could be resolved? The marketing manager jumps the gun: ‘That is an easy one. Our production costs are too high. As a result, we do not turn a large enough profit. It is all down to those old, unreliable machines. So here is my solution: We invest in new machinery.’ The operations manager gives a consenting nod: ‘I could swear I was listening to myself, just then. Last week, production hall 2 was shut down. It took nearly all of Thursday to fix the issue. I would think those machines are over 20 years old by now. There is only so much they can take. The machinery is in desperate need of renewal.’ It goes on for a while, one manager after the next. Brown listen to his team patiently. Once everyone has had their say, he takes the floor: ‘Thank you for your input. I must confess to some slight confusion. You all seem to know what the problem is, you seem to know its main cause, and you even seem to know how it should be solved. So why has nothing happened. Why is there no replacement plan for the old machinery? What is holding us back?’

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The assembled group is quiet for a moment. Then, the financial manager says: ‘Money. There is none available for renewing the production line.’ The operations manager shakes his head at that: ‘The problem is not that there is no money. It is to do with the unwillingness to spend any. New machines would set us back a little in the way of finances, that is true. But did you know there is an entire industry devoted to refurbishing the older models? There is a company in Lancashire, specialising in reconditioning factory machinery. They inspect the old machines and revise what they can. We would only need to replace the machines they cannot pimp up. So we would be able to reconstruct out entire production line from the refurbished existing machines and maybe one or two new models.’ ‘I was under the impression pimping is something that was only done to old cars’, smiles Brown. ‘All kidding aside: We should start by having a look at what is actually going wrong during production. Pimping up our existing machinery could be a solution, but we would first need to establish that our machines are suitable for that process. And who knows, there may be other things issues as well. I am going to assign a project team. We need to start making some headway. I want this problem analysed in detail, so we know exactly what is going on. We need to prevent investing time and money in a solution that does not address the actual problem. Dig deep, I say. We will untangle everything until we are sure we know what is causing us grief.’

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Looking Closely at the Problem How is the problem constructed? What details would give you greater insight into the cause(s) of the problem? Why are those old machines more often turned off than on? Is it a matter of production efficiency? If so, during what production stages? And why have other, earlier solutions not worked properly? You have already had a quick and dirty look at the problem. You have also gained insight into causes and effects using the problem cluster. You know what core problem you want to address. Next, you need to start digging deep. You begin your research. That can also involve looking at possible causes you had not yet assigned to the problem cluster. In essence, it boils down to three activities: 1 Filling in details 2 Looking for causes 3 Reviewing why earlier solutions have not been satisfactory

§ 6.2

Locating the Problem During the problem analysis, you take a renewed and very close look at the problem you have selected. You look for details; for example, where exactly is the problem located? You know there is a problem along the production line, but that is quite a large area. Where is the hitch? Is it an assembly problem, or a matter of supplying resources? You try to visualise the bottleneck as accurately as possible.

§ 6.3

Problem analysis

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Researching Causes Next is a quest for possible causes of the problem. Closely examining the production line may have told you that the problem comes from a tardy supply of resources. So your question then is: What is causing the resources to be delayed? You attempt to solve a knowledge-based problem using the research cycle (see Chapter 11). That is the default procedure when research is needed. Sometimes, other people may already have the information you need. All you need to do is check. But in many companies, you will need additional information – knowledge obtained through research. There are various successful researching methods. You can conduct interviews, or reference scientific literature to find known causes of similar situations. Whatever your approach to research, you need to have some idea of where to start looking. And that is easier said than done. You may have found many different causes, and not be able to research them all. It is better not to waste your time in pursuit of the most unlikely causes; so your focus should mainly be on the most logical ones. During this initial orientation, it may be useful to have a sneak peek at some of the available literature on your subject. It may give you some ideas for possible leads in your research. Do not jump to conclusions – you will not find any new answers without first conducting research.

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In your research, you should mind the following: 1 First list the possible causes of the problem you know of. 2 Involve others in looking for causes. Talk to key figures and people dealing with the problem. 3 Select a limited number of causes to examine in detail. This is often not as simple as it seems, since you may have found many potential causes following your interviews and talks. People rarely come up with exactly the same causes. Their ‘truth’ is often based on a certain (self)interest. Deciding which causes are the most important is something you should do yourself.

6.3.1

Quantifying Variables

An action problem is expressed in variables. This was part of phase 1, defining the problem. A knowledge problem is also expressed in variables you have concretised and made quantifiable using indicators. Indicators are also applied to the possible causes of a knowledge problem. Causes can be just as vague as the actual problems. For example, insufficient communication between internal and external service departments is a possible cause of unsatisfied customers; a cause you can research. But what exactly is the nature of this cause of dissatisfaction? Are there no meetings scheduled involving both departments? Is the external service department unavailable because its staff tends to be on the road? Do the representatives give only the same information as the people available via the helpdesk? Does the internal department adequately respond to signals received by the external department? These types of questions all represent possible indicators of ‘insufficient communication’.

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Measurement levels

Measurement Levels You have assigned variables to the causes. You have also concretised the variables using indicators. Your next goal should be to measure the indicators as accurately as possible. There are four different measurement levels. These levels vary in terms of precision: 1 Nominal Variables. The values of the variables are not quantitatively related. Religious conviction is an example of a nominal variable. You cannot, for example, say that a protestant church member has either more or less religious conviction than a member of the catholic church. They just have different convictions. 2 Ordinal Variables. The values of these variables make some claim as to quantity, but their exact value is unknown. They can, however, be ordered or sorted - for example from greatest to smallest - since you know that one value is larger than another. You do not know, however, exactly how much larger. If, as part of a questionnaire, you are asked to what degree you agree with a certain statement, there tend to be different possible answers – for example, five options ranging from ‘fully disagree’ to ‘fully agree’. This tells you that someone who indicates a ‘somewhat agree’ option is less in agreement than if they had selected ‘fully agree’; but you do not know exactly how much less. 3 Interval Variables. The values of these variables are expressed in numbers, as amounts. It is possible to comment on differences between values of variables. The interrelationships between the different values are still unclear. Say that you leave your office building, which is currently at a snug 20 degrees centigrade. Outside temperature is 14 degrees. Wearing only a shirt, you are suddenly quite chilly. You run toward your car. You have experienced a 6 degree drop in temperature. But you

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cannot express your feeling of chilliness as having increased by around 30%. If you express temperature in kelvins, the office was at 293 and outside was at 287. That is a decrease of around 2%. Percentages, in this case, are meaningless. 4 Ratio Variables. Like interval variables, the values of these variables are expressed in numbers. Here, however, it is possible to establish the ratios between values. If, for example, the political party in office goes from 88 seats to 66, then that is a 25% decrease in the number of seats. Researchers should strive for the highest measurement level, ratio level. This allows for the most quantitative of analyses. Tests may be conducted in a such a manner as to yield results that can be measured at a higher level. Employee satisfaction, for example, can be measured at ordinal level using a questionnaire. Alternatively, you can measure how many people leave the company during a year. The higher the measurement level, the better you can compare results. But you should always be mindful that your ‘hard data’ does not lead to a false sense of security. Counting how many employees leave tells you nothing about why they leave. Is it because their partner has found work elsewhere, or because they are expecting children? Or does it actually have to do with how they enjoy their work? Questions focussed on the direct causes of employee turnover – ordinal measurements, in other words – would probably give you a better insight into the matter in this case. 6 The reliability of your research results is another factor influenced by the measurement level of your variables. A measurement level can be a deciding factor when determining which statistical tests you can and cannot apply. This will have an effect on, for example, the size of the sample used.

6.3.2

No Research for Its Own Sake

The problem analysis is concerned with relationships between causes and effects. You attempt to visualise all factors that could influence the solution. This can lead to a vast swathe of possible causes and issues coresponsible for the problem. In your quest for explanations of problems, do not feel you should untangle every single little detail. There is no point in conducting research for the sake of having conducted research. Some problems do not require a cause to be fixed. Imagine you are staring in confusion at the nail that was lying on the road, now sticking from your wheel. You may be wondering how that pointy little thing got to be where it was, but the answer to that question will certainly not bring you any closer to the problem of your flat tyre. For that, you will need to set to work fixing it. If the nail is still lodged in there, your first order of business is to take it out; now, you are one step closer to a solution. Similarly for an incidental case of pneumonia: If you have it, you will want to be rid of it. The doctor may not particularly care whether you contracted it when you fell into cold water, or were standing somewhere draughty for too long. Currently, the problems that need to be resolved are a painful chest and possible fever. But if your pneumonia is not an isolated event, if you have been suffering from it more frequently, then that is a different story altogether. In that case, the doctor will most definitely want to check for bacteria, viruses, or fungi. And, perhaps, the conditions that caused you to contract your illness should be established to help prevent the same thing from happening again. Here, the problem that needs to be solved is your susceptibility to pneumonia – not your pneumonia itself.

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Three Tips for Researching Causes 1 When faced with a multitude of causes, choose only the most important ones that you know you will be able to influence. Something you cannot alter does not need to be researched. The weather, for example, is a major factor in revenues of holiday camp sites or ski lodges. But try as you might, you will not be able to make it snow or cause the sun to come out. 2 Keep in mind that some causes trump others. Do not turn all causes into knowledge problems to be researched using the research cycle. Focus on those causes you expect to have a major influence on the solution. 3 Try to examine as many relationships as you can within your available timeframe. Scientifically speaking, nothing should be excluded. But since time is virtually always limited, you need to be practical about matters.

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Using Models to Outline Variable Influence

The relationships between the problem and its causes can be outlined in a model, a depiction of reality. This model is similar to the problem cluster you used during phase 1 of the MPSM. You work with a variable that may be expressed using indicators, and arrows that indicate causal relationships. Note that there are several differences between this model (see figure 6.1) and a problem cluster (see figure 6.2). You fill in the model with whatever it is you do not know and therefore need to research. The problem cluster is filled in with things you already do know, omitting things that you do not. And another difference: A model is about establishing relationships, not about depicting known relationships. You do not assign values to the variables as you would in a problem cluster, but you adjust the variables to discover if there is a relationship. For example, a model can be about the relationship between working conditions and motivation. The problem cluster would address these aspects in terms of specific qualitative values, such as poor working conditions as the cause of low levels of motivation. The following is a depiction of outward similarities between a model and a problem cluster. Figure 6.1 shows the model of the problem: ‘What is the relationship between working conditions and motivation?’ You use this model to indicate that you wish to examine what happens to employee motivation levels if there is a change in working condition. FIGURE 6.1

Relationship between working conditions and motivation MODEL

Working conditions

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Motivation

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Figure 6.2 shows a part of a problem cluster for the problem: ‘Motivation levels (too) low’. You use the problem cluster to indicate the encountered relationship between levels of motivation, which are too low, and the working conditions, which are poor. This shows you that poor working conditions cause motivation levels to be (too) low, and that these conditions are therefore a core problem.

Part of a problem cluster for the problem ‘Motivation levels (too) low’

FIGURE 6.2

PROBLEM CLUSTER

Poor working conditions

§ 6.4

Motivation level (too) low

Considering Earlier Solutions

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Problems are often older than when you just start researching them. A production line in difficulty will have had troubles long before today. And it is frequently already known what the bottleneck is; delayed resource supplies, for example. In that case, there will have been suggestions for stricter terms and contracts with supply companies – but for some reason, those contracts were not implemented, or did not have the desired effect. You will often find earlier proposed solutions in company documents, some entirely untried. During this phase, you should review whether those earlier solutions can actually work this time around.

Causal Relationships During the problem analysis phase, the most important feature is relationships between problems and their causes. A relationship can be defined as a causality, a cause-and-effect type relationship, if it meets the following three criteria: 1 There is a sequential order: The cause must precede the problem, the effect. The cause of poor working conditions leads to the problem of poor motivation levels. 2 There is a statistical relationship. If the value of the cause changes, so should the value of the problem. The reverse is also true: if the value of the problem alters, so should that of the cause. If the weather is good, you will find many people at the beach; if the weather is bad, the beaches tend to be empty. This is a statistical relationship between the quality of the weather and the number of people at the beach.

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Not every statistical relationship is a causal one. By way of example, consider the once established statistical link between the number of people enjoying a beach-front coke and the number of people drowning in the sea. You should not conclude that drinking coke is hazardous to your health – the number of drowning victims could also be higher as a result of more people visiting the beach on a sunny day. More people are likely to have a refreshing beach-side coke on a sunny afternoon than on a rainy morning, since there would be fewer people at the beach anyway. 3 There are no alternative explanations for this part of the problem. There is nothing but one single cause of the problem. For example: A company was suffering from a large amount of downtime. The only apparent cause was motivation. The problem disappeared when the manager addressed the motivational issue. He told a colleague with the same problem: ‘When I came on board, people’s motivation went up, and downtime fell.’ The other manager shakes his head and says: ‘We were in the same boat: a lot of downtime, poor motivation. Even when I addressed the issue of motivation, nothing happened to the downtime.’ The first manager comments: ‘I clean forgot! I also brought in some new machines. That helped improve motivation and decreased downtime. The new machines were the actual solution to the problem.’ In this example, no causal relationship exists between motivation and downtime. But there was a causal link between two other relationships. The first is the quality of the machinery and motivation – the new machines were more convenient to work with. The second was between the quality of the machines and the amount of downtime – the new machines produced better quality products. The only factor causing the problem in this case was the quality of the machines.

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Summary

▶ During the problem analysis phase, you conduct research because you need more information. You review your problem identification and problem cluster. You fill in the missing details. You look for as yet unknown explanations for your problem. You re-examine previously suggested solutions. ▶ You use the research cycle to solve your knowledge-based problem. This takes you to the answer to your problem definition step by step. ▶ During your research, you keep the following in mind: * Make sure you quantify your variables using indicators. * Formulate your variables at the highest possible measurement level. * Limit your research to important causes that will contribute to the solution. Review as many relationships as you can in the time you have. Choose only causes you can affect. * Use a model to record the relationships between problems and causes. * Look for causal relations and not just statistical ones.

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Core Concepts

Causality

The relationship between cause and effect.

Measurement Levels

Levels at which variables can be measured. There are four: * nominal variables. Values are named. * ordinal variables. Values are ordered. * interval variables. Distances between variables are known. * ratio level variables. Ratios between variables are known.

Problem Analysis

Researching a problem to find out its causes, and establishing interrelationships between causes and effects.

Statistical Relationships

A numerical relationship between a cause and a problem. Involves variables whose values change together.

Sequential Order

A condition for causality. A problem is always preceded by a cause.

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An Overview of Options

Now that you have established the size and shape of the problem, it is time to start working on a solution. You review your options for removing the problem from the equation. You weigh up the various options, and provide an insightful report for your client. As such, during phase 4 of the MPSM, you formulate alternative solutions, so that management can make a final decision. 7

This chapter addresses the following questions: * Which criteria should a solution conform to? * Which criteria are the most important? * How do you arrive at alternative solutions?

Consensus 76

Sub-Attributes 78

Qualified Majority 76

Majority Rule 81

Attributes 77

Lexicographical Method 81

Non-Compensatory Criteria 77

MoSCoW Rules 82

Conjunction Criteria 77

Synectics 85

Cut-Off Criteria 77

Morphology 86

Killer Requirements 77

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HQ in Hampshire or Hertfordshire?

Selemat Makan and HongKong Food have joined forces. The two major suppliers of Asian foodstuffs have decided on an equal authority merger. The first problem they run into is where to establish their headquarters and central storage facilities. Should they go for Hampshire, known for its large Indonesian community in addition to being the base of operations of Selemat Makan? Or in the south of Hertfordshire, nearer the London basin – a major international melting pot and home to HongKong Food?

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The management boards are unable to decide. They have postponed making the final call for now. A project group has been asked to provide advice. Project leader York Fu has invited both managing directors for a meeting. He subjects both to an intensive interview. First, he asks whether it is essential that the new headquarters and central storage are located close together. Then, the following questions follow in rapid succession: * Who are involved in the final decision? Both boards? Or just the directors? * Does the advice need to be limited to either Hampshire or Hertfordshire? Or would the newly merged company also consider other options?

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* Will the final decision be made based on majority rule? Or must all parties reach consensus? * What are the most important criteria? Are they all equally important? * Does either director have any personal preference? And on, and on… York Fu’s barrage of questions seems inexhaustible. The directors are first asked to debate the issues. Then, for each question, they have to provide only one consensual answer. All questions answered, York Fu and the project group set to work. Two weeks later, he presents their findings to the gathered deciding parties of the new Asian foodstuffs wholesaler. He has brought a PowerPoint presentation illustrating the decision-making process. It details which arguments were considered, and how important each argument was considered to be. Based on a professional approach, York Fu and his team have provided a decision document containing several options. Using their work, York Fu could make a final decision – but he will not be the one doing so. That honour is left to the deciding parties, hopefully along the lines of York Fu’s proposal.

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Seven Steps to a Possible Solution You have examined the problem from all angles. You know exactly what is going on. Time for a solution. But what criteria should that solution fulfil? Say your company needs to deliver parcels around an urban area. Do you choose the latest Mercedes Vito or a Ford Transit for your drivers? Or do you opt for an environmentally friendly approach, choosing transportation by bicycle instead of delivery van? What is clear is that the current fleet of cars has fully depreciated. What you need is a possible way out of this dilemma; preferably more than one. You have to come with and review several options. You do so according to the following seven-step plan: 1 Defining the decision 2 Defining the decision-making process 3 Establishing criteria 4 Scaling criteria 5 Weighting criteria 6 Coming up with optional solutions or using existing possibilities 7 Evaluating options

§ 7.2

Defining the Decision You start by carefully defining what the decision actually entails. Does your client only have to choose which car would be the best option for delivering parcels around the urban jungle? Or is that decision preceded by another process, where the best mode of transportation for the narrow, pedestrian oriented city streets still has to be determined? In case of the latter, the choice is not between different delivery vans, but between, for example, a bike, a lorry, and an electric van or coach. You may first have to decide whether the currently used vans even need to be replaced, or whether they should merely be refurbished. That all depends on the findings that follow from your problem analysis. The question of the best type of delivery van only becomes relevant if you know for sure that new delivery vans are what you need.

§ 7.3

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Defining the Decision-Making Process The party responsible for a final decision often consists of a group of people. The members of such a group may hold different or even conflicting views. One thing the decision-makers definitely need, however, is structure: a set of rules used to guide the decision-making process. The following are important points to consider: * Establish who the decision-makers are. Is it down to one individual, or is it the responsibility of the entire board of directors? Take into account any sensitive areas or issues, such as possible relationships between one of the decision-makers and, for example, a supplier of delivery vehicles. Such issues need to be approached mindfully, and possibly diplomatically. * Determine how the decision is constructed. Is it a one-time vote between all possible available options? Or is the number of available options gradually reduced, with each round of selections using a decreasing number of decision-makers? For example, a project group may be put in charge of reducing a longlist of suppliers to a shortlist. That shortlist is what the board uses to make the final decision.

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Consensus Qualified majority

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* Agree on rules for the decision-making process. Are the decisions to be based on consensus? Or are they down to majority rule? And, in that case, does it concern standard or qualified majority? * To weight or not to weight. Weight is what indicates how important different criteria are. The higher the weight, the more important the criterion. Assigning weight to criteria has its pros and cons. An important reason in favour of working with weighted criteria is that if you do not assign weights, you run the risk of missing out on the best option. Say you have to choose between two cars. Meaning to save time, you do not assign weights to individual criteria, being speed, fuel efficiency, and number of passengers. Your first option, car 1, has a top speed of 200 kilometres per hour, good fuel efficiency, and room for four individuals. Car 2 has a top speed of 220 kilometres per hour, is less economic in terms of fuel use, and is able to accommodate five individuals. As you have not weighted these criteria, you will probably choose whichever car scores the highest in the largest number of criteria – here, car number 2. But are those additional 20 kilometres an hour that important if you have to deal with a 120 kilometre an hour speed limit? Does the extra passenger room even matter if you are likely to make most of your trips by yourself? Are those criteria worth the additional cost from the increased fuel consumption? Maybe, maybe not. The only way of knowing for sure is by weighting. Weighting does have its drawbacks. It is demanding work, and not always reliable. People sometimes (sub)consciously assign different weights from what they have indicated. And they do not think to inform the trouble-shooter of that fact. Criteria can be split up into different parts which can be weighted individually. That is a process that can carry on to near infinity, causing you to lose sight of the bigger picture. In some cases, it does not matter whether or not you weight your criteria. If all criteria are approximately equally important, weighting criteria will often lead to the same choices as not weighting them. You can generally only establish whether criteria are equally important once you have an idea of their weights. To weight or not to weight? Whatever you do, at least try to estimate whether there are clear potential differences in weight between criteria. * Be mindful of subjective elements. Subjective elements are issues which, considering the goal of the decision, should not actually be of influence to the decision. Questions to ask are: Is the company’s best interest always the prime concern during the decision-making? Are there any personal interests involved? Or are the decision-makers focussing on their individual departments instead of the organisation as a whole? Rational and irrational arguments can sometimes be intertwined. Try to take these different motivations into account, and take control if they (threaten to) influence a decision. * Ensure the decision-making process is clearly established. It is not just a matter of options, of contents. The manner in which decisions are made, the process, should also be clear from the start. Items to consider are agreements concerning majority rulings or consensus, or on whether or not to weight criteria. If the decision-making process is unclear, people are able to disregard procedure. * Guide the procedure. This is a task which can be performed by a secretary of a project group or the project leader, along with a chairperson or director. Agree on a set of ground rules regarding following procedure.

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* Consider the acceptation process of the final decision. Every decisionmaker will have to eventually accept the decision, even though it may not be the outcome they had hoped for. If they do not, the decision may not be implemented properly. This means that you will need to do more than merely inform parties following a decision. You need to involve people in the process.

§ 7.4

Establishing Criteria Before you start thinking about solutions, you should first establish the criteria. Do not first come up with a solution and then invent a matching set of requirements. Some problems are in desperate need of a solution. Some people may choose any available option without knowing exactly how it contributes to the solution of the problem. The preference for a particular solution can often occur without the actual pros and cons being known. One example is the popularity of the Joint Strike Fighter jet among the Royal Netherlands Air Force. That branch of the military had had good experience in using the F-16, an American product. The French Mirage fighter jet, on the other hand, was much less well-known. For that reason alone, the Rafale, the follow-up to the Mirage, had little chance of being selected as the replacement to the F-16. Since the JSF is also an American product, it was favoured as the replacement from the outset. When establishing criteria, also known as attributes, you will need to deal with a client’s preconditions and wishes. There may be some criteria that need to be met by definition. These are known as non-compensatory. You will find various different names for these criteria in relevant literature, such as conjunction criteria, cut-off criteria or killer requirements. Scoring too high or low on one of those criteria is not something that can be redeemed, or compensated, by scoring higher on another. When choosing a new type of delivery van, one non-compensatory could be a sliding door allowing the driver to more easily reach the packages. In that case, a vehicle that is more fuel-efficient, less expensive in terms of initial purchase, and whose safety performance is rated higher, still would not qualify if it lacked a sliding door.

Attributes Noncompensatory

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Conjunction criteria Cut-off criteria Killer requirements

A client can set various demands. Are they looking for a risk-free solution? Or are they motivated by money, wanting the most profitable option in spite of potential risk? These are some possibilities you could be faced with: * Effectiveness. Maximising effect. The client is looking for the best possible solution, even if it is a relatively expensive one. What counts, are the gains. If the gains concerned are monetary in nature, this is known as ‘maximising profits’. A client can require an investment has to be recouped within a certain time-frame. This requirement can be subject to various calculation methods. Calculating the break-even point will tell you when a solution stops costing money, and starts to generate a profit. Calculating the net present value lets you calculate the free cash flows of various options, for example. * Efficiency. Limiting resources or maximising profits. Efficiency is concerned with two things: either use the minimum required resources to reach a certain goal, or us the available resources to reach maximum revenue.

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* Risk. Minimising risks. Here, avoiding danger is the motto. This can mean you will reach solutions which, when used on a worst case scenario, will still lead to the best possible and/or still acceptable result. There may be more effective options possible, but those are considered too perilous. Criteria tell you something about the effect of certain options on the solution to a problem. When valuing those effects, you can encounter two possible obstacles. The first is that you may not be fully certain a particular effect will actually occur. For example, you expect that an advertising campaign will lead to increased turnover for your product... but how high should you expect that increase to be? In these types of situations, it is best to work based on expectations. This will let you work according to a worst case and/or best case scenario. There are also those effects which are difficult to quantify. That is the second obstacle. Effects in question can, for example, be concerned with the ease with which internal reorganisations, possibly consisting of forced redundancies, are accepted. Try expressing that one in numbers! Your best bet, instead, is to use different variant possibilities which you can then compare. The level of acceptance for plan A could be greater than that for plan B, even though you may not know exactly how much greater. You could try using a questionnaire to establish preference – which is a seemingly simple solution. But you should nevertheless be careful when interpreting the results. The fact that 60% of personnel prefers plan A and 40% prefers plan B does not guarantee that plan A is preferred. The 60% may feel that plan A is only marginally better than B, and the 40% may feel that plan B is vastly superior to plan A. Properly interpreting the outcomes will require you to analyse the arguments used in favour of the different plans. This will help you predict whether or not the 40% group may also settle for plan A.

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§ 7.5

Scaling Criteria Eventually, you will want to know which option best fits the established criteria. For that, you will need to assign scores to each criterion. You can do so by awarding points on a scale of 1 to 5 to each of the different criteria, for example. Each point on the scale should have a particular meaning. You could choose to award only 1 point for an average fuel efficiency of 1 to 8 mpg (miles per gallon) or lower. Between 8 to 16 mpg would score 2 points, and a car averaging 32 or more miles to the gallon would score the maximum of 5 points. Another option is to award a value of 1 to the worst possible score, and a value of 5 to the best possible one without using numerical values.

Sub-attributes

Each criterion can be divided into sub-attributes. You split up your criteria into separate components. When choosing a new office building, its accessibility by car can be a criterion. Sub-attributes could be the relative distance to motorway exits, the average lengths of on-route traffic queues, or the amount of available parking space. Each of these sub-attributes awards a criterion points on a certain scale. The advantage to this method is that it allows you to cast a much more concrete verdict. You can also weight the sub-attributes. But there is a danger of losing track of the bigger picture, and getting bogged down in prominent but ultimately uninfluential

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details. And you may also wonder whether there is any point to the laborious task of weighting a seemingly endless list of sub-attributes. This detailed approach should therefore be reserved for those situations where you expect it can have a serious impact on the final decision. Establishing sub-attributes is a helpful way of clarifying how a particular attribute is actually defined. It tells you at a glance what an attribute is (or is not) concerned with This will help you form a better picture of which attributes to weigh up against each other. This idea is supported by academic research (see insert ‘A Weighty Matter’). Test subjects in laboratory conditions were asked to weight attributes used in a decision-making process. The subjects, not used to the concept of weighting, used between a third to a quarter of their invested energy in coming up with and combining subattributes. Some of these subsection criteria were weighted, some were not. Attributes and sub-attributes are not assigned points on a scale for nothing. You are looking for the most appealing option. In doing so, you look for two things: The extent to which an option solves the problem, and whether an option would produce any side effects. A solution to combat low levels of productivity could have a negative effect on quality, for example. You would therefore award this option fewer points for the ‘quality’ criterion. Side effects need not always be unintended, however. If the main reason for replacing machinery, for example, is to prevent failures or drop-outs, an intended and planned advantage could be that the newer, more modern machines improve product quality.

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The point scale does not have to be restricted to scores between 1 and 5. What matters is that you work as accurately as possible. What this means is that, in practice, your scale should neither be too coarse nor too fine. You could express the level of comfort of a car in a scale of 1 to 100, for example. But a deciding factor between scoring 53 and 54 points would be nearly impossible to imagine. The same problem would not occur for a scale from 1 to 5. Whatever you do, make sure you are consistent. This means that the difference in appeal between the scores of different attributes has to be comparable. For example, a car can be appreciated in terms of safety and comfort. In that case, the values for scoring 4 points would need to be the same for both comfort and safety. You cannot have a score of 4 mean ‘appealing’ when it comes to comfort and ‘unappealing’ when it comes to safety. Additionally, you also need to take into account the laws of economics, such as the law of diminishing marginal utility. In short: More is not always better. If you feel like a snack, then chances are that two hotdogs later you will value the third one on your plate somewhat lower than the first two. This has relevance on the distance between the values on your scale which, in this case, need not be constant.

§ 7.6

Weighting Criteria Using the scores you have attributed to the different criteria, you can begin comparing available options. But comparing scores is not the short of it: Not all criteria are equally important. You can distinguish between levels of importance by weighting your respective criteria.

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When choosing a new restaurant location, an organisation looking for many on-site visitors will value accessibility over the presence of other restaurants in the vicinity. The latter can be an advantage if local restaurants are only visited infrequently. So where those restaurant holders may value the presence of other local eateries at 0.2 times the score, a nearby bus stop and a large on-site parking lot could be valued at a factor of 0.3 and 0.4 times their score respectively. The weights should be used in combination with a point scale. Table 7.1 is an example of using scores and weighting criteria in practice.

TABLE 7.1

Example of options with weighted criteria

Options/Criteria

Car accessibility Bus accessibility Representative location Local restaurants Final score for each option

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Option 1

Option 2

Score

Weight

Total

Score

Weight

Total

2 3 4 5

0.4 0.2 0.3 0.1

0.8 0.6 1.2 0.5

5 4 2 1

0.4 0.2 0.3 0.1

2.0 0.8 0.6 0.1

3.1

3.5

There are various methods of assigning weight, for example: * awarding marks to different criteria * distributing a number of points between criteria * using pairwise comparison valuation. First, choose between criteria 1 and 2: which of the two is more important? Then, compare criteria 1 and 3. Keep comparing pairs of criteria and determine which is the more important of the two for all pairs of criteria. The winning criterion is awarded a point; whichever criterion has the most points is the most important. Note that these are ordinal values. Once you have finished comparing the pairs, you will be left with your various criteria sorted in a ranking order: criterion 1 is more important than criterion 3, criterion 2 is more important than criterion 1, and so on. While this does allow you to distinguish between the levels of importance of particular sets of criteria, it does not allow you to weight the criteria (e.g. saying that ‘criterion 2 is weighted at 0.4’ or ‘criterion 1 is weighted at 0.2’). A possible solution to this problem is to start by performing paired valuations, and then distribute points between the criteria. This will allow you to distinguish between criteria in terms of numbers of points; but it should not affect the order of your initial paired valuations, of course. Choosing repeatedly from a number of available options. Think, for example, of the way many career choice tests are structured. Career choice test attempt to help people make a decision by giving them an insight into how important they find various job aspects. Looking at criteria such as task variety, status, salary, or job security, candidates are asked to choose between different sets of three or four professions several times. Realistically, this requires candidates to assign weight consciously or subconsciously. The value or level of importance your candidate awards to the various criteria is determined from their choices. If someone

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consistently picks whichever job has the highest salary, that means they value money relatively highly. There are some disadvantages to this method, however. One is that you are trying to help people by weighting certain aspects; but actually, you are letting them choose before you do the weighting. Another issue is that your subjects’ decisions are influenced by the knowledge that they are taking part in a test. Real-life decisions may actually be influenced by numerous factors, such as emotional distress. Weighting criteria helps you maintain a reasonably reliable approach; it does not particularly matter whether you ask people to do so by choosing what they feel is most important, or by using paired valuation or another method. For routine decision-making, these approaches are all up to 70 to 80% accurate. That does mean, however, that there is a 20 to 30% possibility for error - a substantial percentage for high-stakes decisions. Just look at the hordes of students who take part in career tests in high school or secondary school; at least 1 in 4 of higher vocational education or university students drops out as a result of having made what they feel is ‘the wrong decision’. Majority Rule In practice, the process of decision making is different from choosing between theoretical numbers on paper. People often do not actually weight the various criteria. They may simply assume that all criteria are equally important, and then choose whichever criterion has the highest score on the largest number of criteria. This is called majority rule. Alternatively, participants may already know which criterion is the most important, but not how important the other criteria are. This will often make them choose whichever option scores the highest in the most important criterion: the lexicographical method.

Majority rule

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Lexicographical method

Some criteria can be hard to weight properly. You could weight the criterion of ‘brand’ when shopping around for a new car, since you’re looking to buy a Ferrari… but what is that weight based on, realistically? Is it a matter of emotion, of personal preference? That personal preference may end up costing you a lot of money. You may feel a criterion is important, but be unable to explain exactly why that is. In that case, be honest with yourself and make your decision. Either trust your intuition and weight that criterion substantially, or use only justifiably important criteria (and ignore any ‘emotionally charged’ ones). Difficult decisions can be made easier by staggering the decision-making process. First, limit the number of options by setting several noncompensatory criteria; that is, those qualities or aspects that must be met by definition. If you are looking to buy a car, for example, one of your criteria could be ‘maximum price’; call it €20,000. In that case, you would not have to worry about the fuel efficiency of a brand-new Rolls Royce, or whether the latest S-class Mercedes comes with remote controlled doors. And, in setting this maximum, you have also influenced the importance of potential status gained from your new car; a €20,000 car is unlikely to be an important status symbol. Using a number of non-compensatory criteria will generally help limit the number of options to something more manageable. But do make sure you do not eliminate all options outright.

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The Importance of Argumentation Sometimes, the final scores of the available options may be grouped very tightly together. In that case, the weights of the different attributes should determine the final decision. However, those weights may be viewed differently by clients on the one hand, and advisors on the other. In addition, the process by which people arrive at weights is generally uncertain. Nevertheless, we do have some understanding of the theory behind weighting. Whichever attribute is recommended by the most arguments tends to be seen as the most important. These results, while having been found in scientific research, have not yet been sufficiently proven or published. You are recommended to think long and hard about the importance of your selected attributes. For example: Do the arguments used factually apply to the attributes concerned? You might, for example, think that a high maximum speed can help a motorcycle avoid dangerous situations. That reasoning is flawed. Getting away from trouble does not require a high maximum speed per se – what is needed is the ability to accelerate quickly and be on your way at the first sign of trouble. You can come up with dozens of criteria, and divide them into layer upon layer of sub-attributes. But make sure you first determine which attributes actually matter. If you are looking into the safety levels of a vehicle, physical weight can be a sub-attribute. But is it really the vehicle’s weight you are after? Safety is more of a matter of chassis strength and stopping distance. The stronger the chassis, the heavier it probably is (barring the use of carbon fibre or certain polymers); the heavier the chassis, the longer the stopping distance. If you are unable to determine chassis strength or stopping distance, leave out those criteria and use overall weight as a replacement. But if you do manage to find out those figures, for example through a dealership or the manufacturer, you can leave out the overall weight indicator instead. Go through all of your (sub-) attributes in a similarly critical fashion; with any luck, your list of attributes will be much shorter by the time you are through.

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Next, you review whether all sub-attributes are relevant at all times. You take into account the different phases of the problem-solving process, for example by first choosing a prototype which you can improve or expand upon at a later date. In project-based development of software used by employees, for example, the wish list is often quite comprehensive. A new CRM (short for ‘customer relation management’) system should, according to the marketing department, have a virtually endless list of options for managing customer relations. The purchase of a CRM system, therefore, can be preceded by drafting a long list of criteria and sub-attributes, which are then weighted. Those various wishes may, due to restrictions in time or budget, be impossible to fulfil immediately. In that case, you will need to establish some priorities: things that needs to be done right now versus things that can potentially wait till later.

MoSCoW rules

MoSCoW Rules In these situations, the MoSCoW rules (Stapleton, 2005) are truly a boon. You can use these rules to classify the demands or requirements into different categories, from those that are essential to those that would be an added luxury. This will allow you to develop a less complicated basic trial version, for example. That trial version can then later be enhanced gradually. Table 7.2 is an example of the application of the MoSCoW rules to the

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purchase of a content management system (CMS) for the development of a scheduled new website, and the translation of the rules into weights.

TABLE 7.2 MoSCoW rules applied to the purchase of a content management system. The final column indicates how the MosCoW rules can be interpreted in terms of weighting.

MoSCoW-rule

General

CMS website

Weight

Must Have

Solution will not work if these demands are not met (minimum)

Customer uses website to access database

Prerequisites, non-compensatory criteria

Should Have

Solution will still work without meeting these demands (would be required if more time were available)

Search functionality in database

High weight

Could Have

Demands can easily be left out

Extensive search functionality by words, sentence fragments, key phrases, and dates

Low weight

Want to Have but Will Not Have This Time Around

Clients wishes which cannot be implemented now

Personalised customer pages with overview of consulted pages, orders, and offers

Very low to no weight (or criterion is dropped)

A Weighty Matter In the field of decision-making theory, much is paid to how weights are ascertained and what types of circumstances can influence them. Does the way the problem is formulated influence the weight people ascribe to a criterion, for example? Little is currently known about the thought processes people experience when establishing weights: the importance assessment. Research (Heerkens, 2003, and Heerkens, Norde & Van der Heijden, 2011) indicates the following trends: * Actors performing importance assessments spend a lot of energy on clarifying what the attributes actually mean. This is not done by defining attributes, but by splitting them up into as many as forty sub-attributes. * They are not concerned with whether all (sub-)attributes have been identified. They hardly assess the importance of any attributes. For each individual attribute, they establish how important it is without involving any of the others. In addition, they do not rely on a common denominator, such as money. * People who are more experienced in assessing importance hardly differ from people with little experience when faced with a new assessment.

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The following is a list of tools which can be used to ensure a more structured importance assessment process: * Consciously assessing whether all attributes have been identified. * Explicitly linking argumentations to (sub-)attributes. * Relating (sub)attributes to each other (as in the delivery vehicle’s safety example. You would use the weight of the chassis as a sub-attribute if information about stopping distance or chassis strength are unavailable). * Leaving out superfluous attributes. * Making explicit any emotionally charged attributes as best as possible.

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§ 7.7

Providing Alternative Options or Using Existing Possibilities There are various means at your disposal for finding more than one solution. First, before you reach out for help, try doing things under your own power. Try to come up with as many optional solutions as you can during this stage. Nothing and no one is standing in your way of coming up with original ideas. Only when you have had a long, hard think should you turn to others. There are several methods used to generate optional solutions. Older solutions provided by others are sometimes an excellent answer to your current question. Consult relevant professional literature and published scientific research. Or interview people, and see what options they can come up with. In addition, there are creative techniques which you can employ to produce new options.

7.7.1

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Existing Research

Professional literature and scientific research may offer a practical solution when you are looking for answers to your questions. Many problems have already been presented with solutions courtesy of other experts. You are free to copy from their work, as long as you properly source your material. If you intend to adopt procedures, methods, tools, or others solutions used in corporate life, mentioning a source generally will not be enough. Here, patents and copyrights are important barriers to consider. But as for existing scientific research: Do not hesitate to use what others have already provided. Do make sure, however, that you carefully consider whether their options, often conceived to combat a more or less different situation, can apply to your specific case.

7.7.2

Creative Techniques

Aside from using scientific research, there are more creative ways of reaching practicable solutions. Coming up with optional solutions is down to creative skills. How do you use your and others’ inventive genius to arrive at different solutions that also work well? There are different methods used to tap into hidden sources in various situations. The following techniques are used frequently: * Brainstorming * Synectics * Morphology Brainstorming A brainstorming session allows a group of people to come up with a lot of ideas at leisure. There are few restrictive agreements. Each member comes up with a couple of ideas in turn. Meanwhile, the others do not give any comment. Each participant only comes up with new suggestions. Those suggestions can be in line with or even directly opposed to what has already been mentioned. The point is to use association: One idea gives birth to another. From the long list of ideas, you take whichever inspired notions seem most promising. Then, as a team, you determine which ideas would or would not be suitable for further development. Brainstorming is appropriate when you need to come up with a new name for a product, but not when you

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are dealing with a technical flaw in an engine that keeps overheating, for example. It is always a definable problem whose solution can be described in a few words, without needing to draft complicated schedules or drawings. One variation on brainstorming is brainwriting. This involves people writing their ideas on forms which are passed around; this is another way of having group members inspire each other without having the entire group comment on what is being suggested. Once the forms have been used by all group members, you have each individual indicate which ideas they thought were the best. The resulting list of ideas can then be used by the same or another group to formulate new ideas. In practice, brainwriting is more effective than brainstorming. Brainstorming is attractive to the participants. They feel involved in the problem-solving procedure, even though they understand their idea may not be the one that gets selected. Synectics You can also choose a more structured technique. Synectics is a method which imposes substantive rules on the associations. You take your problem along on a jaunt to another world, such as classical antiquity or the animal kingdom. You review whether you can find an analogue problem in that environment, and solve it there. That solution is what you use on your actual problem. Similarly, the designers of the F/A-18 fighter jet at McDonnell Douglas (now Boeing) explored the world of the insects. They studied how these diverse little creatures land from an airborne state. In this case, it was a grasshopper whose legs formed the inspiration for the landing gear used in the F/A-18. Synectics can be a way of inspiring progress. But always make sure whether the solution is fully applicable. Not all realms, times, or places are the same; as a result, solutions from one situation may not work in others. The grasshopper’s eight legs, for example, translated into three wheels for the F/A-18 (Rozenburg & Eekels, 1998).

Synectics

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In order to successfully remove cancerous tumours, doctors studied the art of warfare in the Middle Ages. How do you breach a heavily walled city? Randomly hammering away at the main gate itself is not at all effective, since that is where the defences are the strongest. And it only lends itself to attack by those soldiers on the exact front lines. But if an army focusses its assault on key positions along the wall’s perimeter, the defending party will have to divide their strength to try and absorb the attack. A similarly staggered approach is used by specialists in order to safely remove tumours. A laser beam can be used to remove growths – at a risk of burning off healthy surrounding tissue. Just as with the hostile city, doctors instead focus on several points along the tumour’s edge. They use laser beams which, individually, are not powerful enough to damage healthy tissue. But when these lasers focus on the same spots, they can burn and combat the cancer effectively. Synectics and variants of this technique can help you arrive at original and inventive solutions. You can use a contrasting example, or work on the basis of a more extreme solution. For the development of a fast car, for example, you can first design the slowest moving car, or imagine one that travels at the speed of light. Whatever variant you choose, be sure to take your time and, if the situation calls for it, work with different participants. The most important thing is that you do not overlook any important, promising solutions.

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Morphology

Morphology There are also methods which use fixed patterns to help you arrive at a desired design or solution, for example through the use of morphology. You divide the problem you are trying to solve into different pieces. You come up with variations for each piece. Then, you combine the variations into new formations. This will help you arrive at new, original insights – only one of which you will eventually need. Say there is a factory that produces hammers, and that they are looking to branch out to a new product. Morphology can be a great asset. First, line up the characteristics (variables) and their values into something resembling this: * Force: manual * Function: hitting nails into a board * Operating method: hit the nail * Components: head and handle * Materials: steel and wood In order to arrive at a different product, you change one or more of these values. For example: * Force: hydraulic, electric, pneumatic * Function: drilling screws into a board, paperweight, removing nails from a board * Operating method: exert pressure, push, pull, wrench * Components: power transfer, position detection * Materials: concrete, plastic, cardboard, paper

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This new list can lead you to a new machine which drills screws into wood electrically: a screw gun. The advantage of using morphology is that it allows you to work in little steps, thus reducing the length of the creative leap needed to arrive at a novel idea. A disadvantage is that you assume a certain object or situation as your starting point. This can cause you to subconsciously limit your train of thought to a certain direction, potentially leading to tunnel vision.

§ 7.8

Evaluating the Attractiveness of Available Options Indicate which option will be the most effective in solving the problem. Use a matrix such as the one shown in table 7.1. You offset the options against criteria which you have scored and weighted. The option which achieves the highest overall score is the one you, the trouble-shooter, recommend.

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Choices Come with Strings Attached As an advisor, you may occasionally find yourself in a predicament. Your presentation of available options is not just a matter of technique. One the one hand, you want to inform a client of all options and their associated costs as best as possible. On the other, you need to make choices and limit what is a complex matter. And there are some strings attached to the choices you make. You run several risks. Those who limit themselves to technical analyses will turn up with complicated proposals. The image of the situation they portray is seemingly objective, and often concerned with only part of reality. And that is the reason this approach does not work. Interested parties can use these types of results to further whatever agenda they may have; a situation not at all conducive to swift decision-making. Those who make their client’s life easier by limiting the number of options, on the other hand, will be blamed for exerting an overbearing influence on the decision-making process. Every trouble-shooter makes their own professional calls in judgement. There is nothing at all wrong with that. But it is important that, during the entirety of the process, you properly communicate with your client. That means interim and periodic meetings. And if adjustments have to be made, you will need to re-secure the appropriate parties’ commitment. These procedures have been developed in project management techniques, such as Prince 2 (Koning & Van Onna). There, the project leader reports to the client if progress threatens to deviate from what was initially agreed upon. The project leader describes the cause and its effects, alternate solutions for reducing or undoing the deviations, and their consequences for costs, returns, and risks.

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Summary

▶ When formulating optional solutions, you look for options which can be used to solve a problem. You generate and compare several options. You advise you client of the best solution based on your argumentation. You provide you client with a comprehensive report on the different options. You prepare the decision-making process for the selection of a solution. ▶ You describe what exactly needs to be decided on. ▶ You establish the decision-making process and develop a method for deciding which solution to employ. ▶ You establish criteria. You indicate possible options. Ask the client what they require of a solution. 7

▶ You assign points on a scale to the criteria, for example between 1 and 5. ▶ You weight the criteria. There are several methods for weighting criteria which can involve users of the final solution or product. ▶ You come up with options or use existing possibilities. First, think of as many possible solutions as you can. Then, involve others in your search for alternative options, for example by conducting interviews or using creative techniques, such as brainstorming, synectics, or morphology. Be sure to use information or solutions other researchers have already come up with, if possible. ▶ You indicate which solution is best suited to solving the problem.

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Core Concepts

Attributes

Characteristics of solutions.

Conjunction Criteria

Demands that a potential solution has to meet by definition. Scoring too high or too low in these criteria cannot be redeemed or compensated by scoring higher elsewhere. Conjunction criteria are also known as cut-off criteria, non-compensatory criteria or killer requirements.

Consensus

A state where all parties participating in a meeting are in agreement.

Qualified Majority

An agreement which sets additional demands with regards to decision-making. For example, decisions will only be validated if at least two thirds of the decision-makers agree, or if at least 50% of the relevant decision-making parties is present.

Lexicographical Method

A method of deciding using a set of ranked criteria. The options are first compared based on the most important criterion. Whichever option scores the highest, is selected. In case of a tie, the next-most important criterion is used until there is a winner.

Majority Rule

A rule that favours the option which scores best in the largest number of criteria. Here, all criteria have equal importance, and none are weighted over others.

Morphology

A creative technique used to come up with (design) solutions.

MoSCoW Rules

A method of prioritising requirements and demands that are part of a solution. The consonants in Moscow represent must have, should have, could have, want to have but will not have this time round.

Sub-Attribute

Part of a criterion, a characteristic of an option. Splitting a criterion or attribute into component parts yields subattributes.

Synectics

A creative technique for coming up with solutions based on looking at a problem in a different realm, time, or place.

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The Client’s Move

With your job as advisor complete, you have presented the client with a report detailing several possible solutions to choose from. You have provided argumentation as to which option would be the best match. Nevertheless, your client may not end up following your suggestion. But why would that happen? There are reasons for deviating from an expert’s opinion. It is all down to the client’s wishes in phase 5 of the MPSM, choosing a solution. This chapter addresses the following questions: * Does the decision-maker’s responsibility for the consequences of a decision influence their choice? * Do decision-makers and advisors view assigned scores and weights of options the same? * Do decision-makers differ from advisors in their risk assessment?

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Probability Theory 95

Scenario 95

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A Colourful Advert

‘There is good news and bad news’, says Brent Shaper over the phone. The CEO of Cardboard & Paper International, a merger of cardboard manufacturer Outmark and packaging company Ditchfield located along the Port of Tilbury, is in good spirits. ‘Bad news first: We have had to dismiss all three of your options for our advertising campaign. But fear not. You need not spare any expense in turning all eyes to our strongest and cheapest moving box yet. We want a run of six half page ads in the national and regional papers you suggested. That is quite close to your option C. What we will be adding, is colour. We want our logo to be in colour.’

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‘That will be an additional 250,000 pounds. Is that not slightly over the top for a 3-by-5centimetre square that reads Cardboard & Paper in green?’, project leader Mark Courtland delicately points out. Shaper will not have it: ‘Mark, there are no second impressions. Go big or go home.’

with the advertising agency for days, and the project team has spent hours crunching the numbers to come up with three fully fledged possibilities for a good but affordable advertising campaign. The three variants were compared exhaustively. After much careful deliberation, Courtland decided to suggest option C: a £1,950,000 advertising campaign which, like the other two options, would still be within the realm of the 2-million-pound budget. And now the board of directors have decided to add a cool quarter million on top of that. Just because the logo has to be in colour. ‘It looks nice enough, that little hit of green, but it is too dear.’ That was what the gathered professionals concluded regarding the use of a highlight in the adverts. ‘So what could have happened during that management meeting?’, thinks Courtland. He will have to confer with Shaper tomorrow. First things first: Time to call the advertising agency. There is advertising space that needs to be booked.

Feeling somewhat deflated, Courtland puts down his phone. He has been consulting

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THE CLIENT’S MOVE

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Three Reasons for Deviating from an Advisory Report You have finalised your consultancy report regarding the company’s production capacity problems. You have carefully weighed up the various options based on the overall picture. You have conducted analyses of their cost effectiveness. You have weighted various criteria. In doing so, you have provided your client with a clear insight into what would be the best way of dealing with the problem. As an example, you have suggested moving to a different production location. But management decides differently. They have a different view of the potential risks concerning recruiting technicians in the area you have suggested. The company is to remain where it is. But management does give the go-ahead for the construction of a second production hall on the current premises. Your advice, carefully considered though it is, has not been followed. Since your advisory report is based on your judgement, a client may have a different view of the available options. This means the client can have a different interpretation of the options, potentially leading them to choose something else than what you have suggested. Three explanations for a client deviating from the ‘best’ option: 1 The client is responsible for the decision and its consequences; the advisor is not. 2 The advisor and client may view assigned scores and weights differently. 3 The decision-maker assesses the risk differently.

§ 8.2

Politically Charged Decisions ‘The decision-maker has to make their call in the context of the organisation. This context is something the advisor needs to steer clear of.’ This is a view occasionally held in boardrooms. Advisors whose advisory report is discounted, tend to take a disparaging view of a decision following such a statement, and comment on its ‘politically charged’ nature. In their eyes, the company has opted not for the best possible choice, but for one that would, for example, sit all right with important suppliers. Which is something management might hope to benefit from.

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But taking a political view of decisions is not necessarily a bad thing. Once you make a decision, you will need to deal with its consequences, its outcome. That is quite a responsibility to bear. In the realm of business, executive decisions can have far reaching consequences the advisor may not always be able to fully appreciate. Should Apple begin marketing an improved iPad based on rumours that their competitors plan to come out with new models, superior to the current generation of iPads? Introducing a successor would mean the end for a current hit product. Or should Apple remain confident in their current model’s ability to deal with the competition for the time being? ‘No authority without responsibility’: Wisdom fit for framing on a boardroom wall. The advisor dots all i’s and crosses all t’s to arrive at the best possible option. The decision-maker can take that information on board, but will also look further. Decision-makers have to deal with strategic consequences, and make their decisions in relation to the solution of other problems.

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The advisor compares the different options and assesses what the best possible option would be. The decision-maker studies the advisory report and the choice as it is presented, but makes their choice independently. The difference here is one between evaluating and choosing. The decisionmaker also has a responsibility towards shareholders. The manager who makes the decision is usually a generalist who places the choice for a certain option in a broader context. The advisor is sometimes not even asked to take the context into consideration. There is often no information available. Soft factors, such as ambition, the quality of management, creativity, or workplace atmosphere, may also be involved. These are difficult to measure. The advisor focusses on assessing the alternatives they, in their role as expert, have come up with. Decision-wise, the option of having someone contribute their solutions without any obligations is a good thing. That contributor will not be hindered by others, or by consequences outside of the reach of the investigation.

§ 8.3

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Considering Other Interests If yours were the final call, you would undoubtedly not blindly limit your decision to the options you were presented with. Other issues can also have their influence. Additionally, there may be certain theoretical reasons for not choosing the most attractive option. The advisor finds the best possible solution by calculating score times weight, taking into account any minimum requirements. A manager faced with a decision may use other benchmarks, for example that of majority rule: the manager chooses whichever option scores the highest in the largest number of attributes. A choice like that is easily justified to others: every advantage is an argument in favour, and complicated explanations of why one advantage is ever so slightly more important than another are superfluous. But there are disadvantages to this approach. An alternative that does not score very high marks all round, but does score highly in the most important criterion, may easily be discounted. This method is likely to be used if none of the options are head-andshoulders above the rest. In these cases, securing acceptance of the decision can be more important than choosing the best option (which, in all likelihood, is not that much better than the alternative that was selected). Remorse Another motivation may be an attempt to avoid potentially regrettable situations. Nobody likes to feel buyer’s remorse once they realise they have made a ‘wrong’ decision - something that can happen if the scores of the various options are grouped very closely together. Deciding on the best option may mean having to miss out on all the perks of another. The decision-maker may assess the advantages differently, or take the convictions of other interested parties to heart when making the decision not to follow the advisor. Those parties may view attributes with lower scores as more important. Acceptance of others, incidentally, is not a separate attribute. Sometimes, the decision-maker implicitly takes the wishes of others into account, for example those of fellow directors or employees. It is not a good idea for the advisor to take this issue of remorse into account – any final consideration is the client’s own responsibility.

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Handling Risks Advisors naturally take the risks of the different options into account. But decision-makers do so explicitly. They regard the risks in a broader context, and can also factor in the risks into the scored and weighted criteria is different ways. Here are some examples: * A high threshold value for a non-compensatory criterion. The minimum requirement for the capacity of a new production line may be 50,000 coffee machines per year, even though you have room to store only 20,000; the same kind of decision as demanding a new car has at least five seats even though there are only three of you. What you do not use can be used as backup. * Different scenarios. A decision is based on various scenarios (possible future states). Scenario 1, for example, may leave little room for employment opportunities, but more for economic growth. Scenario 2 comes with a solid increase in employment opportunities, at barely any economic growth. * Flexibility. Managers may decide on purchasing a computer system with capabilities far beyond what is currently required. These capabilities may consist of functionality they do not yet fully grasp, but which the company may come to need at a later date. Compare this to purchasing a heavier, more expansive car with a tow bar. Should you later decide to take a caravan holiday, you will already have the car you need for the job. You have added an extra attribute. This can be specific (e.g. a tow bar) or more generally applicable (e.g. ‘flexibility’). The disadvantage of the more general attributes is that they are hard to properly value. * Modifying/Adapting weights. Decision-makers weight attributes differently if they assess the risks involved to be higher. They might choose for a fleet of fuel efficient cars that nevertheless did not score the best in a costs/benefits analysis. The company is prepared to put more money down because they are taking into account a future increase in fuel prices. In the field of probability theory, risk is defined as probability times consequences. Probability is the number of times something occurs, usually expressed as a percentage. The consequence is the loss in value you incur if the risk occurs. Based on the probability times consequences formula, risks are assessed as acceptable or inacceptable. For frequently occurring risks, using the probability theory definition works well. For example: your experience with customers is that 1 to 2% does not pay their bills. This means you do not know which customers this applies to, but you do know how much money is involved. If you have very few customers, the same does not hold: if only one customer skips the bill, the effect on the total revenue will be much greater.

Threshold value

Scenarios

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Probability theory

Some consequences may be so major as to face the decision-maker with an impossible task. Think, for example, of the field of nuclear energy, where the effects of a nuclear disaster would be incalculable. Due to the extreme nature of the results, any potential risk would be too great. In effect, this would prevent you from making any decisions at all involving nuclear energy. But since it comes with major advantages, there are governments willing to invest in the construction of a nuclear power plant. Their decision, in this

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case, is not merely based on probability times consequences. Indeed, it is often unclear how such decisions are actually made. One possible explanation is that the decision-makers also take a longitudinal view of the consequences. In that case, the question may become: What would be the effects of a nuclear disaster on people born 40 years from when it occurs? They would not know of a world any different from the one they live in. If, in 2020, the nuclear plant in Dungeness suffers a meltdown, it could take out a large chunk of England’s Southeast. Someone who wakes up in Maidstone-sur-Mer in 2040, now home to England’s coastline, will not feel any sense of loss for the High Weald, Royal Tunbridge Wells, the White Cliffs of Dover, etcetera. While this approach seems exceedingly cynical, the alternative, of course, is just to move away from using nuclear energy altogether – discarding any and all life-changing advantages in the process. Aside from risk acceptance, the decision to build a nuclear power plant is also based in the realms of legitimacy and equity, even ethics – topics not covered in this book.

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Summary

▶ The final decision is the client’s prerogative. Based on other considerations, a client may deviate from professional and founded advice. As such, advisors and decision-makers can arrive at different choices. These may often come across as politically charged in the eyes of the advisors. That need not be the case – it need not even be a bad thing. ▶ The trouble-shooter compares the options and assesses what the best possibility would be. The decision-maker reviews the submitted selection, but their decision is an independent one. The decision-maker places the choice for a particular option in a broader context, for example involving a level of responsibility toward shareholders. The advisor does not have this responsibility. ▶ When assessing alternatives, an advisor reviews scores, weights, and prerequisites. The decision-maker may deal differently with the weighting, for example by choosing to apply majority rule. This leads to whichever option conforms to the largest number of attributes. ▶ Decision-makers explicitly take all risks into account in their deliberations. They view the risks in a broader aspect than the advisor. This may lead them to make different choices.

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Core Concepts

Threshold Value

Minimum amount (of products needed for profitable production).

Probability Theory

A method used to calculate the risks involved in an option or event. Risk is defined as probability times consequences. The probability is the average number of times a certain thing occurs, usually expressed as a percentage. The consequence is the loss of value incurred when the risk occurs. Based on the probability times consequences formula, risks are assessed as acceptable or inacceptable.

Scenario

A construction of a possible future state of an aspect of the world. Scenario planning is a way of using various scenarios as the basis for a decision, since it provides an insight into how certain options would work in practice.

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A Systematic Approach

The die is cast. Management has discussed the plan and chosen a solution. The next step is its execution, which is about details and ways of making the advice a reality. You draft an implementation plan in phase 6 of the MPSM, implementing the solution. This chapter addresses the following questions: * What are the steps that need to be taken in order to develop the plan? * What is needed to mobilise employees?

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Implementation Plan 103

Bottom-Up 104

BCH Model 103

Change Management 104

Top-Down 104

Yammer 104

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Developing a Training Plan

A local company’s commercial branch is due an upgrade. Time to send the managers back to school. A certificate from a written course in marketing is no longer sufficient. Company leadership is in need of management strategies and techniques. MBA is the new standard for Sales. Thus sayeth the board. A training plan details how the current managers and team leads should develop. Now it is down to the plan’s execution. The HRM department holds a meeting. There is work to be done. A project group is tasked with filling in all the details of the training plan. A sub-group will tackle the necessary steps. A legal advisor will review the contracts that employees will need to sign. The HRM team has questions, many questions. How many working hours will be allotted for employee studies? Will this lead to staffing issues? And how will any issues

be handled? Are employees required to refund the training fees if they leave within the next three years? Or should that be a five-year term? Can you force people to stay on at the company for a certain number of years following the training? Two HRM members and a communications advisor are asked to consider communications. How are they going to get managers back to hitting the books? An MBA title is a nice thing to have, but studying takes time – even free time. Is everyone willing to invest theirs? The head of P&O tells her staff: ‘For a moment, I was sure that finishing our training plan and getting it past the board would have been the end of it. But looking at what we still need to do, it is almost like we have not done any work at all.’

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A SYSTEMATIC APPROACH

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Two Principles of Implementing a Solution Using your formulation of alternative solutions, you have provided your client with an insight into what would be the best option for dealing with the problem. Also, you have given a global indication of what the consequences of that choice would be. Meanwhile, the client has made a decision. Your job now is to provide a detailed overview of what is needed in order to develop the solution. You describe the steps needed to realise your advice in an implementation plan. You work according to these two principles: * You briefly describe the activities that need to be performed, step by step. This is the technical side of your plan. * You describe the roles of individuals, and how to get them on-board with the change. This is the social side of your plan, involving change management.

§ 9.2

A Brief Description You indicate the activities the organisation will need to perform. You answer many operational questions. A management MBA course is concerned with questions like: How do you get all managers to pass? Which training organisation will you ask for input on the programme? How do you enable possibilities for studying? How do you deal with understaffing issues once managers head off to business school? What kind of contract should you and your employees agree upon? Are they allowed to study during working hours? Are they required to refund the training costs if they leave? Can you compel people to stay on for three years following their studies? How do you handle long-term students? Choices also occur during the execution. Just like with assessing and deciding on alternatives, these lend themselves to using criteria. First, line up what a solution needs to conform to; then, select the most attractive one, for example a particular training organisation. Your implementation plan is a brief description of the necessary activities. Make sure it is appropriately detailed. Do not overdo it on the specifics. What needs to be clear above all is the reason why the company is taking this course. Develop your solution; do not come up with new ones.

§ 9.3

9 Implementation plan

Realising an Idea Solving problems means changing, reorganising activities, and restructuring organisations. There are different ways of doing so, for example by assessing according to the BCH model (Balance, Cohesion, and Heterogeneity) by Weggeman et al. (Kor, Wijnen & Weggeman 2007). This model demonstrates the cohesion between six organisational aspects, including culture, structure, and management style. McKinsey’s 7S model can also be of help. Whatever method you use, make sure you consider the following points when writing your evaluation plan: * Per intended measure, indicate what the goal or sub-goal is. Include the costs and the responsible party/parties.

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Top-down

Bottom-up

Change management

Yammer

* Check up on the progress of changes. To that end, develop a system of control. Do not be conspicuous when monitoring people; this will earn you their aversion. * Be clear in your intended method. Do you opt for a top-down approach, putting management in charge of the solutions or change, making communications a one-way affair, and leaving middle management in charge of informing staff? Or do you go for a bottom-up approach, putting more emphasis on the importance of employee input? * Make sure to respond adequately to possible resistance against change. Take into account existing corporate culture. Invest in change management. Involve people in the different steps of the change process. Let them take part in courses. Clarify which decisions they have a hand in. Make sure their expectations are realistic, and let them know which factors are beyond their control. * Organise internal communications. Consider how you are going to inform everyone working in the company. You can choose from a vast array of tools. The transfer of information can occur through staff or work meetings, the company president’s blog, intranet pages, social media platforms like Yammer, the company magazine, or a special project journal. Make sure people are able to respond to the information provided.

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Summary

▶ Your implementation plan is concerned with precisely detailing the execution of the solution, as well as with the necessary steps to ensure everyone is on board. ▶ Be brief and precise in your description of steps required to properly implement the solution. ▶ In case of choices, use criteria - just as with assessing and deciding on alternatives. ▶ Be systematic. Provide sufficient detail for each measure, and perform progress checks according to a system of control. ▶ Anticipate resistance to change. Be clear about the intended approach: top-down or bottom-up. Let people take part in courses. Organise internal communications.

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Core Concepts

Bottom-Up

A direction of communications in an organisation. Bottom-up means workplace input is possible.

BCH Model

A model used for an internal analysis of an organisation. The letters B, C, and H represent Balance, Cohesion, and Heterogeneity. The model demonstrates the cohesion between six organisational aspects. These are: strategy, structure, culture, systems, management style, and personnel. All of these aspects are interrelated. A change in one is felt throughout the others. Each aspect has a hard (quantifiable) and a soft (unquantifiable) side. Internal communications can influence parts of the BCH model

Implementation Plan

A plan of attack which details what needs to happen in order to implement adopted advice in an organisation.

Top-Down

A direction of communications in an organisation. Top-down means all communications originate from management and move along any existing intermediate layers until they arrive at the workplace.

Change Management

Supervise, organise, and (have others) execute change within an organisation.

Yammer

Yammer is like Twitter for companies. One of various social media platforms which work by submitting short messages.

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Keep Improving

By and large, the problem has been solved. The goals of the problem-solving method seem to have been met. But that does not always mean smooth sailing. What could be the cause of that? You proceed with an evaluation in phase 7 of the Managerial Problem-Solving Method. You review whether the solution works as intended. A full evaluation of all the steps in your problem-solving approach; that is the main task during phase 7 of the MPSM, evaluating the solution. This chapter addresses the following questions: * How do you convince people of the value of an evaluation? * How do you handle an evaluation professionally?

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Evaluating the new website

It took some doing, but the evaluation is underway. None of the parties involved were very keen on cooperating, but management has managed to persuade them. Generally speaking, everyone is pleased with the new working method. ‘What is the point in talking about it?’ they said at first. Eventually though, they popped by to evaluate the new website for packaging suppliers.

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For some time now, the suppliers of pallets, labels, cardboard, and other packaging materials have been signing in weekly to the website of a food manufacturer. This provides the material planners with a rapid overview of over a thousand materials which are in stock at 69 suppliers. Things used to be much different: The email servers would become overburdened with the massive load of messages to-and-fro. The new approach seems a vast improvement. But it is not without the occasional hitch. In one case, the quality of the pallets supplied was not as expected. Or the red colouring of the labels deviated too much from the standard. How come these oversights had not been spotted? Fritz Button is head of the packaging department, and in charge of the evaluating discussion. First, he asks those present if they are satisfied with the new working method. There is no one who wants to return to the old system; that much soon becomes clear. Overall, things are going well.

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But there are some flaws in the execution, which mainly seem to involve the quality of the materials supplied. What could be causing the issues? According to Sven Grubman, the company relies too heavily on brokers who grab their materials from wherever they can. ‘Those guys are cowboys. Today, they will order pallets from Oslo, but tomorrow, if the price drops twenty cents, they will happily switch to a Bulgarian supplier. All they are concerned with, is price.’ Bert Latefield confirms his colleague’s statement: ‘Those companies will shop around anywhere, particular where printed matter is concerned. Anywhere from Belgium to Southern Europe. And if they are looking at large batches, and they have the time, they turn as far as Asia.’ ‘So how do we deal with this?’, asks Button. There are some suggestions to contract other suppliers. ‘So who do we trust instead? Would it not be better to sit down with the most important materials suppliers? We are a major client for them – it should not come as a surprise that we expect their quality to match’, says Grubman. That is a suggestion Button can work with. He wants to set out straight away: ‘Sven, would you gather up some examples of good and bad pallets? I will get in touch with the guys who supplied them. And Bert, who do I talk to about the labels?’

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Three Principles of a Structured Evaluation Your implementation provided a description of how the solution should be implemented in the company. By now, the organisation has adopted the solution to the problem defined in phase 1 of the MPSM. Next is the evaluation, an investigation into the effects of the change. The structured way of approaching an evaluation is by using a list of focal points, such as establishing the goal; finding out who the interested parties are; reviewing which problem indicators you want to evaluate; and setting terms for the evaluation method. In addition, an evaluation can be used to track down those effects that you had not considered or had not thought of as important. Say, for example, that you are the operator of a taxi van service and want to evaluate your product. The evaluation criteria in that case are linked to your passengers’ wishes. As it turns out, your transportation is not limited to passengers – you also operate as a small package delivery service. In that case, you will also need to evaluate your cargo. That might lead you to purchase new vans to deliver packages across town. A structured evaluation operates on three principles: * Convincing people of the usefulness of an evaluation. * Evaluate all phases of the MPSM, not just the final decision itself. Make sure you also review issues you found earlier during your evaluation, but which seemed unimportant at the time. * Deal with the evaluation professionally.

§ 10.2

Evaluation as a Balancing Item Users or decision-makers will rarely be the ones asking for an evaluation. They tend not to see any point in it. Or they are not interested in its outcome. Evaluating scores low on the scale of priorities. So if you want to be able to perform a proper evaluation, you will need to be persuasive. And take into account these potential arguments, facts, and attitudes you may encounter on your path: * ‘There are better ways of spending our time’. Investing in the new and novel tends to go down much better than challenging established activities or working methods. * You may find that the goals that were set were too vague. Keeping things vague can be in people’s interest. This makes it impossible to compare the actual situation to the desired results. * ‘That is just the way things are around here. Cannot be helped’. Office staff may have become used to the occasional network outage. Employees have come to accept the issue. And they are not looking forward to the fuss involved in an evaluation. * Those who have championed the new approach, can often also be found to oppose evaluating. An evaluation might show that the new approach does not work after all, and that things need to be changed again. That could be construed as a loss.

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Evaluations. Nobody seems to be looking forward to them. These feelings of evaluations being a necessary (or even unnecessary) evil are further strengthened if nothing is done with the resulting information. You can establish that something does not work. This is immediately followed by the question: ‘So now what?’ Results can also lead to bickering. ‘Huzzah,’

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exclaim the supporters of the new approach following an 8% increase in revenue. ‘An abject failure,’ mutter its opponents, because in their minds, an 8% increase nowhere near justifies the investments that have been made. In this case, it would appear that no clear agreements were made as to what would have constituted an acceptable investment or increase in profit. Either that, or people have simply changed their minds.

§ 10.3

MPSM: Guiding Along the Path of Evaluation The objections to an evaluation and its associated problems can be removed by applying the MPSM. You use the method to track down indicators and causes of the problem, which lead to the criteria to be used for evaluating solutions. This allows you to measure the effects to the solution. In addition, you will have set goals during the process of formulating alternatives. Those goals can be reviewed during the valuation to see whether the desired effects have been substantial enough. If not, you can go back to phase 3, the analysis of the problem. You may find causes for the disappointing results there for the taking. It is even possible that solutions you discounted earlier may end up being exactly what you are looking for now. The phases of the MPSM also guide you along the path of your evaluation, by reviewing your activities and findings at each different phase.

§ 10.4

Evaluating Systematically Take the people who fill in your questionnaires seriously. Do not merely send out a short email, but provide a good, attractive looking questionnaire. Make it easy to work with. People will feel less burdened if, for example, all they have to do is check a box for yes or no. Use as many close-ended questions as possible, but do allow people to write down any comments they may have.

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Summative evaluaton Formative evaluation

Your evaluation should leave nothing to chance. You will need a professional approach to gain the confidence of any naysayers. Be systematic, and first establish the actual goal of your evaluation. Three important things to consider in that respect are: 1 Checking whether your goals have been met. You measure whether the problem has been reduced without looking at its causes. This is known as a summative evaluaton. 2 Finding out the causes of the effects. For example, checking whether the implementation went according to plan. This is known as a formative evaluation. 3 Consider whether there are any possible improvements to be made. Once you have established the goals of your evaluation, your next step is to decide who is going to execute it. Should it be the trouble-shooter’s own job? They know the company’s situation, and as such have access to a wealth of information. But they are not impartial. The best approach is to contract an evaluator from outside. And hiring an advisor costs money, you can certainly demand a level of quality for whatever you spend.

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Line up the indicators of the problem you are evaluating. These consist of the most important indicators of your original problem, but also those issues subject to much uncertainty, the goals and effects whose importance was (or will be) recognised later, or which are valued highly by the higher-ups. You have to examine the full scope of the problem environment. That includes any unintended (side-)effects. Say you are investigating whether costs were successfully reduced by restructuring the production process. During your evaluation, you may learn that the reorganisation had a side-effect: Personnel costs have increased because more temps were hired. Those temps were needed because of an increase in absenteeism which itself had gone up because the reorganisation caused people to experience their work as monotonous. Involve Others in the Evaluation Find out who have an interest in the solution of the problem. You will soon arrive at individuals or groups who were originally bothered by the bottleneck. But you may need to expand the list from there, for example with people who are experiencing possible negative side-effects of an implemented change. Convince the interested parties of the usefulness of the evaluation. Make an inventory of questions they need answered. Try to get them to commit to the evaluation – a job which is made more easy by setting agreements with them. Think of the working method, others’ contributions to the evaluation, and the method of discussing the results. Out of sight is out of mind, so keep up the pace. If you fail to inform everyone on time, you may lose their support. Make sure you keep (and keep to) a tight schedule. Process the opinions of all parties involved in your final report. People need to feel heard. That will not necessarily mean you will arrive at a unanimous verdict, but it does mean that everyone will have to acknowledge that the end of the evaluation process has been reached. Set up communications regarding the results of your evaluation. Respond to the different needs for information of different groups. It is generally advisable to stick to the same story - but you may, for example, need to adjust the tone of voice, perspective, or vocabulary to your target audience. What is crucially important to one group can be considered an insignificant side-effect by another. Point out the importance of taking the improvements suggested in the evaluation seriously. 10 As the evaluation ends, the feedback process begins. Make sure that everyone is convinced of that fact. The evaluation is not the end – it is the beginning. There is a margin between the current and desired situations. The problem owner is experiencing a discrepancy between the norm and reality, an action-based problem. You return to the MPSM to focus on phase 1, defining the problem.

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Summary

▶ The evaluation of an implemented solution should be handled in a structured manner. ▶ People are often not keen on an evaluation. Convince them of its usefulness. ▶ Use your findings from the different phases of the MPSM if the desired effects of a change are not encountered strongly enough. You may find the causes in the analysis, or may be able to use solutions you had discounted earlier. ▶ Handle the evaluation professionally. Among others, this involves: establishing the goal of the evaluation, making an inventory of people experiencing the problem, formulating your goals as to be able to evaluate them after, determining the indicators of the problem, assembling the evaluation team and, above all, involving others in the evaluation process.

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Core Concepts

Formative Evaluation

A way of evaluating whereby you review the causes of the effects encountered. Reviewing whether the implementation has gone according to plan, for example. This also involves establishing whether your goals have been met.

Summative Evaluation

A way of evaluating which focusses on establishing whether your goals have been met. You measure whether the size or severity of the problem has decreased without looking at its causes.

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In Search of Knowledge

While dealing with your problem, you will run into questions or uncertainties. You will regularly find that you do not have the knowledge necessary to deal with these issues. To obtain that knowledge, you will need to conduct research. How do you solve knowledge problems? Using the research cycle, you systematically collect the data you will need during virtually every phase of the Managerial Problem-Solving Method. This chapter addresses the following questions: * What are the characteristics of a good problem statement? * How do you arrive at a research design? * What is the appropriate measuring method? * What conclusions can you draw from the data you have obtained?

Cross-Sectional Research 124

Operationalisation 126

Longitudinal Research 124

Validity 127

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An Experienced Sales Team: The Way Forward?

There is no more to be gained on the cost side of things. A thorough analysis of the disappointing quarterly figures concludes that the only way forward is to sell more. That is a bit of a bother. Major advertising campaigns and radio commercials have so far failed to do the trick. No choice but to hire better sales agents. Just a matter of pulling a couple of experienced, knowledgeable, and technologically savvy salespeople from a hat. But will that do the trick? Are those men and women guaranteed to up the revenue? By how much? Does existing literature indicate that a year’s worth of experience equals a certain increase in sales made? What you have are questions. What you need is knowledge. You can only begin to

solve your action problem once you have an answer to your knowledge problem or problems. You need to conduct research. You approach the issue systematically. You establish how your research should be conducted, step by step. Your goal is clear; so now you turn to formulating your problem statement, your research questions, and your research design. And then you start answering questions: what are the variables that make up the problem you are researching? How should you conduct your measurements? What about how the data is processed? Once you have answered those questions, you will have arrived at your preliminary destination: drawing conclusions by reviewing your problem statement.

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Gathering Knowledge Using the Research Cycle Solving a managerial problem does not seldom involve researching certain matters. Without the required data, your problem-solving approach will grind to a halt. Before you can continue, you will first need to solve your knowledge problem. Research is a regularly required step during nearly every phase of the Managerial Problem-Solving Method. Only phase 5, where you decide on which solution to choose for solving the problem, is an exception. All other phases occasionally involve a short trip to the eight phases of the research cycle, which are: 1 Formulating the research goal 2 Formulating the problem statement 3 Formulating the research questions 4 Formulating the research design 5 Performing the operationalisation 6 Performing the measurements (gathering data) 7 Processing the data 8 Drawing conclusions (reviewing the problem statement) As with the MPSM, you may occasionally need to move back and forth between the phases of the research cycle. When formulating the research design, you may find that it is not possible to gather data (i.e. measure) by questionnaires alone. If, for example, you want to investigate unconscious behaviour of members of a works council, you will not be able to do so using a questionnaire alone. You will need to adjust your problem statement, limiting it to conscious behaviour. Adjusting the work you did during earlier phases of the cycle is sometimes known as ‘retconning’. Retconning can occur during every phase following phase 1 of the research cycle.

§ 11.2

Formulating the Research Goal The research cycle starts with formulating the goal of your research. You state the reason for wanting to solve the knowledge problem. The results of your investigation are needed in order to deal with your action problem. During this phase, you have to define what it is that you need to know. You need the answers to a certain number of questions. What information is required? What is already known? What is still missing? What knowledge do you need your research to yield? Consider whether you need all missing knowledge right now, or whether part of it can wait till later. Based on your research results, you may have to conduct supplementary research later.

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Make sure you avoid conducting research for its own sake. An incorrect research goal is easily identified. Come up with a hypothetical answer to your research goal and see to what extent you can use it to solve your action problem. If the answer does not help or even matter, you will have asked the wrong question, and set the wrong goal.

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§ 11.3

Formulating the Problem Statement You have established why you need to solve your knowledge problem. Time to start the next phase: formulating the problem statement. Within the context of the research cycle, formulating the problem statement means formulating the knowledge problem. The smart thing to do is to formulate the problem statement as a question. Avoid using a statement or theorem for this purpose to make it easier to discern between an action problem (formulated as a statement) and a knowledge problem (formulated as a question).

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When formulating your problem statement, take into account the type of research you are going to conduct. Make sure you take the following steps: * Determine the type of research. Establish whether your research is to be explanatory or descriptive. Descriptive research is about establishing facts, for example the amount of absenteeism. Explanatory research is about relationships between variables, for example the causes of absenteeism. Whether you need to explain or describe depends on the research goal. * Define the variables. Similar to how you would as part of the MPSM, you define variables like the revenue per employee in euros, or the length of employment in years. * Indicate the possible relationships between variables to be researched. Note that this should be part of explanatory research only. There are several possible scenarios: – The first is that you know exactly which relationship(s) you want to investigate. For example, if the poor working conditions the office staff are subject to are most likely the cause of the low motivation levels, and management has already got a plan in place improving the situation with the help of new blinds and climate control. Here, your problem statement could be: To what extent do the working conditions determine the office staff’s motivation levels? – The second is that you are already aware of several causes, but do not yet understand which of these really matters. This means your problem statement should be defined along the following lines: To what extent do the working conditions, levels of training, and/or possible rewards influence employee motivation? – The third is that you do not have any clue as to the causes whatsoever. In that case, your problem statement could start off as: Which factors influence office staff motivation levels? This situation is complicated by the fact that these factors may number in the hundreds. Your best bet would be to start with some preliminary research. You begin by studying relevant literature and conducting some interviews aimed at uncovering potential factors. Next, your main research investigates the influence of a limited number of factors, the factors you expect to be the most likely culprits considering the circumstances. Obviously, you do run the risk of researching the wrong factors or overlooking others. But you should limit that risk by being thorough in your work. Solid preliminary research will reduce the chances of your main research failing. * Determine the research population. These are the people, objects, or items you wish to gain knowledge about, for example the sales team or members of the accounting department.

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* Draft a model. You visualise the variables and their relationships. Relationships are indicated using arrows. Figure 11.1 is a model of a problem statement, namely: To what extent does the motivation of employees in the accounting department influence productivity?

Model of a knowledge problem concerning the relationship between motivation and productivity

FIGURE 11.1

Level of Motivation

Level of Productivity

* Choose a theoretical perspective. You indicate from which philosophy found in scientific literature you intend to operate. Where motivation is concerned, you will find that you will soon arrive at Maslov’s hierarchy of needs. But Maslov has not been the only one to consider this topic. For example, motivation can also be regarded from the perspectives of Festinger’s theory of social comparison, or Herzberg’s two factor theory. Whatever theory you choose; you define your variables based on scientific literature. Alternatively, you can opt for a so-called disciplinary perspective. For example, you only evaluate the financial consequences of a certain decision, and do not consider its social repercussions. In any case, you should note that the variables used in your problem statement fit the perspective used.

Problem Statement Pointers and Pitfalls * For research purposes, a close-ended question does not make for a convenient problem statement. The answer to the question ‘Are the employees motivated’ is simply either ‘Yes’ or ‘No’. A better question would be: ‘What is the level of motivation of the employees?’ * Are you after facts or opinions? For example, do you want to know how advisors feel about a certain topic, or do you want to know the facts behind it? You could ask the advisors for the factual information... but are they sure to be right, or objective? For example, the answer to question ‘What reasons do investment advisors give for the rapid development of countries like Brazil, Russia, India, or China?’ does not yield a value-free answer. It would be better to ask: ‘What are the reasons for the rapid development of countries like Brazil, Russia, India, or China?’ You can consult investment advisors on both questions – their answers could very well be different. Similarly, scientific literature is home to a fair share of differing or even conflicting facts and opinions. Your job is to compile them into your own conclusions. * Make sure your question does not contain a norm. That would mean you would be looking at an action problem, instead of a knowledge problem in need of research. An example of a norm used in a problem statement is: What should the company do to improve their German revenue? ‘Improve’ means the problem owner perceives a difference between the

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actual revenue and the desired revenue. In other words, they perceive a discrepancy between the norm and the reality – an action problem. The word ‘should’ also implies that there is a norm. Note that research never tells you what you should do; at most, it tells you what you could do. * The problem statement should not be almost the same as the research goal. The problem statement explains what you intend to research. The research goal explains why you intend to conduct research. Say your problem statement is: What is the relationship between motivation and productivity? You research goal in that case should not be: Gaining an insight into the relationship between motivation and productivity. Rather, it should be: Verifying the supposed cause (here: motivation). This is knowledge you will need in order to implement the appropriate measures. * Make sure you do not overgeneralise the problem statement. That will not help you find specific enough conclusions for solving your knowledge problem and thereby your action problem. Solving a more contained knowledge problem is often more effective. An example of an overgeneralised problem statement is: Which activities within the production process are not proceeding according the established procedures? A problem statement like that risks a flood of generalised information, without going into the necessary details. In this case, it would be better to examine part of the production process, thereby generating more specific information which you can use for improvements. * Limit the number of variables in your problem. The large the number of variables you investigate, the larger your problem becomes. Analysing vast numbers of variables and their relationships soon becomes a timeconsuming matter. A thorough investigation into a more accessible number of variables is much preferred.

§ 11.4

Formulating the Research Questions Next, you start formulating your research questions. These are questions used to split up a problem statement, thereby making it more accessible. Research questions are also convenient for a proper division of labour; you can assign aspect of your research to different researchers based on the different questions.

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It is important that the research questions are somehow systematic. Problem statements lend themselves to many hundreds of questions, but the ones you actually ask should be relevant. And you should, of course, make sure there is nothing you have overlooked. Two things made easier by using a systematic approach in order to concretise your problem statement. When coming up with research questions, use your systematic approach in tandem with a creative one. First, come up with as many questions as possible. Next, cluster the questions according to their theme(s). Order the clusters into a structured whole; a system or logic. This will help you pick out any bottlenecks. For example, not all themes may fit your system, for example leading to answers indicating both personnel and financial problems. This may mean that certain questions are irrelevant to solving your knowledge problem, or that you should reassess your logic. And your

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side-step into systematic logic can also inspire new ideas. If you find indications of both personnel issues and financial issues, you could consider that these are both managerial functions. So: ‘What about other similar functions, such as commerce, R&D, and production?’ You can keep refining this method, until you arrive at an appropriate and complete set of research questions. This way, you will prevent omitting any important topics or asking the questions twice. You can test the quality of your research questions by applying the following questions: * Do the research questions contain all the variables of the problem statement? * Do the research questions have any new variables not found in the problem statement? If so, you will need to adjust either the problem statement or the research questions. * Do any of the research questions overlap? Remove any (partial) unwanted duplicates. * Has the number of variables and relations per research questions been kept to a minimum? Aim for two variables per research question.

§ 11.5

Formulating the Research Design You have established the topic of your research. You have formulated your research goal, your problem statement, and your research questions. You know what you are going to look into. Next, you need to establish how your research is to be conducted. That starts with strategy. You formulate how you intend to reach your goal. Making choices, that is the thing now. Here are several choices to consider: * Do you want to influence your variables? A lot of research requires that you measure only, and do not influence any factors yourself. Say, for example, that you want to measure iPad owner satisfaction with the device’s user-friendliness. You can interview iPad users about their experiences. Alternatively, you can have a group of subjects complete certain tasks and then ask them about their feelings regarding userfriendliness afterwards. The latter is a type of experiment, an assignment, which influences them. The assignment which uses the iPads here is called a ‘stimulus’. You can also give subjects a set of different iPad assignments of increasing levels of difficulty. This way, you can measure whether their opinion of user-friendliness is influenced by the degree of difficulty of the assignment. You can even vary the external conditions of the test, for example between fully closing to fully opening the blinds – text on an iPad is sometimes difficult to read in direct sunlight. The measurements you can get from an experiment are accurate, but experiments are often expensive and demand secure preparations. You need to prevent your measurements being influenced by forces outside your control. * Do you wish to be in direct contact with your research population? Desk research or literature studies do not put you in touch with your research population. A questionnaire or observational study will bring you closer to the group you are investigating. Literature studies are relatively cheap, and convenient if no research population is available – something that can occur if, for example, you want to research events or situations in the distant past. Contact with a research population will often yield information not available from any literature, such as personal opinions of office

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Cross-sectional Longitudinal

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employees. On top of that is the fact that your own research can let you measure exactly what you are interested in, while other people’s research is more confined to their interests. One disadvantage is that research involving contact with a research population is often quite expensive – and not all participants are necessarily looking forward to cooperating. * Do you conduct your research under laboratory conditions? The option to perform research under controlled circumstances is a potential asset. It is also, however, a more expensive way of researching. In addition, you will have to very carefully determine the circumstances or setting. Do you intend to go for broad or for in-depth research? If you want to know to what extent Joe or Jane Public is in favour of a military mission to Africa or Asia, then that is considered broad research – and a questionnaire is an instrument well-suited to the task. But if you want more insight into organisational changes within a company, you could opt for a case study of several months’ worth of internal investigations. That type of research is known as in-depth. * Do you choose cross-sectional or longitudinal research? Cross-sectional research is where all measurements are conducted virtually simultaneously. Think of a one-time questionnaire on employees’ opinions of the new travel expenses remuneration arrangement. But, on the other hand, if you approach the same group or address the same topic at different points over a (longer) period of time, this is known as longitudinal research. Longitudinal research is the type used if you want to know, for example, how the employees’ opinions of the remuneration arrangement have changed over time. You might submit your questionnaire immediately following the arrangement’s introduction, followed by additional measurements (using the same or a similar questionnaire) three months and/or six months later. This longitudinal research may show that employees were initially dissatisfied but, in time, have begun to see the advantages of the new arrangement. ‘To Do’-List The answers to the previous questions constitute your research strategy. The details of your research design are completed by establishing the points on the following ‘to do’-list: * Research Population. This may require a more specific description of the individual(s), group(s), or organisation(s) you wish to use as the subject of your research than you had given in your problem statement. This is especially true for explanatory research. If, for example, you are researching the relationship between the innovative capabilities of small-to-medium-sized chemical companies and their success rate, your research population should not be limited to successful companies only. You are not only measuring how innovative very successful companies are; you also want to know how innovative less successful companies are. Only then can you make some claim as to whether successful companies are more innovative than less successful ones. * Subjects. This concerns the units or group you are actually going to measure. Say that your unit is car mechanics. The units need not necessarily be parallel to the research population; in this case, the research concerns car dealerships. These dealerships are companies; abstract concepts which you cannot interview for an opinion. For that reason, you choose a different subject - here, car mechanics.

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* Sample. You will need to decide on conducting a sampling and, if so, establish how your sampling is to be executed. You could choose a random sample, where all elements of the group from which you draw your subjects stand an equal chance of taking part; or a representative sample, where, for example, the ratio of men to women matches the reality. Alternative, you can opt out of sampling, but choose an extreme case, examining the most unusual aspects since those are the ones you stand to learn the most from. * Data Gathering. There are various and varied ways of gathering data, with examples including but not limited to: observations, interviews, questionnaires, or analyses of primary sources. * Processing and Analysing. How do you handle your data? Do you emphasise the quantitative or the qualitative? Obtaining some telling quantitative data is nearly always possible; it is highly insightful to conduct open interviews to ascertain how employees feel about a company’s reward system. But that sort of information dramatically gains in conviction if you can demonstrate that dissatisfied employees number in the order of 70%. The danger of restricting your research to the qualitative is that the conclusions you reach tend to be overly generalised, or even ambiguous. Some numerical data used in a supporting role is a good way of deciding, for example, which of a number of possible qualitative explanations are the most likely candidates. But there are some downsides to quantitative research as well. Numbers can offer a false sense of security. An average of 5-year tenures of 78% of employees seems a good thing. Low employee turnover figures mean low training or recruitment costs. But it is entirely possible that many people opt to stay not out of loyalty, but because they simply have no one else that will hire them. The question is: Are those the people you would want working for you? Another potential hitch occurring in quantitative research is that measuring variables takes substantial preparation. If you are interested in someone’s opinion, a few general questions made more explicit during an interview, a form of qualitative research, can be sufficient. If you are interested in expressing, for example, an employee’s opinion on a reward scheme in terms of a score out of 10, you will have to carefully consider what you are going to ask. But is this required planning time a disadvantage? You should note that thoroughly preparing your questions has a way of saving time later on. A massive pile of numerical data is more easily to analyse than a massive pile of quantitative data, no matter how clear and interesting your questions seemed during the interviews. In hindsight, the notes you made and the conversations you recorded may turn out to contradict each other, or even be unrelated to the matter you were trying to touch upon in your problem statement. * Report Structure. You come up with a layout and preliminary table of contents for your research report in advance. * Activity Schedule. You draft a planning for all the steps you aim to take during your research, to which you can refer back along the way.

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Performing the Operationalisation Now that you know what it is you want to research and how you are going to go about it, it is time to make your variables quantifiable. Abstract variables, such as status, motivation, or assertiveness, cannot be measured. You

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need to operationalise them using indicators. This process is the same as for variables found in action problems (see paragraph 4.5: Making Problems Quantifiable). If you wanted to measure the status levels of managers, you could look at the authority they are attributed, or the size of their office, for example. The larger the office, the higher the status level. Note that you will need to be able to provide evidence of the relationship between the indicator and the variable, either using existing or original research. Indicators are used to highlight a number of aspects of your variables. The combination of aspects does not necessarily have to encompass the variable exactly. This method of using indicators is known as concretising. Alternatively, you may need to split up your variables into separate components. The indicators of profit, for example, are turnover and costs. When settled against each other, these variable do exactly amount to your variable. This method of splitting up variables is known as decomposing.

Operationalisation

§ 11.7

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Concretising or decomposing/splitting variables are logical approaches to operationalisation. It will help readers of your research report understand your methods. Because you have specifically indicated what it is you intend to measure, you will be able to handle existing theories in a better, more focussed manner. Proper operationalisation also ensures your research will yield the data you expect it to. In the example of manager status saw the use of the maxim ‘The bigger the office, the higher the status’. Here, office size is an indicator of status. The same rule will not apply to a manager who has been kicked upstairs, and has received a larger office by way of compensation. You have to make sure the indicators you use are tailored to the circumstances of your investigation; are you looking at successful managers, or managers who have been kicked upstairs?

Performing the Measurements You research report is not limited to the results of your measurements – it should also indicate any factors potentially influencing their validity and reliability. For example, you should mention the level of cooperation your interviews received. Is it possible to draw conclusions if an important part of the research population refused to cooperate? You should also mention any possible errors in the measuring method. It is possible that a lot of the people you interviewed did not understand some (or any) of the questions they were asked. What did you do to correct that oversight? Are your actions potentially of influence on the results? The scientific quality of all research is measured by its reliability and its validity. In the example of a watch, for example, you will see the connection between the two concepts. If you have a watch that is always ten minutes fast, then you have a reliable watch. However, its time measurement is not valid - it does not indicate the correct time, but rather what time it will be ten minutes from now. If, on the other hand, you have a watch that wavers between being fast and being slow, then your watch is unreliable in its timekeeping. It may occasionally hit on the correct time as it moves from fast to slow; even a watch that does not run at all will indicate the correct time twice every 24 hours. But the points at which these faulty watches do

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so are accidental – and they are unknown if you do not have a reliable watch to verify them with. If a watch is unreliable, then its time measurement cannot be considered valid. Reliability is concerned with the stability of the research results; similar research conducted at a later date using the same method ought to yield the same results. Validity is concerned with the contents. Have you measured what you intended to measure? Does the questionnaire yield the correct data? There are many potential threats that can compromise the validity of your research. These are three examples: 1 Internal Validity. This is concerned with whether the research design and your measuring instruments have been properly formulated and constructed. One potential threat is that of self-selection. If you want to replace company PCs with iPads, and you ask for several volunteers to try them out, there is every chance that you will end up with a group of digital device enthusiast; people whose approach to a company iPad would be radically different from that of the average employee. The information you gain from this experiment, therefore, is probably of very little use. 2 External Validity. To what extent can you apply your research to other groups than your research population? Here, the main threat is that of unjustifiable generalisations. Measures that effectively address vandalism in a small town environment are not necessarily very useful when applied in a major city. 3 Construct Validity. This type of validity is concerned with abstract concepts. You establish whether they have been properly operationalised, logically related and, where possible, based on available scientific knowledge. A potential threat is that of an insufficiently specific definition of the concepts used in the problem statement. This is something that happens if, for example, the problem statement is concerned with employee motivation without specifying what ‘motivation’ entails. Is it only concerned with employees performing their tasks, or also with working for the company with a measure of satisfaction? Using a problem statement that clearly specifies how ‘motivation’ is defined means limiting the risk of using indicators for both types of motivation.

§ 11.8

Validity

Processing the Data Your research design will generally not allow for a detailed schedule or plan for the analysis of your data. That is not a problem, because you will often come to new insights during the measuring phase – and that would mean having to revisit and change a previously established analysis plan. Nevertheless, your research design does need some comments regarding data processing, if only for you to help guide yourself along the right lines and help you keep an eye on your route along the way. Whatever you do, try to make sure your method of analysis is a simple one. Complicated statistical models are only useful if the quality of the information available is exceedingly high. Generally speaking, though, it is not. A simple cross table tends to suffice quite well. During this phase, you should also remember to spend some time on an evaluation of the validity and reliability of the measurement results. Have enough people taken part in your questionnaire for you to be able to draw

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any conclusions? Have any of the interviewees misinterpreted some of the questions, leading to inconsistent answers? Should you really have been measuring some additional variables as well? Since hindsight is 20/20, you will often find points you could have changed or improved. That is generally not a problem; no research is perfect, and there are almost always enough interesting results left to work with. Be that as it may, though, you have to be honest about any mishaps in your research report. And ‘retconning’ (see paragraph 11.1) will often get you a long way.

§ 11.9

Drawing Conclusions (Reviewing the Problem Statement) You have arrived at the final step in your investigation. It is time to draw your conclusions, to see what exactly your research has yielded. Can you give a full answer to your problem statement? Or can you only draw conclusions for certain aspects or situations? Truthfully consider to what extent you have been able to answer the problem statement. New insights or missing data may force you to conclude that there are some questions still open. That is not a problem, as long as you can be honest about it. If you find, for example, that you cannot make any claims about the entire company, but only about a single branch, then say so – and do not make recommendations for the entire company anyway. You may even have to adjust your problem statement – keep in mind the potentially useful concept of ‘retconning’. Remember that any result is a result. If you wanted to establish whether the old machinery is the cause of the poor quality of goods produced, and it turns out that it is not, then that does not mean your research has failed. At most, you will have to restart the search and come up with alternative causes of the poor quality. And the knowledge that the machines are not the culprit is still valuable. It is not an obvious fact, or you would not have been pursuing it as a cause anyway.

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You check whether you have met the prerequisites of your research. To do so, you can use these questions. Can you answer both with ‘Yes’? 1 Are the facts (i.e. the results) separate from your personal interpretation (i.e. your conclusions/opinions)? 2 Is there an explicit link between the solution to the knowledge problem (i.e. your research) and the actions you will need to perform to solve the action problem? If the answer to either question is ‘No’, then you will need to conduct additional research. If it is a resounding ‘Yes’ all round, then you can use your newfound knowledge to continue dealing with your action problem.

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Summary

▶ You will require knowledge at various points during your problem-solving approach. Knowledge may require research. The research cycle is a way of conducting research step by step. ▶ Begin by formulating your research goal. State the reason for wanting to solve the knowledge problem. ▶ Formulate a problem statement. Phrase it in the form of a question. Consider the type of research involved: descriptive or explanatory. Define your variables and indicate the relationships to be researched. Establish your research population. Draft a model. Use a theoretical perspective if necessary. Keep the following tips in mind: * Do not phrase your problem statement as a close-ended question. * Draw your own conclusions from potentially biased and conflicting available information * Make sure your problem statement is not identical to your research goal * Do not overgeneralise your problem statement * Limit the number of variables to keep your research orderly and accessible. ▶ Formulate your research questions systematically. ▶ Formulate your research design, the intended strategy of your research. Answer the following questions: * Do you want to give your subjects stimulus? * Do you want or need to be in contact with your research population? * Do you conduct your research in laboratory conditions? * Do you want your research to be broad or in-depth? * Do you want to conduct cross-sectional or longitudinal research?

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▶ Operationalise your variables (resulting in indicators). You can choose to concretise: use indicators to highlight several aspects of your variable which need not necessarily amount to the variable exactly. Or you can choose to decompose: split up your variables into separate components which, when combined, add up to your variable exactly. ▶ Perform your measurements.

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▶ Indicate how you processed the data. Clarify how you gathered your data. Choose as uncomplicated a method of analysis as possible. Indicate any potential influences on their validity and reliability. ▶ End by drawing conclusions and revisiting the problem statement. Consider whether you can fully answer the problem statement. If so, use your newfound knowledge to solve your action problem. If your conclusions can only apply to certain aspects or situations, you will need to conduct additional research.

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Core Concepts

Cross-Sectional Research

A method of research which involves performing all measurements virtually simultaneously.

Longitudinal Research

A method of research which involves performing measurements at different points in time. These measurements are then compared for differences.

Operationalisation

Using indicators to make variables quantifiable.

Validity

Refers to the quality of research results. Are you measuring what you had intended to measure? There are several types of validity, such as internal validity (concerned with properly formulating and constructing research designs and measuring instruments), external validity (concerned with the extent to which the research can be applied to groups other than the research population), and construct validity (concerned with whether abstract concepts are properly operationalised, logically coherent and, where possible, based on available scientific knowledge).

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Sources

Books: Van Aken, J.E., Berends, H. & Van der Bij, H. (2007), Problem solving in organizations, A methodological handbook for business students, Cambridge: Cambridge University Press. (chapters 1-8) Athos, A.G. & Pascale, R.T. (1982), The art of Japanese management, Harmondsworth: Penguin Baarda, D.B. & de Goede, M.P.M. (2006), Basisboek methoden en technieken, Groningen: Stenfert Kroese. Babbie, E. (2010), The practice of social research, 12th edition, Belmont: Wadsworth Bos J., Harting E. e.a. (2006), Projectmatig creëren 2.0, herziene editie, Schiedam: Scriptum Cooper, D.R. & Schindler, P.S. (2008), Business research methods, 10th revised edition, New York: McGraw-Hill/Irwin Ishikawa, K. (1985), What is Total Quality Control? The Japanese Way, New Jersey: Prentice Hall. Grit, R. (2015), Projectmanagement, 7e druk, Groningen/Houten: Noordhoff Uitgevers Goodwin, P. & Wright, G. (2009), Decision analysis for management judgment, 4th edition, Chichester: John Wiley & Sons Ltd Heerkens, H. (2004), Methodologische checklist, Enschede: TSM Business School Hicks, M.J. (2004), Problem solving and decision making; hard, soft and creative approaches, 2nd edition, London: Thomson Learning. Koning, A. & Van Onna, M. (2010), De kleine Prince 2, Gids voor projectmanagement, 6e druk, Den Haag: SDU Academic Service Kor, R., Wijnen, G. & Weggeman, M. (2007), Meesterlijk Organiseren, Deventer: Kluwer Leeuw, A.C.J. de (2000), Organisaties; analyse, ontwerp en verandering; een systeemvisie, 4e druk, Assen: Van Gorcum Patton, M.Q. (2008). Utilization-focused evaluation, 4th edition, Thousand Oaks: Sage Publications Inc. Peters, T.J. & Waterman Jr., R.H. (1982), In search of excellence: lessons from America’s best run companies, New York: Warner Books Edition Riemsdijk, M.J. van (redactie) (1999), Dilemma’s in de bedrijfskundige wetenschap, Assen: Van Gorcum Rozenburg, N.F.M, & Eekels, J. (1998), Productontwerp; structuur en methoden, 2e editie, Utrecht: Lemma Stapleton, J. (2005), DSDM, de methode in praktijk, 2e editie, Amsterdam: Pearson Education Benelux Wijnen, G. & Storm, P. (2007), Projectmatig werken, 24e druk, Utrecht: Spectrum Internet: Quotes via quotes.net. Taken from http://www.quotes.net/quotations/problems on July 11th, 2016

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Illustration Acknowledgements

Shutterstock, New York: p. 8, 18, 28, 38, 52, 60, 72, 90, 100, 108, 116

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Index

A Action problem 21 Attributes 77 B BCH model 103 Bottom-up 104 C Causality 67 Change management 104 Concretising variables 47 Conjunction criteria 77 Consensus 76 Cross-sectional 124 Cut-off criteria 77 D D3: Do, Discover, and Decide 55 Decomposing variables 47 Discrepancy 22 F Formative evaluation 112 I Implementation plan 103 K Killer requirements 77 Knowledge problem 23 L Language of variables 14 Lexicographical method 81 Longitudinal 124 M Majority rule 81 Managerial Problem-Solving Method (MPSM) 11 Measurement levels 64

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Morphology 86 MoSCoW rules 82 N Non-compensatory 77 O Operationalisation 126 P Probability theory 95 Problem analysis 63 Problem cluster 42 Problem context 41 Problem identification 42 Problem owner 22 Q Qualified majority 76 Quick and dirty 41 R Research cycle 55 Research population 23 S Scenarios 95 Sequential order 67 Statistical relationship 67 Sub-attributes 78 Summative evaluaton 112 Synectics 85 T Threshold value 95 Top-down 104 V Validity 127 Y Yammer 104

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About the Authors

Hans Heerkens (1958) teaches the methodology of problem-solving, researching, and decision-making as part of various courses at the University of Twente and several business schools. His research and advisory work are concerned with the managerial aspects of aviation, in particular the development of unmanned cargo aircraft and strategical decision-making processes in the aviation and defence industries. He holds a PhD in decision theory.

Arnold van Winden (1957) teaches Communications at the Amsterdam University of Applied Sciences. He is thoroughly familiar with communications and project management, and the subjects he teaches include communications during change processes and dealing with the media. For many years, Van Winden worked in various communications-related functions. He studied journalism and obtained an MBA at Business School Netherlands.

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