The Oxford Handbook of Megaproject Management 9780198732242, 0198732244

Table of contents :
Cover
The Oxford Handbook of Megaproject Management
Copyright
Contents
List of Illustrations
List of Tables
List of Contributors
1. Introduction: The Iron Law of Megaproject Management
Part I Challenges
2. Has Megaproject Management Lost Its Way? Lessons from History
3. Cycles in Megaproject Development
4. Big Is Fragile: An Attempt at Theorizing Scale
5. Institutional Challenges and Solutions for Global Megaprojects
6. Megaproject Decision Making and Management: Ethical and Political Issues
7. Biggest Infrastructure Bubble Ever? City and Nation Building with Debt-​Financed Megaprojects in China
Part II Causes
8. Did Megaproject Research Pioneer Behavioral Economics? The Case of Albert O. Hirschman
9. Megaproject Escalation of Commitment: An Update and Appraisal
10. Megaprojects as Games of Innovation
11. Power and Sensemaking in Megaprojects
12. A Collective-​Action Perspective on the Planning of Megaprojects
13. Understanding Drivers of Megaevents in Emerging Economies
Part III Cures
14. Innovation and Flexibility in Megaprojects: A New Delivery Model
15. Megaproject Stakeholder Management
16. Private Finance: What Problems Does It Solve, and How Well?
17. Wider Impacts of Megaprojects: Curse or Cure?
18. Quality Assurance in Megaproject Management: The Norwegian Way
19. The Good Megadam: Does It Exist, All Things Considered?
Part IV Cases
20. Cracking the Code of Megaproject Innovation: The Case of Boeing’s 787
21. The Power of Systems Integration: Lessons from London 2012
22. Iconic Urban Megaprojects in a Global Context: Revisiting Bilbao
23. Private Provision of Public Services: The Case of Australia’s Motorways
24. Megaprojects as Political Symbols: South Africa’s Gautrain
25. Large Dam Development: From Trojan Horse to Pandora’s Box
Index

Citation preview

 

T h e Ox f o r d H a n d b o o k o f

M E G A P ROJ E C T M A NAG E M E N T

 

 

The Oxford Handbook of

MEGAPROJECT MANAGEMENT Edited by

BENT FLYVBJERG

1

 

3 Great Clarendon Street, Oxford, ox2 6dp, United Kingdom Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and in certain other countries © Oxford University Press 2017 The moral rights of the author‌have been asserted First Edition published in 2017 Impression: 2 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by licence or under terms agreed with the appropriate reprographics rights organization. Enquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above You must not circulate this work in any other form and you must impose this same condition on any acquirer Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America British Library Cataloguing in Publication Data Data available Library of Congress Control Number: 2017933991 ISBN 978–​0–​19–​873224–​2 Printed and bound by CPI Group (UK) Ltd, Croydon, cr0 4yy Links to third party websites are provided by Oxford in good faith and for information only. Oxford disclaims any responsibility for the materials contained in any third party website referenced in this work.

 

Contents

List of Illustrations  List of Tables  List of Contributors 

ix xi xiii

1. Introduction: The Iron Law of Megaproject Management  Bent Flyvbjerg

1

PA RT I   C HA L L E N G E S 2. Has Megaproject Management Lost Its Way? Lessons from History  Sylvain Lenfle and Christoph Loch

21

3. Cycles in Megaproject Development  Matti Siemiatycki

39

4. Big Is Fragile: An Attempt at Theorizing Scale  Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn

60

5. Institutional Challenges and Solutions for Global Megaprojects  Raymond E. Levitt and W. Richard Scott

96

6. Megaproject Decision Making and Management: Ethical and Political Issues  Bert van Wee and Hugo Priemus

118

7. Biggest Infrastructure Bubble Ever? City and Nation Building with Debt-​Financed Megaprojects in China  Xuefei Ren

137

PA RT I I   C AU SE S 8. Did Megaproject Research Pioneer Behavioral Economics? The Case of Albert O. Hirschman  Bent Flyvbjerg

155

 

vi   Contents

9. Megaproject Escalation of Commitment: An Update and Appraisal  Helga Drummond

194

10. Megaprojects as Games of Innovation  Roger Miller, Donald Lessard, and Vivek Sakhrani

217

11. Power and Sensemaking in Megaprojects  Stewart R. Clegg, Shankar Sankaran, Chris Biesenthal, and Julien Pollack

238

12. A Collective-​Action Perspective on the Planning of Megaprojects  Nuno Gil

259

13. Understanding Drivers of Megaevents in Emerging Economies Robert A. Baade and Victor A. Matheson

287

PA RT I I I   C U R E S 14. Innovation and Flexibility in Megaprojects: A New Delivery Model  Andrew Davies, Mark Dodgson, and David M. Gann

313

15. Megaproject Stakeholder Management  Graham Winch

339

16. Private Finance: What Problems Does It Solve, and How Well?  Graeme Hodge and Carsten Greve

362

17. Wider Impacts of Megaprojects: Curse or Cure?  Roger Vickerman

389

18. Quality Assurance in Megaproject Management: The Norwegian Way  Gro Holst Volden and Knut Samset 19. The Good Megadam: Does It Exist, All Things Considered?  Thayer Scudder

406 428

PA RT I V   C A SE S 20. Cracking the Code of Megaproject Innovation: The Case of Boeing’s 787  Vered Holzmann, Aaron Shenhar, Yao Zhao, and Benjamin Melamed

453

 

Contents   vii

21. The Power of Systems Integration: Lessons from London 2012  Andrew Davies

475

22. Iconic Urban Megaprojects in a Global Context: Revisiting Bilbao  Gerardo del Cerro Santamaría

497

23. Private Provision of Public Services: The Case of Australia’s Motorways  Demi Chung

519

24. Megaprojects as Political Symbols: South Africa’s Gautrain  Janis van der Westhuizen

539

25. Large Dam Development: From Trojan Horse to Pandora’s Box  Rhodante Ahlers, Margreet Zwarteveen, and Karen Bakker

556

Index 

577

 

 

List of Illustrations

1.1 Size of selected megaprojects, measured against GDP of selected countries 

3

2.1 When to choose trial-​and-​error-​learning or selectionism 

31

3.1 S-​curve of innovation adoption 

41

3.2 Number and type of Major League baseball stadiums constructed, 1860–​2010 

44

3.3 Global development of super-​tall skyscrapers 

46

3.4 Boom and bust: opening of new nuclear reactors worldwide 

50

4.1 A map of fragility 

65

4.2 Graphing “investment fragility” 

68

4.3 Sample distribution of 245 large dams across five continents (1934–​2007) 

72

4.4 Density trace of actual/​estimated cost (costs overruns) in constant local currency terms 

73

4.5 Density trace of schedule slippage with the median and mean 

74

4.6 Location of large dams in the sample and cost overruns by geography 

79

4.7 An aspiration to investment robustness in the Guavio hydroelectric project  81 4.8 Cumulative fragility: erosion near the foundation of Kariba Dam wall 

83

4.9 Inaccuracy of cost estimates (local currencies and constant prices) for large dams over time (1934–​2007) 

84

5.1 Involvement level of key actors in SR91X at critical events over the course of development 

109

8.1 Box plots of cost risk and benefit risk 1920–​2011 

179

10.1 Project shaping 

222

10.2 Shaping as a sequence of options 

227

10.3 An megaproject value tradespace with many possible design options 

228

12.1 Stylized representation of different infrastructure design structures 

266

12.2 Excerpts of the design structure matrices and companion organizational matrices for the London Olympic Park and HS2 cases 

268

12.3 Sustaining highly fragile consensus-​oriented developments 

273

14.1 Balancing routines and innovation in megaprojects 

322

 

x   List of Illustrations 14.2 Balanced response to uncertainty 

322

16.1 The European PPP market by value and number of projects since 2005 

366

18.1 The Norwegian quality-​at-​entry regime for major public investment projects  408 18.2 Stochastic cost estimation: definition of key terms 

417

18.3 Deviation between the final cost and the cost frame approved by Parliament  418 18.4 Number of projects with cost overruns and savings by sector 

419

18.5 Deviations between the final cost and the approved cost frame at the time of commissioning for the project 

420

18.6 Deviation between the final cost and the agreed steering frame for the project  421 20.1 The Diamond of Innovation model 

461

20.2 The Dreamliner’s Diamond of Innovation 

464

21.1 London 2012 Olympics: Program, projects, and systems

484

25.1 Construction of dams by decade during the twentieth century 

562

25.2 Change in monthly downstream flows owing to Aswan High Dam

564

25.3 Financial flows in dam building 

566

 

List of Tables

1.1 The “four sublimes” that drive megaproject development 

6

1.2 Large-​scale projects have a calamitous history of cost overrun 

11

3.1 Selected waves of innovation in urban development, 1890–​2007 

42

4.1 Total stock of public net external debt (US$ current, MM) 

80

6.1 Scores on statements related to the relationship between the researcher and client 

123

6.2 Seven North–​South Metro Line contracts 

130

6.3 HSL-​South: contracts awarded for civil engineering substructure 

131

6.4 Categorization of incentives to improve the neutrality/​independence of research  134 8.1 Are higher-​than-​estimated costs outweighed by even higher-​than-​ estimated benefits? 

175

10.1 Major issues around which megaprojects are shaped 

222

10.2 Illustrative devices to shape and sculpt projects 

223

10.3 Episodes in the shaping of projects 

226

12.1 High-​level description of the sample of cases, interviewees, and archival database  264 12.2 Excerpt of tabular display analysing 

269

13.1 Host cities for the World Cup since 1930 

289

13.2 Expected and actual outcomes for selected variables for megaevent hosting by South Africa, India, and Brazil

296

14.1 Dynamic capabilities in megaprojects 

319

16.1 Three phases of arguments for using private finance in public projects 

367

16.2 Selected PPP evaluations, 1998–​2014 

373

17.1 Benefits from Crossrail 

395

17.2 The economic case for HS2 

396

17.3 Impacts of connectivity on GDP from HS2 

397

20.1 Boeing 787 build-​to-​performance model 

456

20.2 787 Dreamliner sequence of main events 

457

 

xii   List of Tables 20.3 Diamond of Innovation model: definitions, dimensions, and project types  462 20.4 Comparison of the Dreamliner’s actual events to a proposed alternative plan 

467

21.1 Levels of complexity in megaprojects 

477

21.2 Major systems within the Olympics Park 

481

21.3 Systems integration on the London Olympics 2012 

483

23.1 DBFO motorways in New South Wales and Victoria 

531

23.2 Changes to the toll compared with the original project concept 

535

 

List of Contributors

Rhodante Ahlers  is an Independent Researcher Atif Ansar  is Lecturer at the Blavatnik School of Government, University of Oxford Robert A. Baade  is the A. B. Dick Professor of Economics and Business at Lake Forest College in Lake Forest, Illinois Karen Bakker  is a Professor, Canada Research Chair, and Founding Director of the Program on Water Governance at the University of British Columbia Chris Biesenthal  is a Senior Lecturer at the School of the Built Environment at the University of Technology, Sydney Alexander Budzier  is a Business Development Manager at the Saïd Business School, University of Oxford Demi Chung is a Senior Lecturer and Undergraduate Studies Coordinator at the University of New South Wales Stewart R. Clegg is a Professor in the University of Technology Sydney Business School. He is also a Strategic Research Adviser, Newcastle University Business School, UK, and a Visiting Professor, School of Business and Economics, Universidade Nova, Lisbon, Portugal Andrew Davies  is Professor in the Management of Projects, The Bartlett Faculty of the Built Environment, University College London Gerardo del Cerro Santamaría  is Research Professor of Planning and Megaprojects at The Cooper Union for the Advancement of Science and Art in Manhattan Mark Dodgson  is Director of the Technology and Innovation Management Centre at the University of Queensland Business School Helga Drummond is a Professor of Decision Sciences in University of Liverpool Management School and Visiting Professor of Business, Gresham College London Bent Flyvbjerg is the BT Professor and inaugural Chair of Major Programme Management at the University of Oxford David M. Gann is the Vice-​ President (Development and Innovation), Imperial College London

 

xiv   List of Contributors Nuno Gil is Academic Director at the Centre for Infrastructure Development, Manchester Business School Carsten Greve is Professor of Public Management and Governance, Copenhagen Business School Graeme Hodge  is a professor of Public Policy in the Law Faculty at Monash University Vered Holzmann  Coller School of Management, Tel Aviv University Sylvain Lenfle  a professor of Innovation Management at the Conservatoire National des Arts et Métiers (CNAM) in Paris and associate researcher at the Centre de Recherche en Gestion (CRG), Ecole Polytechnique, France Donald Lessard is the Epoch Foundation Professor of International Management, Emeritus at the MIT Sloan School of Management Raymond E. Levitt  is Professor of Civil and Environmental Engineering and Director of the Center for Global Projects (CGP) at Stanford University Christoph Loch  is a Professor and the Director of Cambridge Judge Business School at the University of Cambridge Daniel Lunn is an Emeritus Fellow in the Department of Statistics, University of Oxford Victor A. Matheson  is Professor of Economics at the College of the Holy Cross Benjamin Melamed  is Distinguished Professor at Rutgers Business School Roger Miller  École EMD, Aix-​Marseille Julien Pollack  is the Senior Lecturer at the School of the Built Environment, University of Technology Hugo Priemus  is Professor Emeritus System Innovation and Spatial Development, Delft University of Technology Xuefei Ren  is an Associate Professor of Sociology and Global Urban Studies, Michigan State University Vivek Sakhrani  is a PhD candidate and researcher at the Massachusetts Institute of Technology, and CPCS Transcom Inc Knut Samset  is Professor of Project Management at the Faculty of Engineering Science and Technology, Norwegian University of Science and Technology Shankar Sankaran  is Professor of Organizational Project Management at the School of the Built Environment, University of Technology Sydney W. Richard Scott  is Emeritus Professor of Sociology at Stanford University

 

List of Contributors    xv Thayer Scudder is Emeritus Professor of Anthropology, California Institute of Technology Aaron Shenhar  is Professor of Project and Technology Management, CEO, The SPL Group and TLI Matti Siemiatycki is an associate professor of Geography and Planning at the University of Toronto Janis van der Westhuizen  is an Associate Professor, Stellenbosch University Bert van Wee  is Professor in Transport Policy at Delft University of Technology Roger Vickerman  is the Dean for Europe and Professor of European Economics at the University of Kent Gro Holst Volden is a Research Director for the Concept Research Program, Norwegian University of Science and Technology Graham Winch  is Professor of Project Management, Manchester Business School, University of Manchester Yao Zhao  is Professor and Department Vice Chair, Rutgers Business School, Rutgers University Margreet Zwarteveen  is Professor of Water Governance, UNESCO-​IHE

 

 

Chapter 1

Introdu c t i on The Iron Law of Megaproject Management Bent Flyvbjerg

1.1  Classics in Megaproject Management The ambition for this inaugural edition of The Oxford Handbook of Megaproject Management is to become the ultimate source for state-​of-​the-​art scholarship in the emerging field of megaproject management. The book offers a rigorous, research-​oriented, up-​to-​date academic view of the discipline based on high-​quality data and strong theory. Until lately, the literature in this new field was scattered over a large number of publications and disciplines, making it difficult to obtain an overview of the history, key issues, and core readings. Megaproject Planning and Management: Essential Readings (Flyvbjerg 2014a) assembled the central historical texts in the field. The Oxford Handbook of Megaproject Management has been designed to provide the most important contemporary readings. Taken together, the two books are intended to map out the best of what is worth reading in the megaproject management literature, past and present. In a recent survey, the author asked 114 experts to identify the classics in megaproject management (Flyvbjerg 2014b: xxx–​xxxi). The results show that if one defines a “classic” in the conventional sense—​as a written work that is generally recognized as definitive in its field by a majority of experts in that field—​then there are no classics in megaproject management. Remarkably, the publication proposed by the most respondents as a classic was proposed by only five respondents—​several times less the required majority for a classic. In no less than 79% of cases, a publication put forward as a classic was proposed by one and only one respondent, indicating a huge spread in views regarding what the classics might be in this field.

 

2   Bent Flyvbjerg Several explanations exist for this lack of consensus regarding classics in megaproject management. The field is young and unconsolidated as an academic discipline; therefore, perhaps more time is needed to develop and agree upon possible classics. Moreover, the field is multidisciplinary and fragmented, which makes consensus harder to come by. Whatever the explanation, Kuhn (2012) and other philosophers of science hold that classics are necessary to develop and strengthen an academic field, because classics serve as exemplars and reference points around which paradigmatic research may evolve and against which revolutionary research can pit itself. Following Kuhn and others, it is argued here that megaproject management, if it is to make progress as an academic field of inquiry and a professional field of practice, is very much in need of classics. The Oxford Handbook of Megaproject Management together with the previous book of historical texts have therefore been developed with the explicit purpose of contributing to the growth of such classics, and hopefully one or more papers in these books may one day become classics. In addition to the print version of The Oxford Handbook of Megaproject Management, an electronic version is planned to ensure the widest possible dissemination and to allow updates as new research appears.1 The primary audience for the book is the research academic community, professionals, doctoral students, master’s programs, and executive education programs in management, strategy, planning, megaproject management, and project and program management. It is hoped that by providing the present set of cutting-​edge contemporary readings in megaproject management the book will help progress the discipline, academically and professionally. It is also hoped that citizens and communities interested in and affected by megaprojects may find useful insights in this book.

1.2  What Are Megaprojects? Megaprojects are large-​scale, complex ventures that typically cost $1 billion or more, take many years to develop and build, involve multiple public and private stakeholders, are transformational, and impact millions of people.2 Hirschman (1995: vii, xi) calls such projects “privileged particles of the development process” and points out that often they are “trait making;” that is, they are designed to ambitiously change the structure of society, as opposed to smaller and more conventional projects that are “trait taking”—​they fit into and follow pre-​existing structures and do not attempt to modify them. Megaprojects, therefore, are not just magnified versions of smaller projects. Megaprojects are a completely different breed of project in terms of their level of aspiration, stakeholder involvement, lead times, complexity, and impact. Consequently, they are also a very different type of project to lead. Conventional project managers should not lead megaprojects. Megaprojects require reflective practitioners (Schön 1983) as leaders who have developed deep domain experience in this specific field.

 

Introduction   3 Megaprojects are increasingly used as the preferred delivery model for goods and services across a range of businesses and sectors, such as infrastructure, water and energy, information technology, industrial processing plants, mining, supply chains, enterprise systems, strategic corporate initiatives and change programs, mergers and acquisitions, government administrative systems, banking, defense, intelligence, air and space exploration, big science, urban regeneration, and major events (Chapter 2, Lenfle and Loch; Chapter 3, Siemiatycki). Examples of megaprojects are high-​speed rail lines, airports, seaports, motorways, disease or poverty eradication programs, hospitals, national health or pension ICT systems, national border control, national broadband, the Olympics, large-​scale signature architecture, dams, wind farms, server farms, offshore oil and gas extraction, aluminum smelters, the development of new aircrafts, the largest container and cruise ships, high-​energy particle accelerators, and the logistics systems used to run large supply-​chain-​based companies such as Apple, Amazon, and Maersk. To illustrate just how big megaprojects are, consider that in dollar terms some of the largest projects are as big as the GDP of many nations (Figure 1.1). Or take one of the largest dollar figures from public economic debate: the size of the US debt to China. This debt is just north of a US$1 trillion and is considered so large that it may destabilize the world economy if it is not managed prudently. With this supersize measuring rod, now consider the fact that the combined cost of just two of the world’s largest m ­ egaprojects—​ the Joint Strike Fighter aircraft program and China’s high-​speed rail project—​is more than half of this figure. The cost of a mere handful of the world’s largest megaprojects will dwarf almost any other economic figure, and certainly any investment figure. Finally, consider that in delivering a megaproject one has to—​over a relatively short period of time—​set up, run, and take down a temporary organization that is often the size of a billion-​dollar corporation. The size of megaprojects is staggering no matter what the comparison, and is matched only by the challenges of managing one.

2015 USD, billions GDP

Megaprojects

437

399

Measuring rod

329 246 156 98

67

68 11

Austria

Ireland

Kenya

Laos

Joint Strike Fighter

China HSR

International California Space HSR Station

HS2

Figure 1.1  Size of selected megaprojects, measured against GDP of selected countries.

 

4   Bent Flyvbjerg But megaprojects are not just large; they are constantly growing ever larger in a long historical trend with no end in sight. When New York’s Chrysler Building opened in 1930 at 319 meters it was the tallest building in the world. The record has since been surpassed seven times, and from 1998 the tallest building has significantly been located in emerging economies, with Dubai’s Burj Khalifa presently holding the record at 828 meters. That is a 160% increase in building height over eighty years. Similarly, the longest bridge span has grown even faster, by 260% over approximately the same period. Measured by value, the size of infrastructure projects has on average grown by 1.5–​2.5% annually in real terms over the past century, which is equivalent to a doubling in project size two to three times per century (author’s megaprojects database). The size of ICT projects, the new kid on the block, has grown much faster, as illustrated by a sixteen-​fold increase from 1993 to 2009 in lines of code in Microsoft Windows, from five to eighty million lines. Other types of megaprojects, from the Olympics to industrial projects, have seen similar developments. Coping with increased scale is therefore a constant and pressing issue in megaproject management, as emphasized by Ansar et al. (Chapter 4). With increasing scale comes increasing globalization, and a set of institutional issues related to this (Chapter 5, Levitt and Scott). “Mega” derives from the Greek word megas and means great, large, vast, big, high, tall, mighty, and important. As a scientific and technical unit of measurement, “mega” specifically means a million. If we were to use this unit of measurement in economic terms, then strictly speaking, megaprojects would be million-​dollar (or euro, pound, or other) projects, and for more than a hundred years the largest projects in the world were indeed measured mostly in the millions. This changed with World War II, the Cold War, and the Space Race. Project costs now escalated to the billions, led by the Manhattan Project (1939–​46), a research and development program that produced the first atomic bomb, and later the Apollo program (1961–​72), which landed the first humans on the moon (Morris 1994; Flyvbjerg 2014b). According to Merriam-​Webster, the first known use of the term “megaproject” was in 1976, but before that, from 1968, “mega” was used in “megacity” and later, from 1982, as a standalone adjective to indicate “very large.” Thus the term megaproject came into use just as the largest projects technically were megaprojects no more, but, to be accurate, “gigaprojects”—​“giga” being the unit of measurement meaning a billion. However, the term gigaproject has not caught on. A Google search reveals that the word megaproject is used more frequently on the Web than the term gigaproject.3 For the largest of this project type, costs of $50–​100 billion are now common, as for the California and UK high-​speed rail projects, and costs above $100 billion not uncommon, as for the International Space Station and the Joint Strike Fighter. If they were nations, projects of this size would rank among the world’s top hundred countries measured by gross domestic product—​larger than the economies of, for example, Kenya or Guatemala. When projects of this size go wrong, whole companies and national economies are affected. “Tera” is the next unit up, as the measurement for a trillion (a thousand billion). To illustrate how the numbers scale, consider that one million seconds ago, compared with the present, is twelve days in the past; a billion seconds is thirty-​two years in the past; and

 

Introduction   5 a trillion seconds is 31,710 years in the past, or the equivalent of several ice ages. Recent developments in the size of the very largest projects and programs indicate that we may presently be entering the “tera era” of large-​scale project management. Owing to large cost overruns, the Joint Strike Fighter program looks to become the first stand-​alone “teraproject” in human history, measured on life-​cycle costs (United States Government Accountability Office 2012). Similarly, if we consider as projects the stimulus packages that were launched by the United States, Europe, and China to mitigate the effects of the 2008 financial and economic crises, then these are teraprojects too. Finally, if the major acquisition program portfolio of the United States Department of Defense—​which was valued at $1.6 trillion in 2013—​is considered a large-​scale project, then this, again, would be a teraproject (United States Government Accountability Office 2013: 2). Projects of this size compare with the GDP of the world’s top twenty nations, similar in size to the national economies of, for example, Australia or Canada. There is no indication that the relentless drive to scale is abating in megaproject development. Quite the opposite; scale seems to be accelerating. Megaprojects are growing ever larger.

1.3  How Big Is the Global Megaprojects Business? Megaprojects are not only large and growing constantly larger; they are also being built in ever greater numbers at ever greater value. The McKinsey Global Institute (2013) estimates global infrastructure spending at US$3.4 trillion per year through 2013–​2030, or approximately 4% of total global gross domestic product, mainly delivered as large-​scale projects. The Economist (7 June 2008: 80) has similarly estimated infrastructure spending in emerging economies at US$ 2.2 trillion annually for the period 2009–​2018. To illustrate the accelerated pace at which spending is taking place, consider that China used more cement in the three years 2011–​13 than the United States in the entire twentieth century. Similarly, in a recent five-​year period China spent more on infrastructure in real terms than in the whole of the past century (Flyvbjerg 2014b). That is an increase in spending rate of a factor of twenty. Finally, in a recent four-​year period China built as many kilometers of high-​speed rail as Europe did in two decades, and Europe was extraordinarily busy building this type of rail during these years (Chapter 7, Ren). Not at any time in the history of mankind has infrastructure spending been this high measured as a share of world GDP, according to The Economist, who calls it “the biggest investment boom in history.” And that is just infrastructure. If we include the many other fields where megaprojects are a main delivery model—​ oil and gas, mining, aerospace, defense, ICT, supply chains, megaevents, and so on—​ then a conservative estimate for the global megaproject market is US$ 6–​9 trillion per year, or approximately 8% of total global gross domestic product. For perspective, consider that this is equivalent to spending five to eight times the accumulated US debt to

 

6   Bent Flyvbjerg China, every year. That is big business by any definition of the term. Moreover, megaprojects have proven remarkably recession-​proof. In fact, the downturn from 2008 helped the megaprojects business to grow further by showering stimulus spending on everything from transportation infrastructure to ICT. From being a fringe activity—​ albeit a spectacular one—​mainly reserved for rich, developed nations, megaprojects have recently transformed into a global multi-​trillion-​dollar business that affects all aspects of our lives, from our electricity bill to what we do on the Internet to how we work and shop and commute. With so many resources tied up in ever larger and ever more megaprojects, at no time has the management of such projects been more important. The potential benefits of building the right projects in the right manner are enormous and are only equaled by the potential waste from building the wrong projects, or building projects wrongly. Never has it been more important to choose the most fitting projects and get their financial, economic, social, and environmental impacts right. Never has systematic and valid knowledge about megaprojects therefore been more important to inform policy, practice, and public debate in this very costly area of government and business. The Oxford Handbook of Megaproject Management is dedicated to delivering such knowledge.

1.4  Ten Things you Must Know about Megaprojects What drives the megaproject boom described above? Why are megaprojects so attractive to decision makers? The answer to these questions may be found in the so-​called four sublimes of megaproject management (Table 1.1). The first of these, Table 1.1 The “four sublimes” that drive megaproject development Type of sublime

Characteristic

Technological

The excitement engineers and technologists get in pushing the envelope for what is possible in “longest–​tallest–​fastest” type of projects.

Political

The rapture politicians get from building monuments to themselves and their causes, and from the visibility this generates with the public and media.

Economic

The delight business people and trade unions get from making lots of money and jobs from megaprojects, including for contractors, workers in construction and transportation, consultants, bankers, investors, landowners, lawyers, and developers.

Aesthetic

The pleasure designers and people who love good design get from building and using something very large that is also iconic and beautiful, such as the Golden Gate bridge.

 

Introduction   7 the “technological sublime,” is a term variously attributed to Miller (1965) and Marx (1967) to describe the positive historical reception of technology in American culture during the nineteenth and early twentieth centuries. Frick (2008) introduced the term to the study of megaprojects and here describes the technological sublime as the rapture engineers and technologists obtain from building large and innovative projects, with their rich opportunities for pushing the boundaries for what technology can do, such as building the tallest building, the longest bridge, the fastest aircraft, the largest wind turbine, or the first of anything (see also Chapter 10, Miller et al.; Chapter 20, Holzmann et al.) Frick (2008) applied the concept in a case study of the multi-​billion-​dollar New San Francisco–​Oakland Bay Bridge, concluding that “the technological sublime dramatically influenced bridge design, project outcomes, public debate, and the lack of accountability for its [the bridge’s] excessive cost overruns” (239). Flyvbjerg (2012, 2014b) proposed three additional sublimes, beginning with the “political sublime,” which here is understood as the rapture politicians obtain from building monuments to themselves and their causes (Chapter 13, Baade and Matheson; Chapter 24, van der Westhuizen). Megaprojects are manifest; they garner attention and lend an air of proactiveness to their promoters. Moreover, they are media magnets, which appeals to politicians who seem to enjoy few things better than the visibility they get from starting megaprojects; except maybe cutting the ribbon of one in the company of royals or presidents who are likely to be present, lured by the unique monumentality and historical import of many such projects. This is the type of public exposure that helps politicians get re-​elected. They therefore actively seek it out. Next there is the “economic sublime,” which is the delight financiers, business people, and trade unions get from making lots of money and jobs from megaprojects. Given the enormous budgets for megaprojects, there are ample funds to go around for all, including contractors, engineers, architects, consultants, construction and transportation workers, bankers, investors, landowners, lawyers, and developers. Finally, the “aesthetic sublime” is the pleasure designers and people who appreciate good design get from building, using, and looking at something very large that is also iconically beautiful, such as San Francisco’s Golden Gate bridge or Sydney’s Opera House. All four sublimes are important drivers of the scale and frequency of megaprojects described above. Taken together they ensure that there exist strong coalitions of stakeholders who benefit from megaprojects and who will therefore work for more such projects to happen. For policy makers, investment in infrastructure megaprojects seems particularly coveted, because, if done right, such investment (i) creates and sustains employment, (ii) contains a large element of domestic inputs relative to imports, (iii) improves productivity and competitiveness by lowering producer costs, (iv) benefits consumers through higher-​quality services, and finally, (v) improves the environment when infrastructures that are environmentally sound replace infrastructures that are not (Helm 2008: 1; Chapter 11, Clegg et al.).

 

8   Bent Flyvbjerg But there is a big “if ” here, indicated previously with the words “if done right.” Only if this is disregarded—​as it often is by promoters and decision makers for megaprojects—​ can megaprojects be seen as an effective way to deliver infrastructure. In fact, conventional megaproject delivery—​infrastructure and other—​is highly problematic, with a dismal performance record in terms of actual costs and benefits, as we will see later. The following characteristics of megaprojects are typically overlooked or glossed over when the four sublimes are at play and the megaproject format is chosen for delivery of large-​ scale ventures: 1. Megaprojects are inherently risky because of long planning horizons and complex interfaces (Flyvbjerg 2006; Chapter 21, Davies). 2. Often projects are led by planners and managers without deep domain experience, who keep changing throughout the long project cycles that apply to megaprojects, leaving leadership weak. 3. Decision making, planning, and management are typically multi-​actor processes involving multiple stakeholders, public and private, with conflicting interests (Chapter 6, van Wee and Priemus; Chapter 15, Winch; Aaltonen and Kujala 2010). 4. Technology and designs are often non-​standard, leading to “uniqueness bias” among planners and managers, who tend to see their projects as singular, which impedes learning from other projects.4 5. Frequently there is overcommitment to a certain project concept at an early stage, resulting in “lock-​in” or “capture,” leaving alternatives analysis weak or absent, and leading to escalated commitment in later stages. “Fail fast” does not apply; “fail slow” does (Chapter 9, Drummond; Cantarelli et al. 2010; Ross and Staw 1993). 6. Because of the large sums of money involved, principal-​agent problems and rent-​ seeking behavior are widespread, as is optimism bias (Eisenhardt 1989; Stiglitz 1989; Flyvbjerg et al. 2009). 7. The project scope or ambition level will typically change significantly over time. 8. Delivery is a high-​risk, stochastic activity, with overexposure to so-​called black swans; that is, extreme events with massively negative outcomes (Taleb 2010). Managers tend to ignore this, treating projects as if they exist largely in a deterministic Newtonian world of cause, effect, and control. 9. Statistical evidence shows that such complexity and unplanned events are often unaccounted for, leaving budget and time contingencies for projects inadequate. 10. As a consequence, misinformation about costs, schedules, benefits, and risks is the norm throughout project development and decision making. The result is cost overruns, delays, and benefit shortfalls that undermine project viability during project delivery and operations. In Section 1.5, we will see just how big and frequent such cost overruns, delays, and benefit shortfalls are.

 

Introduction   9

1.5  The Iron Law of Megaprojects Performance data for megaprojects speak their own language. Of such projects, 70–90% have cost overruns, depending on project type. For some projects, such as the Olympics, 100% have cost overruns. Overruns of up to 50% in real terms are common, and over 50% not uncommon. Cost overrun for London’s Jubilee Line Underground extension was 80% in real terms; for Denver International Airport, 200%; Boston’s Big Dig, 220%; the Canadian Firearms Registry, 590%; Sydney Opera House, 1,400%. Overrun is a problem in private, as well as public sector projects, and things are not improving; overruns have stayed high and constant for the 90-​year period for which comparable data exist (Chapter 8, Flyvbjerg; Chapter 16, Hodge and Greve; Chapter 23, Chung). Geography also does not seem to matter; all 104 countries and six continents for which data are available suffer from overrun. Similarly, large benefit shortfalls are common, again with no signs of improvements over time and geographies (Flyvbjerg et al. 2002, 2005). Combine the large cost overruns and benefit shortfalls with the fact that business cases, cost-​benefit analyses, and social and environmental impact assessments are typically at the core of planning and decision making for megaprojects, and we see that such analyses can generally not be trusted. For instance, for dams an average cost overrun of 96% combines with an average demand shortfall of 11%, and for rail projects an average cost overrun of 40% combines with an average demand shortfall of 34%. With errors and biases of such magnitude in the forecasts that form the basis for business cases, cost–​benefit analyses, and social and environmental impact assessments, such analyses will also, with a high degree of certainty, be strongly misleading. “Garbage in, garbage out,” as the saying goes (Flyvbjerg 2009; for in-​depth studies of dams, see Chapter 19, Scudder; Chapter 25, Ahlers et al.). As a case in point, consider the Channel Tunnel, the longest underwater rail tunnel in Europe, connecting the United Kingdom and France. This project was originally promoted as highly beneficial both economically and financially. At the initial public offering, Eurotunnel, the private owner of the tunnel, tempted investors by telling them that 10% “would be a reasonable allowance for the possible impact of unforeseen circumstances on construction costs.”5 In fact, capital costs went 80% over budget, and financing costs 140%. Revenues started at a dismal 10% of those forecast, eventually growing to half of the forecast. As a consequence, the project has proved financially non-​viable, with an internal rate of return on the investment that is negative, at –​14.5%, with a total loss to Britain of US$17.8 billion. Thus the Channel Tunnel has detracted from the British economy instead of adding to it. This is difficult to believe when you use the service, which is fast, convenient, and competitive compared with alternative modes of travel. But in fact each passenger is heavily subsidized–​not by the taxpayer, as is often the case for other megaprojects, but by the many private investors who lost billions when Eurotunnel went insolvent and was financially restructured. This drives home an important point. A megaproject may well be a technological success but a

 

10   Bent Flyvbjerg financial failure, and many are. An economic and financial ex post evaluation of the Channel Tunnel, which s­ ystematically compared actual with forecast costs and benefits, concluded that “the British Economy would have been better off had the Tunnel never been constructed” (Anguera 2006: 291). Other examples of financially non-​viable megaprojects are Sydney’s Lane Cove Tunnel, the high-​speed rail connections at Stockholm and Oslo airports, the Copenhagen Metro, Denmark’s Great Belt Tunnel—​the second longest underwater rail tunnel in Europe after the Channel Tunnel, and the Chinese projects described in Ansar et al. (2016) (Table 1.2) (see also Chapter 17, Vickerman). Large-​scale ICT projects are even more risky. One in six such projects become a statistical outlier in terms of cost overrun, with an average overrun for outliers of 200% in real terms. This is a 2,000% overincidence of outliers compared to normal, and a 200% overincidence compared with large construction projects, which are also plagued by cost outliers (Flyvbjerg and Budzier 2011). Given the central role of large-​scale ICT projects in many transforming organizations in both government and business, the prevalence of ICT cost outliers are ticking time bombs under such transformations, waiting to go off. Total project waste from failed and underperforming ICT projects for the United States alone has been estimated at $55 billion annually by the Standish Group (2009). Delays are a separate problem for megaprojects, and delays cause both cost overruns and benefit shortfalls. For instance, results from a study undertaken at Oxford University, based on the largest database of its kind, shows that delays on dams are 45% on average (Ansar et al. 2014). Thus if a dam was planned to take ten years to execute, from the decision to build until the dam became operational, then it actually took 14½ years on average. Flyvbjerg et al. (2004) modeled the relationship between cost overrun and length of implementation phase based on a large dataset for major construction projects. They found that on average a one-​year delay or other extension of the implementation phase correlates with an increase in percentage cost overrun of 4.64%. To illustrate, for a project the size of London’s $26-​billion Crossrail project, a one-​year delay would cost an additional $1.2 billion, or $3.3 million per day. The key lesson here is that in order to keep costs down, implementation phases should be kept short and delays small. This should not be seen as an excuse for fast-​tracking projects; that is, rushing them through decision making for early construction start. All you do if you hit the ground running is fall, in the case of megaprojects. Front-​end planning needs to be thorough before deciding whether to give the green light to a project or stop it (Williams and Samset 2010). You need to go slow at first (during project preparation) in order to run fast later (during delivery). But often the situation is the exact opposite. Front-​end planning is rushed and deficient, bad projects are not stopped, implementation phases and delays are long, costs soar, and benefits and revenue realization diminishes and recedes into the future. For debt-​financed projects this is a recipe for disaster, because project debt grows while there are no revenues to service interest payments, which are then added to the debt, and so forth. As a result, many projects end up in the so-​called debt trap where a combination of escalating construction costs, delays, and increasing interest payments makes it impossible for project revenues to cover costs, rendering projects non-​viable. That is what happened to the Channel Tunnel and Sydney’s Lane Cove Tunnel, among many other projects.

 

Table 1.2 Large-​scale projects have a calamitous history of cost overrun Project

Cost overrun (%)

Suez Canal, Egypt

1,900

Scottish Parliament Building, Scotland

1,600

Sydney Opera House, Australia

1,400

Concord(e) Supersonic Aeroplane, UK, France

1,100

Troy and Greenfield Railroad, USA

900

Montreal Summer Olympics, Canada

720

Excalibur Smart Projectile, USA, Sweden

650

Canadian Firearms Registry, Canada

590

Medicare Transaction System, USA

560

National Health Service IT System, UK

550

Bank of Norway Headquarters, Norway

440

Lake Placid Winter Olympics, USA

320

Furka Base Tunnel, Switzerland

300

Verrazano Narrow Bridge, USA

280

Boston’s Big Dig Artery/​Tunnel Project, USA

220

Denver International Airport, USA

200

Panama Canal, Panama

200

Minneapolis Hiawatha Light Rail Line, USA

190

Humber Bridge, UK

180

Dublin Port Tunnel, Ireland

160

Montreal Metro Laval Extension, Canada

160

Copenhagen Metro, Denmark

150

Boston–​New York–​Washington Railway, USA

130

Great Belt Rail Tunnel, Denmark

120

London Limehouse Road Tunnel, UK

110

Brooklyn Bridge, USA

100

Shinkansen Joetsu High-​Speed Rail Line, Japan

100

Channel Tunnel, UK, France

80

Karlsruhe–​Bretten Light Rail, Germany

80

London Jubilee Line Extension, UK

80

Bangkok Metro, Thailand

70

Mexico City Metroline, Mexico

60

High-​Speed Rail Line South, Netherlands

60

Great Belt East Bridge, Denmark

50

 

12   Bent Flyvbjerg This is not to say that megaprojects do not exist that were built on budget and on time and delivered the promised benefits (Chapter 12, Gil; Chapter 14, Davies et al.). The Bilbao redevelopment project, with the Guggenheim Museum Bilbao, is an example of that rare breed of project (Chapter 22, del Cerro Santamaria). Similarly, recent metro extensions in Madrid were built on time and to budget (Flyvbjerg 2005), as were a number of industrial megaprojects (Merrow 2011). It is particularly important to study such projects to understand the causes of success and test whether success may be replicated elsewhere. It is far easier, however, to produce long lists of projects that have failed in terms of cost overruns and benefit shortfalls than it is to produce lists of projects that have succeeded. To illustrate, as part of ongoing research on success in megaproject management, the present author and his colleagues are trying to establish a sample of successful projects large enough to allow statistically valid answers. But so far they have failed. Why? Because success is so rare in megaproject management that at present, it can be studied only as small-​sample research, whereas failure may be studied with large, reliable samples of projects. Success in megaproject management is typically defined as projects delivering the promised benefits on budget and on time. If, as the evidence indicates, approximately 1–​2 out of ten megaprojects are on budget, 1–​2 out of ten are on schedule, and 1–​2 out of ten are on benefits, then approximately 1–​8 in a thousand projects is a success, defined as on target for all three. Even if the numbers were wrong by a large margin the success rate would still be dismal. This serves to illustrate what may be called the “iron law of megaprojects:” Over budget, over time, under benefits, over and over again (Flyvbjerg 2011). Best practice is an outlier, and average practice a disaster, in this interesting and very costly area of management.

1.6  The Megaprojects Paradox This analysis leaves us with a genuine paradox: the so-​called megaprojects paradox, first identified by Flyvbjerg et al. (2003: 1–​10). On one side of the paradox, megaprojects as a delivery model for public and private ventures have never been more in demand, and the size and frequency of megaprojects have never been larger. On the other side, performance in megaproject management is strikingly poor and has not improved for the 90-​year period for which comparable data are available, when measured in terms of cost overruns, schedule delays, and benefit shortfalls. Today, megaproject planners and managers are stuck in this paradox because their main delivery method is what has been called the “break–​fix model” for megaproject management.6 Generally, megaproject managers—​and their organizations—​do not know how to deliver successful megaprojects, or do not have the incentives to do so. Therefore megaprojects tend to “break” sooner or later—​for instance, when reality catches up with optimistic, or manipulated, estimates of schedule, costs, or benefits; and delays, cost overruns, and so on, follow. Projects are then often paused and

 

Introduction   13 reorganized—​sometimes also refinanced—​in an attempt to “fix” problems and deliver some version of the initially planned project with a semblance of success. Typically, lock-​ in and escalation make it impossible to drop projects altogether, which is why megaprojects have been called the “Vietnams” of policy and management: “easy to begin and difficult and expensive to stop” (White 2012; also Cantarelli et al. 2010; Ross and Staw 1993; Drummond 1998). The “fix” often takes place at great and unexpected cost to those stakeholders who were not in the know of what was going on and were unable to or lacked the foresight to pull out before the break.7 The break–​fix model is wasteful and leads to a misallocation of resources, in both organizations and society, for the simple reason that under this model decisions to go ahead with projects are based on misinformation more than on information, with misinformation caused by a lack of realism at the outset. The degree of misinformation varies significantly from project to project, as seen by the large standard deviations that apply to cost overruns and benefit shortfalls documented by Flyvbjerg et al. (2002, 2005). We may therefore not assume, as is often done, that on average all projects are misrepresented by approximately the same degree and that, therefore, we are still building the best projects, even if they are not as good as they appear on paper. The truth is, we do not know, and often projects turn out to bring a net loss, instead of a gain, to the government or company that promoted them. The root cure to the break–​fix model is to get projects right from the outset so that they do not break, through proper front-​end management, and then have competent teams deliver a realistic front end (Chapter 18, Volden and Samset; Williams and Samset 2010). But megaproject managers must also know how to fix projects once they break, for the simple reason that so many break. The present book deals with both types of situation: (i) getting projects right from the start, and (ii) fixing projects that break.

1.7  Challenges, Causes, Cures The chapters in the book have been selected to give readers a thorough, research-​based understanding of (i) the challenges in megaproject management, (ii) the root causes of those challenges, and (iii) cures that may help meet the challenges. The book is thus systematically focused on the what, the why, and the how of megaproject management. In addition, it contains a set of case studies to exemplify general points. First, as regards the what of megaproject management—​the challenges—​Lenfle and Loch (Chapter 2) and Siemiatycki (Chapter 3) present the historical overview. Ansar et al. (Chapter 4) focus on the basic challenge of scale and attempt to theorize scale in terms of fragility. Levitt and Scott (Chapter 5) deal with institutional challenges, especially as these pertain to global megaprojects; that is, projects that span activities in multiple countries, as is increasingly common for megaprojects. van Wee and Priemus (Chapter 6) spell out an important but often overlooked aspect of megaproject management: namely, the ethical and political issues involved; what is megaproject ethics, they

 

14   Bent Flyvbjerg ask? Finally, Ren (Chapter 7) poses a truly sobering question of current debt-​financed megaproject investments in China: “Is this the biggest infrastructure bubble in the history of humankind?” Second, for the why of megaproject management—​ the causes—​Flyvbjerg (Chapter 8) explores a recent claim made by Cass Sunstein, professor at Harvard, that behavioral economics was pioneered by early research on large projects and that this research accounts well for behavior with megaproject planners and managers. Drummond (Chapter 9) updates and appraises key theories on escalation of commitment and lock-​in, as they pertain to megaprojects. Miller et al. (Chapter 10) explain megaproject management in terms of games of innovation, and they explicate how the game is best played. Clegg et al. (Chapter 11) present an overview of how scholars and practitioners make sense of megaprojects and megaproject management, and how power is related to such sensemaking. Gil (Chapter 12) introduces a new collective-​action perspective on the planning of megaprojects with a focus on dispute resolution, central to any megaproject. Baade and Matheson (Chapter  13) spell out the drivers of megaevents in emerging economies—​an issue of growing importance as megaevents and other types of megaprojects have shifted in increasing numbers from developed to emerging economies, with the major part of investments now happening in the latter. Third, concerning the how of megaproject management—​the cures—​Davies et al. (Chapter 14) describe a new delivery model for megaprojects aimed at securing innovation and flexibility in projects, and they illustrate how the model worked for three UK megaprojects. Winch (Chapter 15), drawing on developments in strategic management research, broadens the notion of stakeholder management to better take into account pressing issues of future generations and the natural environment. Hodge and Greve (Chapter 16) ask and answer the question of how well privatization works as a cure to the challenges of megaproject delivery. Vickerman (Chapter 17) identifies as dubious the common claim that the wider benefits of megaprojects are large and will often justify projects, even when direct benefits do not. Volden and Samset (Chapter 18) describe how Norway implemented a quality assurance program for megaprojects and how this has improved outcomes. Based on a lifetime of research, Scudder (Chapter 19) closes this part of the book by synoptically asking and answering the following question of the perhaps ultimate megaproject, the megadam: “Does the good megadam exist, all things considered?” Fourth, and finally, Holzmann et  al. (Chapter  20) launch the case studies with an in-​depth inquiry into how the team on Boeing’s 787 cracked the code of innovation in megaproject delivery—​something high on the agenda for most megaprojects, irrespective of type. Davies (Chapter 21) spells out the lessons learned from the London 2012 Olympic Games in terms of systems integration—​again a general concern in most megaprojects. del Cerro Santamaria (Chapter 22) updates and sets straight the record for perhaps the most iconic urban megaproject of the past generation, the $1.5-​billion Strategic Plan for the Revitalization of Metropolitan Bilbao, spearheaded by what Philip Johnson, the godfather of architecture, called “the greatest building of our time:” Frank Gehry’s Guggenheim Museum Bilbao. Chung (Chapter 23) navigates the maze

 

Introduction   15 of Australia’s slightly dodgy experience with public–​private partnerships in the provision of motorways, and identifies the challenges and opportunities for going forward. van der Westhuizen (Chapter 24) tells the story of megaprojects as mythical political symbols, focusing on Africa’s first high-​speed railway, the Gautrain, which was initially packaged with South Africa’s bid to host the 2010 Soccer World Cup, another first for Africa. Lastly, Ahlers et al. (Chapter 25) study the Aswan High Dam on the Nile and the Nam Theun 2 on the Mekong to illustrate how dam development has changed recently to a situation where political power is more diffuse and where basic transparency and citizens’ rights are therefore more difficult to secure; the authors suggest “dam democracy” as an organizing principle for addressing these issues. In sum, the chapters for this book were selected to be strong on theory and to contain high-​quality data, as an antidote to the weak theory and idiosyncratic data that characterize much scholarship in megaproject management (Flyvbjerg 2011). Strong theory is here understood as ideas with a high degree of explanatory power for phenomena in megaproject management. Good data are valid and reliable information that allows systematic comparison of important variables across projects, studies, geographies, and time, or make possible high-​quality in-​depth case studies. The focus on strong theory and good data is intended to help bring the field forward academically and professionally. As a further criterion, chapters were selected that are relevant not only to developed nations, but also to emerging economies, because at present the main part of investments in megaprojects is taking place here. Finally, chapters providing an historical overview of the field and good case studies have been included. The intention has been to produce a well-​rounded book that is a must-​read for anyone embarking on study, research, or practice in megaproject management, or who is impacted by megaprojects and wants to understand them better.

Acknowledgments I would like to thank the contributors to The Oxford Handbook of Megaproject Management for the quality of their contributions and for their patience with my requests for changes during the editing of the book. Special thanks are due to David Musson, former Business and Management Editor at Oxford University Press. David poked me seven years ago to do this book. I deferred, because at the time I did not think there was enough high-quality scholarship in the field of megaproject management to justify, let alone fill, a major volume like this. Today, this situation has happily changed. Megaproject management is rapidly establishing itself as a new field of academic inquiry. I would like to thank the University of Oxford and Saïd Business School for pioneering this development by having the foresight to establish the first permanent chair and the first degree program in the world in this budding area of scholarship, and for giving me the honor of being the first holder of the chair and academic director of the program. This gave me the ideal conditions for working on the Handbook. Finally, I wish to thank Clare Kennedy, Assistant Commissioning Editor of Business and Management

 

16   Bent Flyvbjerg at Oxford University Press, for excellently seeing the book through the production and printing process to become the handsome tome you are now holding in your hand or viewing on your screen. Bent Flyvbjerg Jericho, Oxford July 2016

Notes 1. See more at . 2. “Megaprojects” are usually measured in billions of dollars; “major projects” in hundreds of millions; and “projects” in millions or tens of millions. Megaprojects are sometimes also called “major programs.” 3. Google search, 17 January 2017. 4. “Uniqueness bias” is here defined as the tendency of planners and managers to see their projects as singular. This particular bias stems from the fact that new projects often use non-​ standard technologies and designs, leading managers to think their project is more different from other projects than it actually is. Uniqueness bias impedes managers’ learning, because they think they have nothing to learn from other projects as their own project is unique. This lack of learning may explain why managers who see their projects as unique perform significantly worse than other managers (Budzier and Flyvbjerg 2013). Project managers who think their project is unique are therefore a liability for their project and organization. For megaprojects this would be a megaliability. 5. Quoted from “Under Water Over Budget,” The Economist, 7 October 1989, 37–​8. 6. The author owes the term “break–​fix model” to Dr Patrick O’Connell, former Practitioner Director at the BT Centre for Major Programme Management, Saïd Business School, University of Oxford. 7. For a rare look behind the scenes of a break–​fix project—​to see in real time how a break happens and a fix is attempted—​see Flyvbjerg et al. (2014), about Hong Kong’s XRL high-​ speed rail line to mainland China, which broke in 2014, midway through construction.

References Aaltonen, K. and Kujala, J. (2010). “A project lifecycle perspective on stakeholder influence strategies in global projects,” Scandinavian Journal of Management, 26: 381–​97. Anguera, R. (2006). “The Channel Tunnel: An ex post economic evaluation,” Transportation Research Part A, 40: 291–​315. Ansar, A., Flyvbjerg, B., Budzier, A., and Lunn, D. (2014). “Should we build more large dams? The actual costs of hydropower megaproject development,” Energy Policy, March: 43–​56. Ansar, A., Flyvbjerg, B., Budzier, A., and Lunn, D. (2016). “Does infrastructure investment lead to economic growth or economic fragility? Evidence from China,” Oxford Review of Economic Policy, 32(3): 360–​90. Budzier, A. and Flyvbjerg, B. (2013). “Making sense of the impact and importance of outliers in project management through the use of power laws,” Proceedings of IRNOP (International Research Network on Organizing by Projects), vol. 11 (June), pp. 1–​28.

 

Introduction   17 Cantarelli, C. C., Flyvbjerg, B., van Wee, B., and Molin, E. J.  E. (2010). “Lock-​in and its influence on the project performance of large-​scale transportation infrastructure projects:  Investigating the way in which lock-​ in can emerge and affect cost overruns,” Environment and Planning B: Planning and Design, 37: 792–​807. Drummond, H. (1998). “Is escalation always irrational?” Organization Studies, 19(6): 911–​29. Economist, The. (2008). “Building BRICs of growth,” 7 June: 80. Eisenhardt, K. M. (1989). “Agency theory: An assessment and review,” Academy of Management Review, 14(1): 57–​74. Flyvbjerg, B. (2005). “Design by deception:  The politics of megaproject approval,” Harvard Design Magazine, no. 22, Spring/​Summer: 50–​9. Flyvbjerg, B. (2006). “From Nobel Prize to project management: Getting risks right,” Project Management Journal, 37(3): 5–​15. Flyvbjerg, B. (2009). “Survival of the unfittest: Why the worst infrastructure gets built, and what we can do about it,” Oxford Review of Economic Policy, 25(3): 344–​67. Flyvbjerg, B. (2011). “Over budget, over time, over and over again: Managing major projects,” in P. W. G. Morris, J. K. Pinto, and J. Söderlund (eds.), The Oxford Handbook of Project Management. Oxford: Oxford University Press, pp. 321–​44. Flyvbjerg, B. (2012). “Why mass media matter, and how to work with them: Phronesis and megaprojects,” in B. Flyvbjerg, T. Landman, and S. Schram (eds.), Real Social Science: Applied Phronesis. Cambridge: Cambridge University Press, pp. 95–​121. Flyvbjerg, B. (ed.) (2014a). Megaproject Planning and Management: Essential Readings, vols. 1–​2. Cheltenham, UK, and Northampton, MA: Edward Elgar. Flyvbjerg, B. (2014b). “Introduction,” in B. Flyvbjerg (ed.), Megaproject Planning and Management: Essential Readings, vols. 1–​2. Cheltenham, UK, and Northampton, MA: Edward Elgar, pp. xiii–​xxxiv. Flyvbjerg, B., Bruzelius, N., and Rothengatter, W. (2003). Megaprojects and Risk: An Anatomy of Ambition. Cambridge: Cambridge University Press. Flyvbjerg, B. and Budzier, A. (2011). “Why your IT project might be riskier than you think,” Harvard Business Review, 89(9): 24–​7. Flyvbjerg, B., Garbuio, B., and Lovallo, D. (2009). “Delusion and deception in large infrastructure projects: Two models for explaining and preventing executive disaster,” California Management Review, 51(2): 170–​93. Flyvbjerg, B., Holm, M. K. S., and Buhl, S. L. (2002). “Underestimating costs in public works projects: Error or lie?” Journal of the American Planning Association, 68(3): 279–​95. Flyvbjerg, B., Holm, M. K. S., and Buhl, S. L. (2004). “What causes cost overrun in transport infrastructure projects?” Transport Reviews, 24(1): 3–​18. Flyvbjerg, B., Holm, M. K. S., and Buhl, S. L. (2005). “How (in)accurate are demand forecasts in public works projects? The case of transportation,” Journal of the American Planning Association, 71(2): 131–​46. Flyvbjerg, B., Kao, T.-​C., and Budzier, A. (2014). “Report to the Independent Board Committee on the Express Rail Link Project,” in MTR Independent Board Committee: Second Report by the Independent Board Committee on the Express Rail Link Project. Hong Kong: MTR, pp. A1–​122. Frick, K. T. (2008). “The cost of the technological sublime: Daring ingenuity and the new San Francisco–​Oakland Bay Bridge,” in H. Priemus, B. Flyvbjerg, B. van Wee (eds.), Decision-​ Making on Mega-​Projects:  Cost–​Benefit Analysis, Planning, and Innovation. Cheltenham, UK, and Northampton, MA: Edward Elgar, pp. 239–​62.

 

18   Bent Flyvbjerg Helm, D. (2008). “Time to invest: Infrastructure, the credit crunch and the recession,” Monthly Commentary, 18 December, . Hirschman, A. O. (1995). Development Projects Observed. Washington, DC:  Brookings Institution. First published 1967. Kuhn, T. S. (2012). The Structure of Scientific Revolutions, 4th edn. Chicago, IL: University of Chicago Press. First published in 1962. Marx, L. (1967). The Machine in the Garden:  Technology and the Pastoral Ideal in America. Oxford and New York: Oxford University Press. McKinsey Global Institute. (2013). Infrastructure Productivity: How to Save $1 Trillion a Year. New York: McKinsey and Company. Merrow, E. W. (2011). Industrial Megaprojects: Concepts, Strategies, and Practices for Success. Hoboken, NJ: Wiley. Miller, P. (1965). The Life of the Mind in America:  From the Revolution to the Civil War. New York: Harvest Books. Morris, P. W. G. (1994). “The 1960s: Apollo and the decade of management systems,” in The Management of Projects. Reston, VA: American Society of Civil Engineers, pp. 38–​88. Ross, J. and Staw, B. M. (1993). “Organizational escalation and exit: Lessons from the Shoreham nuclear power plant,” The Academy of Management Journal, 36(4): 701–​32. Schön, D. A. (1991). The Reflective Practitioner: How Professionals Think in Action. New York: Basic Books. First published 1983. Standish Group. (2009). CHAOS Report. West Yarmouth, MA. Stiglitz, J. (1989). “Principal and agent,” in J. Eatwell, M. Milgate, and P. Newman (eds.), The New Palgrave: Allocation, Information and Markets. New York: Norton, pp. 241–​53. Taleb, N. N. (2010). The Black Swan: The Impact of the Highly Improbable, 2nd edn. London and New York: Penguin. United States Government Accountability Office (GAO). (2012). Joint Strike Fighter: DOD Actions Needed to Further Enhance Restructuring and Address Affordability Risks, Report GAO-​12-​437. Washington, DC: Government Accountability Office. United States Government Accountability Office (GAO). (2013). Defense Acquisitions: Assess­ ments of Selected Weapon Programs, Report GAO-​13-​294SP. Washington, DC: Government Accountability Office. White, R. (2012). “A waste of money, for years to come,” The New York Times, 27 January, . Williams, T. and Samset, K. (2010). “Issues in front-​end decision making on projects,” Project Management Journal, 41(2): 38–​49.

 

Pa rt  I

C HA L L E N G E S

 

 

Chapter 2

Has Megaproj e c t Managem e nt L o st Its Way? Lessons from History Sylvain Lenfle and Christoph Loch

The performance track record of megaprojects is dismal, even though the basic ingredients of successful large project management are not new. Put simply, the trick is to combine uncertainty in dealing with the difficulties of long time horizons and non-​standard technologies with stakeholder complexity as expressed through the involvement of multiple powerful interested parties (Flyvbjerg and Cowi 2004). This challenge was conquered in the successful creation of the atomic bomb in the 1940s; but seventy years on, some of the lessons of the Manhattan Project are not being heeded, and modern megaprojects are the poorer because of it. Take the nuclear reactor industry, a poster child for delays and budget overruns. The current generation II EPR reactors were announced as the future in 2003, and construction began on the first project in Finland in 2005 with plans to launch operation in 2009. But this project will (as of the status in August 2015) not start operating before 2018 and has already incurred a cost escalation from €3.3 billion to €8.5 billion (World Nuclear Association 2015). Another project using the EPR technology in Flamanville in France is now expected to take more than double the original timeframe and cost €9 billion rather than the initial estimate of €3.3 billion (Le Monde, 21 April 2015). The Hinkley Point C project in the United Kingdom is too early in its construction to show large overruns, but to reflect high risks, there are hefty price guarantees built into its building contract (Taylor 2016: ch. 12). Nuclear power is not alone. Studies show that 90% of major projects are over budget, with overruns of above 50% being common (Flyvbjerg 2011). A country-​specific study in Germany found that among 170 megaprojects, the average budget overrun

 

22    Sylvain Lenfle and Christoph Loch was 73% (Kostka 2015). One study calls big cost overruns the “iron law of megaprojects” (Flyvbjerg 2014). This chapter illustrates that it is possible to identify a few core management shortcomings that have significantly contributed to such systemic-​like failures. We then show that knowledge of how to address these shortcomings existed and was partly applied as early as during the World War II. Thirdly, we will use this review of past knowledge in order to sketch some recommendations for managerial measures that might help improve performance of megaproject management today.

2.1  Three Common Causes of Megaproject Failures When we describe the spectacular failures of large projects over the last decades, three overarching themes arise.

2.1.1 Underestimation of, or Refusal to Acknowledge, Uncertainty Megaprojects are often started on the assumption that with enough planning, the design and project plan can be firmly designed at the beginning. But over long timeframes, with non-​standard technology and multiple interested parties, it is impossible to plan for everything—​and parties then slip into a damaging fight for control that results in multiple redesigns and additional costs. A case in point is the Circored project, a pioneering iron ore reduction facility to produce pure iron briquettes, undertaken in Trinidad (Loch and Terwiesch 2002). The project began in 1995 with a target start of production in 1999, owned and run by the iron-​ore company Cleveland Cliffs, using a new technology that Lurgi AG had developed and tested in a small prototype. An intensive risk analysis suggested that all problems could be anticipated and managed, but many unforeseen problems occurred in the scale-​up, delaying the project by two years. Although the project ultimately succeeded technically, the delay made the facility vulnerable to the commodity price meltdown of 2002 and thus unprofitable. Ultimately, Cleveland Cliffs wrote off the plant and sold it at a steep discount to Mittal. A key reason for the failure is that while Lurgi understood its technology’s immaturity and technical risks, the plant owner rejected a longer testing phase on grounds that risks could be contained through proper planning and analysis. So ensuing problems had to be dealt with reactively, costing more in time and money than if properly addressed to begin with.

 

Has Megaproject Management Lost Its Way?    23

2.1.2 Stakeholder Neglect or Mismanagement Megaprojects normally require coalitions of active partners in addition to the support or at least passive tolerance of external stakeholders who do not participate directly. Peril inevitably results when stakeholders are ignored, or when a false agreement is finessed, causing conflicts to fester, hidden behind wooly political statements. A famous example is the Eurotunnel project (Bensen et al. 1989a and b), which between 1987 and 1994 dug a 50-​km twin tunnel under the English Channel, through which passenger and freight trains now pass between Calais and Dover. The initial project had a seven-​year duration and a (1987) budget of £4.8 billion, but ran over by 29% in schedule (after the original opening target of June 1993, freight operations started in May 1994, but full operations were not achieved until December 1994), and ran over budget by 65%, for a total cost of £8 billion. Also, some initial specifications were not achieved, with trains running through the tunnel at 80 km/​h compared with the original target of 160 km/​h—​thus extending travel time and reducing tunnel capacity. But most importantly, the operator, Eurotunnel plc, came out of the project so debt-​burdened that it could not turn a profit, and shareholders lost their investment twice (Garg et al. 2008), until finally the banks forgave a significant percentage of the debt in 2013. The Eurotunnel troubles were not rooted in uncertainty: although some new tunneling machinery was used, related problems were quickly handled, and initial projections of revenues and operating profits turned out to be fairly close. Instead, the root cause for Eurotunnel’s woes was in the fraught relationships among the stakeholders: the construction consortium and the later operator Eurotunnel were in constant conflict and embroiled in lawsuits; the banks managed to transfer all risks, including inflation, to Eurotunnel, which resulted in a three-​month work hold-​up and an inflated debt burden. Stakeholder conflicts are a major source of project problems and are especially dangerous for megaprojects, which by their very nature involve many parties with the power to exert influence. Whenever a party is ignored, or when an agreement forces one party into agreement or superficially glosses over differences in views or interests, then these agreements probably break apart when changes disrupt the equilibrium—​ at which point the parties then no longer collaborate but work against one another (Loch et al. 2015).

2.1.3 Inflexible Contractor Management (Prominently, Awarding Work to the Lowest Bidder) Many parties have to collaborate in order to accomplish megaprojects owing to their sheer size and variety of expertise required. The well-​known practice of “bid low and sue later” is caused by project owners awarding contracts on the basis of the lowest bid

 

24    Sylvain Lenfle and Christoph Loch price, forcing contractors to bid aggressively and then work inflexibly—​asking for more compensation with every change in the project. This was already observed thirty years ago (McDonald and Evans 1998), and is still alive and well—​and criticized by a German government commission that examined practices in large public works projects (Kammholz 2015). A globally visible specific example is in the $5.25-​billion megaproject for the expansion of the Panama Canal, which invited bids in 2009 and was scheduled to open in 2014. A Spanish-​led consortium of construction firms won the $3.2-​billion bid for the locks of the fifty-​ mile waterway, underbidding a US-​led rival consortium by $1 billion. But in 2014 the consortium demanded a $1.6-​billion compensation from the Panama Canal Authority (PCA), the project owner, citing “breaches of contract” (for example, claiming they were misled about geological ground conditions). The dispute has already delayed the project to mid-​2015. However, concerns were voiced right at the outset that the bid was too low, and that a cost increase would be required at some point (Kriel and Dowsett 2014). Although the PCA defends the original bid as reasonable, experts openly discuss the aggressive underbidding strategy used (The Economist 2014).

2.1.4 Interactions Among the Themes These three root causes of problems are even more difficult to address because they strongly interact. For example, stakeholders in the Eurotunnel project had differing interests such as the short-​term view of the constructor versus the long-​term operator’s view. In an atmosphere of mutual distrust, even moderate uncertainties are difficult to address, leading to disputes (such as over cost overruns) and even further distrust. As a result, collaboration becomes even harder. Yet although these challenges are difficult to address, there are potential solutions that have been ignored. Relevant knowledge has been available for seven decades, but much of this knowledge has been disregarded and not used effectively in the project community—​as we describe next.

2.2  What Project Management Already Knew in the 1940s The irony is that, historically, there were projects where these three problems were in fact overcome. This is particularly true of the World War II and large post-​war US military and space projects which, interestingly, are the roots of contemporary project management. Indeed, the Manhattan, Atlas, Polaris, and Apollo projects, to name the most famous ones, were managed very successfully, and on schedule. It is therefore interesting

 

Has Megaproject Management Lost Its Way?    25 to draw lessons from these cases. At the conceptual level, these projects did two crucial things right. First, on the organizational level, they created almost from scratch a dedicated organization to overcome the traditional bureaucratic fights that plagued major R&D projects. The development of Intercontinental Ballistic Missiles (ICBM) within the US Air Force and the US Navy is typical of this strategy. Consider briefly the Polaris case (Sapolsky 2003). The problem was to coordinate and integrate the functionally defined branches or bureaus and the dozens of firms involved. Moreover, as a new technology, ballistic missiles did not fit easily into the existing weapons acquisition structures: it was neither a bomber, nor a bomb, nor a guided missile. To overcome this problem, the Navy created the Special Project Office (SPO)—​a new body that had complete autonomy and power to manage the Polaris project. It was supervised by a brilliant and powerful project manager, Admiral William F. Raborn, who infused a sense of dedication and urgency into the entire team. He said: “Our religion was to build Polaris” (Spinardi 1994: 35). The creation of this structure constitutes unquestionably one of the key success factors of the Polaris project (Sapolsky 1972). And we find a similar logic, a dedicated organization led by a brilliant project manager, in all the aforementioned projects (the Manhattan Engineer District and L. Groves, the Western Development Division of the USAF and B. Schriever, the Office of Manned Space Flight and S. Phillips). Therefore, the success of these projects rested on “doing what it took” with almost unlimited project management power, supported by almost complete autonomy to take the right actions in the interest of achieving the goals. Second, concerning the management of uncertainty, these PMs developed brilliant insights. They understood, right from the outset, that one does not know what one does not know. This cannot be more clearly stated than by General Groves when he stated that, given the huge unforeseeable uncertainties of the design of the atomic bomb, they were “proceeding in the dark” (Groves 1962: 40) and, therefore “had to abandon completely all normal orderly procedures” (72). What is fascinating is that they drew the right managerial conclusions: they combined experimentation (for example, in the form of pilots), parallel pursuit of alternatives, and dedicated (possibly costly) actions to gather information as part of the core project activities. The Manhattan Project forcefully demonstrates the relevance of this approach: acknowledging that it was impossible to define, at the outset, the right design of an atomic bomb, Groves and the steering committee decided to simultaneously explore different technical solutions both for the production of fissionable materials and for the design of the bomb. This explains why the two bombs dropped on Japan had completely different designs, and also how they succeeded in such a short time to overcome the tremendous scientific and engineering challenges (Lenfle 2011). This strategy was transferred directly to the ICBM Atlas project (and others) through discussions between Groves, Oppenheimer, and B. Schriever, chief of the Western Development Division of the USAF (Hughes 1998). It is sobering for project management how these lessons have been lost in the course of the institutionalization of the discipline. Indeed, the principles of uncertainty

 

26    Sylvain Lenfle and Christoph Loch management were theoretically well understood in the 1950s, especially the need for experimentation and adjustment, and the advantage of starting multiple parallel trials on subprojects in order to assure one successful outcome (Alchian and Kessel 1954; Arrow 1955; Klein and Meckling 1958). However, these principles had completely disappeared from PM textbooks and have only recently been rediscovered (from the view of multiple disciplines, for example, Leonard-​Barton 1995; Loch et al. 2006). Lenfle and Loch (2010) show how flexible approaches to uncertainty were abandoned in favor of a more control-​oriented view of PM as the accomplishment of a clearly defined goal through a phased/​stage-​gate logic. This process unfolded in three dimensions (Lenfle and Loch 2010): 1. On the political side, the deployment of ballistic missiles completely changed the context. The fear of a “missile gap” disappeared, and the sense of utmost urgency of the military megaprojects faded away. This led to an important reorganization within the DoD in the form of the Defense Reorganization Act of 1958, which greatly increased the power of the Secretary of Defense over the armed services. It gave him the authority to “transfer, reassign, abolish, or consolidate” service functions, and control over the budget. This paved the way for the “McNamara revolution.” Coming from the Ford Motor Company, Robert McNamara, named Secretary of Defense in 1961, started a complete reorganization of the planning process in the DoD. His objective was to consolidate planning and budgeting, which hitherto had been two separate processes. He pursued his objective with the implementation of the famous Program Planning and Budgeting System (PPBS). This process was antipodean with the logic of the early missile projects and prompted a complete reversal in project management. Indeed, it emphasized the complete definition of the system before its development in order to limit uncertainty and institutionalize a phased approach. This de facto eliminated parallel trials and concurrency. Therefore, the phased-​planning approach (now called Stage-​Gate) became the project management model of the DoD and the newly formed NASA (Johnson 2000). This was enforced by the diffusion of managerial tools such as PERT. In particular, a NASA/​DoD PERT/​Cost Guide was issued in 1962 and became part of the bidding process of both administrations, transforming these tools into de facto standards for project management. This limited the scope of project management for the ensuing decades. From now on, strategy was centralized at the DoD, and Project Management’s role was to execute given missions. 2. This shift had a theoretical counterpart. Indeed, the McNamara revolution was theoretically grounded in RAND thinking and its faith in rational decision making.1 This view was clearly expressed by Charles Hitch, an eminent RAND member who later became comptroller of the Department of Defense under McNamara. In 1960 he published The Economics of Defense in the Nuclear Age, which introduced a broad audience to a view of defense as an economic problem of resource allocation to achieve a desired objective. This view had major consequences for project management: the focus gradually changed from the “performance at all costs” attitude of the first missiles projects to one of optimizing the cost/​performance ratio.

 

Has Megaproject Management Lost Its Way?    27 This new logic is clearly visible in the early literature on project management. For example, Systems Analysis and Project Management (1968) by Cleland and King became a classic. The book is typical of the phased logic. It consists of two parts that corresponded to the two key project phases. The first advocated the power of systems analysis to analyze complex strategic issues and define project missions. The second part dealt with project execution and emphasized the need to create a specific project organization to integrate stakeholder contributions, along with project planning and control using formal methods. The result of all of these events was that by the early 1970s the phased approach had become “natural.” 3. The last stage of this standardization process was the creation, in 1969, of a professional organization: the US Project Management Institute. Indeed, the years following the success of Polaris saw a plethora of publications and an intense promotion of the PERT/​CPM method by numerous consulting firms (Vaszonyi 1970). The planning method was viewed as synonymous with success in the management of large projects. The idea of a professional association arose in this context within the tight-​knit community of PERT and CPM users (R. Archibald, E.  Benett, J. Snyder, N. Engman, J. Gordon Davis, and S. Gallagher). Since all its founders were project control experts, it was natural for the PMI to focus on control tools, such as PERT/​CPM. Therefore, for the next two decades, “modern project management” became equated with PERT/​CPM after Polaris and the MacNamara revolution (Snyder 1987). This, as the reader will recognize, provides the basic principles of the dominant model of project management today: the stage-​gate process. The problem is that this rational view of project management oversimplifies the processes at stake, particularly for innovative projects and for megaprojects with their inbuilt unforeseeability (because of long timeframes and stakeholder complexity). Moreover, this leads, as argued by Lenfle and Loch, to misinterpretations of the success factors of these projects. For example, Apollo is remembered in the project literature for the setting up of a complex project management system organized around a phased approach (Seamans 2005; Johnson 2002). While this unquestionably contributed to getting back on track during the project crisis of 1962–​63, this narrow view neglects the upstream exploratory work and the fact that the phased approach was implemented quite late in the project. However, the fact is that this control-​oriented approach of project management remains dominant today.

2.3  The Limitations of the Breakthrough Project Management Styles of the 1950s Based on the previous discussion, we might ask the question whether the issue is to “get some of the capability of the 1940s and 1950s back.” But this, we think, would be too

 

28    Sylvain Lenfle and Christoph Loch simple. Indeed, these projects unfolded in a very specific context and, therefore, were not exposed to the full spectrum of complications that face the megaprojects of today. One has to remember that, for all these projects, the context was the highest level of national urgency either because of World War II (Manhattan) or the Cold War with the USSR (Atlas, Polaris, and Apollo). This had two major consequences. First, the project goals reflected the military nature of the missions and were, in a sense, “simple” (although technically impressive): build a nuclear bomb, build a missile that can hit a small target from a long distance, start the missile from a submarine, or go to the moon.2 These do not reflect the goal complexity of projects that, today, inevitably have a societal component. Second, the Cold War and the competition with the Soviets led to the suppression of any debate around the projects. It is useful here to remember John F. Kennedy’s address to the Congress that formally launched the Moon project: If we are to win the battle that is going on around the world between freedom and tyranny, if we are to win the battle for men’s minds, the dramatic achievements in space which occurred in recent weeks should have made clear to us all, as did the Sputnik in 1957, the impact of this adventure on the minds of men everywhere who are attempting to make a determination of which road they should take. ( … ) We go into space because whatever mankind must undertake, free men must fully share. ( … ) I believe this Nation should commit itself to achieving the goal, before this decade is out, of landing a man on the moon and returning him safely to earth. No single space project in this period will be more impressive to mankind, or more important for the long-​range exploration of space; and none will be so difficult or expensive to accomplish. (Special Message to the Congress on Urgent National Needs, 25 May 1961)

Indeed, if the stakes were “the battle between freedom and tyranny,” there could be no debates around the project.3 In other words, if we rely on contemporary concepts, stakeholder disagreements were absent or small. There were no parties that stopped support, or protesters that blocked further work, because they no longer agreed with changed outcomes, or external groups that demanded transparency and accountability. This was also true for supplier management. These project teams had huge power over their suppliers—​again, these were military projects where suppliers were paid well but had to unquestioningly carry out orders. In fact, the entire organization was designed to avoid politics. As demonstrated by Hughes (1998) for Atlas, and Sapolsky (1972) for Polaris, the main goal of the creation of the WDD and the SPO was explicitly to avoid the bureaucratic fights and politicking that, traditionally, plagued large R&D projects. They were, in a sense, “closed” projects (Edwards 1996; Hughes 1998). Politics was reduced to the army and the government. There could be debates, but no protest outside likely to stop the project (Beard 1976). It was possible for Admiral Raborn to “build a fence to keep the rest of the Navy off of us” (Sapolsky 1972: 124) and to “engineer the politics of the program so as to provide resources without interference” (Spinardi 1994: 35–​6). Therefore, the question of stakeholder management was literally out of the scope.

 

Has Megaproject Management Lost Its Way?    29 This very specific context disappeared with the end of the Cold War and the emergence of a networked world—​it is no longer the case in megaprojects today. Now the challenge is to manage megaprojects in an “open” context in which no project team can hope to keep the outside world behind a fence. In this perspective, Hughes (1998) brilliantly demonstrates that the “system engineering” methods developed for military projects failed when confronted with civil megaprojects such as the famous Boston Central Artery Tunnel. Here, the challenge was to deal with the messy complexity of multiple stakeholders, each with different objectives and constraints. F. Salvucci, the Boston CA/​T key figure, had to patiently negotiate his way through the maze of the Boston area, discussing with engineers, community groups, the City, the State of Massachussets, and so on, around to-​be-​defined criteria, such as the design of a bridge. Therefore, as argued by Lundin et al. (2015: 201–​2), “The traditional view of the ‘project client’ as the single focal interlocutor of the project vanishes, giving place to a complex fuzzy system of diversified actors that has to be ‘managed’ in novel sophisticated governance and communication processes.” The problem is all the more important because, they argue, there is an ever-​growing demand of accountability for public and private megaprojects. General Groves never had to deal with this situation. In other words, we cannot simply go back to the heyday of 1950s project management—​what worked brilliantly then would be insufficient today. And yet, it is still worthwhile to repeat the lessons on uncertainty management from the 1950s, as some of the recent failed megaprojects simply violated what is known about uncertainty management. Moreover, knowledge on all three key drivers of megaproject failure has slowly accumulated over the last fifty years, not only on uncertainty management but also on stakeholder and contractor management. We will review the key lessons of this knowledge history in Section 2.4.

2.4  Lessons and Recommendations 2.4.1 Managing Uncertainty Building on the work from the 1940s described earlier, project management theory has, since the stage-​gate process became dominant, been able to articulate that many projects are characterized by variation (many small influences causing a possible range of duration and costs on a particular activity), which can be addressed by buffers, and foreseeable uncertainty or risk (identifiable and understood influences that the project team cannot be sure will occur, so different outcomes are possible), which can be addressed by planned and “programmed” risk management that “triggers” contingent actions depending on which risks occur (De Meyer et al. 2002). However, megaprojects suffer also from unforeseen uncertainty, which cannot be identified during project planning. The team either is unaware of the event’s possibility or cannot create the contingencies. Unforeseeable uncertainty may be caused by large “unthinkable” events,

 

30    Sylvain Lenfle and Christoph Loch or by many influences (including stakeholder actions) that interact through complexity. Unforeseeable uncertainty requires more flexible and “emergent” approaches than smaller uncertainty levels do (and than the stage-​gate process has allowed for). Still, the presence of unforeseeable uncertainty can be diagnosed. For example, discovery-​driven planning (McGrath and MacMillan 1995, 2000) proposes to explicitly acknowledge that unknown unknowns exist and to uncover them with analyses such as assumptions checklists. Similarly, Loch et al. (2008) illustrated with the example of a start-​up venture project, how the presence of unknown influences can be diagnosed by systematically probing for knowledge gaps in the project, building intuition about areas where unknown events may be looming. Two fundamental approaches exist for this level of unforeseeable uncertainty: trial-​and-​error learning and selectionism (Leonard-​ Barton 1995; Pich et al. 2002; Loch et al. 2006). Under trial-​and-​error learning, the team starts moving toward one outcome (the best it can identify), but is prepared to repeatedly and fundamentally change both the outcome and the course of action as new information becomes available. Exploratory experiments, aimed at gaining information without necessarily contributing “progress,” are an important part of this approach; failure of such experiments is a source of learning rather than a mistake. It is therefore important to track the learning and reduction in knowledge gaps rather than tracking only the progress toward a target. Well-​known examples are pharmaceutical development projects, in which promising indications often emerge during large scale trials via unexpected (positive) side effects. Alternatively, the team might choose to “hedge” and opt for selectionism, or pursuing multiple approaches in parallel, observing what works and what does not work (without necessarily having a full explanation why) and choosing the best approach ex post facto. Examples of this approach abound, including Microsoft’s pursuit of several operating systems during the 1980s (Beinhocker 1999), or “product churning” by the Japanese consumer electronics companies in the early 1990s (Stalk and Webber 1993). In a large-​scale empirical study of sixty-​five new venture projects, Sommer et  al. (2009) showed that the best combination of learning and selectionism, as measured by their effect on project success, depends on the level of unforeseeable uncertainty in the project and the complexity of the project (Figure 2.1). When both uncertainty and complexity are low (lower left quadrant), planning and standard risk management are up to the task and the most efficient. When unforeseeable uncertainty looms large, be flexible and apply trial and error. When complexity is high, use parallel trials and narrow the field down to the best as soon as possible. The hardest situation is in the upper right quadrant, which is where megaprojects usually find themselves and where unforeseeable uncertainty and project complexity combine. It turned out that the highest success level was associated with parallel trials if they could be kept alive until uncertainty had been reduced to the point that all important risks were known. Otherwise, trial and error performed better. Of course, in any large project, trial and error and selectionism can be combined and applied differently across subprojects. The largest challenge lies in the managerial structures and control-​mindedness in large corporations, partially prompted by the stage-​gate process revolution of the 1960s,

 

Has Megaproject Management Lost Its Way?    31 Complexity Low

Unforeseeable uncertainty

Learning Flexibility to fundamentally High re-define business plan and venture model Planning • Execute plan toward target Low • Risk identification and risk management • Learning and updating

High Selectionism Selectionism is most effective if choice of best trial can be deferred until unk unks have emerged (true market response is known) Selectionism • Plan as much as possible • Try out several alternative solutions and choose the best as soon as possible

Figure 2.1  When to choose trial-​and-​error-​learning or selectionism. (From Sommer et al. 2009.)

discussed previously. It makes it very difficult for managers in large organizations to take on risks. For example, one study on “breakthrough innovation” in large companies shows that they use a stage-​gate-​like approach to selecting and executing large innovations, which pushes managers to conservativism and early termination of risky projects (He 2015). Similarly, Sehti and Iqbal (2008) demonstrated that the stage-​gate process leads to project inflexibility, which, for innovative projects, is synonymous with failure. Even more fundamentally, the stage-​gate process has shaped an “aesthetic” of eliminating uncertainty and experimentation through rigid up-​front planning and control. For example, a study of relationships between startups and investors found that investors reacted with “punishment” (that is, by enforcing business reviews) to evidence of parallel trials and (to a lesser degree) trial-​and-​error iterations (Loch et al. 2011). Managers are, in principle, fully capable of intelligently responding to unforeseeable uncertainty, as R&D management and many experienced project management organizations amply demonstrate. However, much education is needed in order to equip management in many (particularly public) organizations, investors, and critically, the public with the flexibility required to deal with uncertainty.

2.4.2 Stakeholder Management and Project Governance No universally agreed “national agenda” exists any longer, based on which the brilliant projects in the 1950s could successfully proceed, because megaprojects touch on too many interests and agendas to still be able to be pushed by any central will. Consultation and involvement of powerful interested parties has become a must. On the other hand, political compromises do not make good bases for decisions, and muddled goals and inconsistent decisions based on fluctuating agreements destroy projects. How can these two imperatives be reconciled? This is a question of project governance.

 

32    Sylvain Lenfle and Christoph Loch Project teams execute, but the scope and strategic positioning of a project is set at the level of project governance, typically at the level of the “steering committee” (SC). Loch et al. (2015) examined effective and non-​effective SC practices in seventeen complex and uncertain projects (innovation, as well as organizational change), and found that the SC is the place where representation of interests (including consultation) needs to be combined with the production of a shared project vision and the translation of this vision into operational plans—​in order to effectively identify conflicts and solutions as the environment of the project changes. Several specific principles arise from the study: • Stakeholder representation:  the SC needs to represent the most important and powerful parties that have an interest in the megaproject (such as government, suppliers, or customers). At the same time, the size of the SC must not grow too large (by allowing “anyone with interest to participate”) because large groups become too difficult to manage and keep together. • Goal agreement. The SC has the critical responsibility to articulate a project vision that is at least acceptable to all parties, and then translate it into operational goals and targets that expose key conflicts. “Motherhood and apple pie” goals regularly get thrown out during later operational phases when conflicts inevitably do occur. Only if the conflicts are negotiated at the outset (in a way that maintains a shared project vision) can the goals evolve and change in negotiated ways that allow maintaining a shared vision. • Staying informed and renegotiating during crises. The SC must invest enough time and effort to understand the key issues of the project (insisting on translation of technical language and issues into the strategic policy or business language that is needed to maintain the strategic positioning of the project). The SC must also invest the time and effort to stay informed, so when changes and crises occur (both inevitable over the time horizon of megaprojects), project modifications can be renegotiated in ways so that the parties maintain their agreement/​ support. If a party feels excluded or taken advantage of, projects fail, but if the SC can successfully manage one crisis together, it becomes stronger in managing the next. • Keeping the project team aligned. The SC must maintain a position of control, which means in this context, understanding the key issues rather than maintaining and enforcing (“come what may”) an initial project plan. Trust needs to be built with the project team that bad news and changes are treated reasonably, demanding solutions and accountability, but not looking for scapegoats to punish—​otherwise, information about the true status of the project will not be forthcoming. This is necessary because changes will happen in a megaproject, and the SC needs to set up itself, as well as its project team, to be able to address these changes in ways that do not lead to the typical symptoms of megaproject disasters—​such as mission creep, late mission changes because of political maneuvering, accumulated unaddressed problems, or the falling out with an important stakeholder.

 

Has Megaproject Management Lost Its Way?    33 Several key challenges exist that make these principles difficult to achieve. Interest conflicts and differences in thinking styles among stakeholders make the achievement of true alignment a long affair (leading to longer planning times) and consume significant managerial effort during a project. The temptations are ever present to not invest enough effort, or to exploit political circumstances of unbalanced power to one’s own advantage. This is also where the widely observed temptation of “low-​balling early [on costs] and then present a fait-​accompli to the stakeholders” (Flyvbjerg 2007) comes in. While this is certainly true in some cases, it is not inevitable. Evidence in Loch et al. (2015) suggests that if the SC represents stakeholders and seeks the dialog with them, and if it is sufficiently involved with the project team to be able to follow and evaluate progress, success overestimation can be avoided. Of course, this leaves out situations where a skeptical public (or political establishment) is simply not willing to accept a project under a realistic scenario, and the only way to get the project approved is by “lying” about it. But whoever engages in misrepresentations in order to get the project started (“they will learn and change their minds later”) is running severe risks both for their own careers, as the project later runs into difficulties preprogrammed by the unrealistic initial estimates, and for the public, whose faith in project execution capabilities becomes undermined. Yes, it may be true that (for example) the Eurotunnel was a significant macro-​economic success in hindsight, connecting London and Paris in ways that were previously unthinkable. But on the way there, many shareholders lost their money, and careers of good people involved were damaged, and so initial overpromising is perilous and not advisable, even if one might be able to construct a long-​term justification for it.

2.4.3 Contractor Management Contracts are core vehicles of governing partners and the subcontractors of pieces of work in projects, and they form a complex web of relationships in megaprojects. But contracts can handle only limited complexity (a contract can quickly run into thousands of pages, which means they become ineffective), and they are inflexible where flexibility is required to deal with the inevitable changes in megaprojects. A contract is a dangerous instrument and should always be approached with trepidation and caution … Theoretically, the aim of a written contract is to achieve certainty of obligation of each party, the avoidance of ambiguities, and such definiteness of understanding as to preclude ultimate controversy. In practice, construction contracts are generally formed not to definitely fix obligations, but to avoid obligations. (MacDonald and Evans 1998: 1–​2)

Specifically, contracts cause the temptation to explore gaps in the understanding of the counterparty to create obligations that one can then exploit—​a fallacious expectation because the other side usually finds a way to sooner or later stall in their turn or to

 

34    Sylvain Lenfle and Christoph Loch retaliate (von Branconi and Loch 2004). The well-​known temptation to “bid low and sue later” falls in this context, but it often leads to protracted business and legal battles, victimizing the project. Much evidence has been accumulated that contracts need to be designed with flexibility, and they need to be complemented with relationships. A good example is the celebrated Heathrow Terminal 5 project, which applied an integrated approach that incorporated careful strategic governance (accomplishing system integration) within diligent process management that included supplier selection by track record (rather than the lowest bid price) and flexible contracts that rewarded problem solving (Davies et al. 2009b). The project owner BAA “changed the rules of the game” by creating a new type of agreement based on two fundamental principles: the client bears the risk and works collaboratively with contractors in integrated project teams. BAA had to take responsibility for risks and uncertainties, while creating an environment within which suppliers could find solutions. Suppliers were repaid all the costs on a cost-​transparent “open book” basis and incentivized to improve their performance and innovate by bonuses for exceeding previously agreed “target costs” and completion dates. If the performance of a project exceeds target costs, the profits are shared among team members. This contractual approach was underpinned by routines to expose and manage risks rather than transfer or bury them, and offered incentives for innovation and problem solving (Davies et al. 2009a: 24–​5). The Heathrow Terminal 5 project addressed one fundamental problem with contracts: they cannot specify all desired outcomes beforehand in the complex and uncertain environment of a megaproject, and fixing any outcomes (no matter with how many “contingencies) opens up incentive conflicts when contractors either cannot deliver or can deliver in unforeseen ways. The cost-​reimbursement contracts with “innovation bonuses” offered a way out of this dilemma. But it is possible to go even further in turning contracts from fixed outcome descriptions into vehicles for collaborative problem solving. One example for this is the OSA Alliance between Orange (France Telecom’s mobile telephone arm) with its partners in managing roaming, the complicated agreements that allow regional telecom operators to provide service for a customer from other regions and be reimbursed by the telecom operator who has a contract with the customer and charges this customer for the roaming (Van Der Heyden et al. 2006). The “contract” that partner operators in the alliance signed up for did not specify any specific collaboration procedures or outcomes, but was nothing but a specification of a collaborative problem solving procedure: how would the group make decisions in setting up a technical system, or a customer agreement, or a revenue sharing when it arose. Decisions were indeed made by voting, with safeguards that neither the large operators (with a revenue majority) nor the many small operators (with most votes) could force through agreements. Each specific agreement itself (what would normally be seen as a contract) became a mere technical description. This structure of agreements allowed the partners to keep collaborating flexibly and robustly in an environment of changing technologies and regulatory regimes. (The regulatory bodies tightened rules on roaming which had become very profitable.) However, when we discuss such collaboration structures with

 

Has Megaproject Management Lost Its Way?    35 project and program managers, they usually are very uncomfortable because it feels to them like a “loss of control.” This is another example of the control “aesthetics” that the dominance of the stage-​gate process has created in project management. And yet there are again large challenges in adopting these new methods that would allow addressing the systematic problems that have plagued megaprojects. The temptation to use “market forces” to depress prices to contractors, using unbalanced power to get one’s way (if only for a short period), is ever present. As a case in point, the Heathrow Terminal 5 owner BAA was acquired in 2006 and, “in a complete reversal of strategy (and to the surprise of many in the UK construction industry) decided to revert back to the traditional role of client as procurer rather than project manager, relying on ‘risk-​shifting contracts,’ detailed up-​front specifications and inflexible routines” (Davies et al. 2016). Similarly, the authors have discussed the OSA “framework contract” approach with managers from many companies, and have witnessed directly how deeply threatening managers find such an approach—​it feels to them as if they are giving away control over their own fate. Yet another cultural and “aesthetic” influence that has been connected to the stage-​gate process, which adds a specific definition of “professional standards” to the earlier-​mentioned short-​term temptations in making it very difficult to make the new methods in megaproject management enter the mainstream.

2.5 Conclusion System engineering and technical complexity are well understood, but uncertainty and stakeholder complexity are still the big challenges for megaprojects. Avenues have been identified to address these challenges that require behavioral changes:  these include resisting the temptation to press one’s own advantage with contractors; accepting some loss of predictability and control; patience in bringing the multiple sides to the table that are always present in megaprojects; and the discipline to maintain a common direction that allows progress-​directed decision making rather than merely conflict-​avoiding compromises. Many of these techniques will require companies to learn new and potentially daunting behavior; but in fact many of these managerial mechanisms are tried and true techniques that worked wonders for megaprojects a few generations ago and could help point the way to a brighter future for huge projects in the future.

Notes 1. McNamara’s thinking was rooted in, and had a major impact on, “cold war rationality”—​the belief that one could find the optimal solution beforehand. Here, the reader may refer to Erickson et al. (2013). 2. Apollo is an ambiguous case, since it was a civil project largely managed by the military after 1963.

 

36    Sylvain Lenfle and Christoph Loch 3. On the Manhattan Project, there was no debate simply because it was a “black,” completely secret, project. Even Harry Truman, Roosevelt’s Vice-​President, ignored the existence of the project until he became President in April 1945.

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Has Megaproject Management Lost Its Way?    37 He, X. (2016). Breakthrough Innovation in Large Companies. PhD dissertation, Cambridge University Department of Engineering. Hughes, T. (1998). Rescuing Prometheus. New York: Vintage Books. Johnson, S. (2000). “From concurrency to phased planning:  An episode in the history of systems management,” in A. Hughes and T. Hughes, Systems, Experts and Computers: The Systems Approach to Management and Engineering, World War II and After. Cambridge, MA: MIT Press, pp. 93–​112. Johnson, S. (2002). The Secret of Apollo: Systems Management in American and European Space Programs. Baltimore, MD: John Hopkins University Press. Kammholz, K. (2015). “Bericht rügt Deutschlands Vresagen als Bauherr,” Die Welt, 29(6): Section Politik. Klein, B. and Meckling, W. (1958). “Application of operations research to development decisions,” Operations Research, 6(3): 352–​63. Kostka, G. (2015). Grossprojekte in Deutschland-​zwischen Ambition und Realität. Study of the Hertie School of Governance. Kriel, L. and Dowsett, S. (2014). “Insight: Lowball bid comes back to haunt Panama Canal expansion,” Reuters World, 20 January. Lenfle, S. (2011). “The strategy of parallel approaches in projects with unforeseeable uncertainty:  The Manhattan case in retrospect,” International Journal of Project Management, 29(4): 359–​73. Lenfle, S. and Loch, C. H. (2010). “Lost roots: How project management came to emphasize control over flexibility and novelty,” California Management Review, 53(1): 32–​55. Leonard-​Barton, D. (1995). Wellsprings of Knowledge.Cambridge, MA: HBS Press. Loch, C. H., Pich, M. T., and De Meyer, A. (2006). Managing the Unknown: A New Approach to Managing Projects Under High Uncertainty. Hoboken, NJ: Wiley. Loch, C. H., Solt, M. E., and Bailey, E. (2008). “Diagnosing unforeseeable uncertainty in a new venture,” Journal of Product Innovation Management, 25(1): 28–​46. Loch, C. H., Sommer, S. C., Dong, J., Jokela, P., and Pich, M. T. (2011). “Managing risk and responding to uncertainty: How entrepreneurs and VCs can improve their effectiveness; a comparison of three countries,” INSEAD Working Paper. Loch, C. H., Sommer, S., and Mähring, M. (2015). “What project steering committees actually do: A framework for effective project governance,” Working Paper, Cambridge Judge Business School/​HEC Paris/​Stockholm School of Economics. Loch, C. H. and Terwiesch, C. (2002). The Circored Project A, B and C. INSEAD Case Study. Lundin, R., Arvidsson, N., Brady, T., Ekstedt, E., Midler, C., and Sydow, J. (2015). Managing and Working in Project Society:  Institutional Challenges of Temporary Organizations. Cambridge: Cambridge University Press. McGrath, R. C. and MacMillan, I. (2000). The Entrepreneurial Mindset: Strategies for Continuously Creating Opportunity in the Age of Uncertainty. Cambridge, MA: Harvard Business Publishing. McDonald, D. F. and Evans III, J. O. (1998). “Construction contracts: Shifting risk or generating a claim?” AACE International Transactions, LEG.01: 1–​8. McGrath, R. and McMillan, I. (1995). “Discovery-driven planning,” Harvard Business Review, (July–August): 44–54. Pich, M. T., Loch, C. H., and De Meyer, A. (2002). “On uncertainty, ambiguity and complexity in project management,” Management Science, 48(8): 1008–​23.

 

38    Sylvain Lenfle and Christoph Loch Sapolsky, H. (1972). The Polaris System Development. Cambridge, MA:  Harvard University Press. Sapolsky, H. (2003). “Inventing systems integration,” in A. Prencipe, A. Davies, and M. Hobday, The Business of Systems Integration. Oxford: Oxford University Press, pp. 15–​34. Seamans, R. (2005). “Project Apollo: The tough decisions,” Monographs in Aerospace History Number 37. Washington DC: NASA History Division. Sehti, R. and Iqbal, Z. (2008). “Stage-​gate controls, learning failure, and adverse effects on novel new products,” Journal of Marketing, 72(1): 118–​34. Sommer, S. C., Loch, C. H., and Dong, J. (2009). “Managing complexity and unforeseeable uncertainty in startup companies: An empirical study,” Organization Science, 20(1): 118–​33. Snyder, J. (1987). “Modern project management: How did we get there – Where do we go?” Project Management Journal, 18(1): 28–9. Spinardi, G. (1994). From Polaris to Trident:  The Development of US Fleet Ballistic Missile Technology. Cambridge: Cambridge University Press. Stalk, G. and Webber, A. M. (1993). “Japan’s dark side of time,” Harvard Business Review, 71(4): 93–102. Taylor, S. (2016). The Fall and Rise of Nuclear Power in Britain. Cambridge: UIT Cambridge. Van Der Heyden, L., Doz, Y., and Vankatraman, V. (2006). Orange Group’s Open Seamless Alliance (OSA). INSEAD Case Study. Vazsonyi, A. (1970). “L’histoire de Grandeur et de la Décadence de la Methode PERT,” Management Science, 16(8): B449–55. von Branconi, C. and Loch, C. H. (2004). “Contracting for major projects: Eight business levers for top management,” International Journal of Project Management, 22(2): 119–​30. World Nuclear Association. (2015). “Nuclear power in Finland: Country profiles,” 13 August, .

 

Chapter 3

Cycles in M eg a proj e c t Devel op me nt Matti Siemiatycki

3.1 Introduction Infrastructure megaprojects are an enduring feature of human civilizations. Throughout the world, the landscape is marked by the remnants of historic efforts to undertake construction initiatives on a massive scale, from the Egyptian pyramids to the Roman aqueducts, roads, and Coliseum, to the Greek Parthenon. While large-​scale public works have been significant throughout history, it was with industrialization that megaprojects rose to prominence, as a strategic investment in productive capital and as ideology (Lehrer and Laidley 2008: 788). Today there are many different types of megaprojects, including immense transportation, energy, healthcare, office tower, justice, telecommunications, cultural, and information technology infrastructures that support the functioning of a modern society. Megaprojects are defined by their large scale in terms of costs, which can range from $100 million to upwards of $1 billion, depending on the context in which they are being developed. They can be funded, built, and operated by public-​sector, as well as ­private-​ sector institutions or some combination of the two. Megaprojects are also defined in terms of the scale of planning and engineering complexity, the high level of public and political interest that they attract, and their outsized impact on the surrounding economic, social, and natural environment. Indeed, megaprojects are identified as the ­largest-​scale infrastructure and development projects that a given society undertakes, which attract the greatest amount of public interest, and have the most significant impacts and externalities on their surrounding communities. One of the more puzzling aspects of megaprojects is that they tend to follow distinctive cycles or waves of innovation. It is quite common for the development of a new technology or type of infrastructure megaproject in one place to spark a wave of similar projects developed in a variety of other locations, before they are usurped by a

 

40   Matti Siemiatycki subsequent wave of development of a new technology in the same asset class or a different type of infrastructure altogether. Put differently, new technologies or types of megaprojects appear to diffuse across space, from the place where an innovative idea emerges, through to a surge in popularity in many locations, before it declines in popularity either because the project type does not function as expected, has fulfilled the required goal, or has been replaced by a new technology that provides even better benefits. To date, such patterns have often been identified and dismissed as one-​off fads capturing the economic imperative or cultural zeitgeist of a specific moment in time. For instance, the “Bilbao effect” is a popular term to explain how the development of a new Guggenheim Museum with an iconic building design in the northern Spanish city in the late 1990s sparked a tidal wave of museum and cultural-​institution developments around the world. And scholars have identified a dramatic recent upswing in the development of urban tram or streetcar systems globally, which reimagine the streetcars that were pervasive in the early 1900s but removed from most city streets because they were seen as outdated and inefficient. Yet a closer examination across a wide range of infrastructure asset types and time periods suggests that there is consistency in this wave-​ like pattern in the development of specific types of infrastructure, over fairly brief time periods. New infrastructure megaproject technologies often rise on the ashes of previous innovations, are developed in punctuated bunches, and then recede in popularity as they are superseded by the next big thing. How pervasive are these cycles or waves of megaproject development? How do we explain the transfer of megaproject ideas and development from place to place? And how can this insight inform the decisions of infrastructure project planners, policy makers, and investors? It is these questions that are the focus of this chapter. But first, it is necessary to briefly examine where new ideas come from, and how they spread over time.

3.2  Riding the Wave The cyclical nature of innovation development and diffusion is a topic of great interest for academics, policy makers, business leaders, and the general public. Over the years, extensive attention has been paid to documenting cycles in the way that new fashion styles, music, technologies, public policies, business management strategy, and nutrition emerge and spread. An important insight into the cyclical development of innovative new ideas or products is that they tend to follow a consistent “natural history” through different identifiable stages—​most succinctly defined by Best (2006:  21)  as “emerging, surging, and purging.” This natural history is characterized by a standard “S” innovation curve, which is often depicted in a wave-​like pattern to denote that a new innovation typically builds on the foundation of a previous product or idea that has run its course or is being improved upon (Figure 3.1).

 

Cycles in Megaproject Development    41

ADOPTION OF INNOVATION

Maturity is reached, leading to slowdown or declining adoption

Adoption of innovation surges

Early adopters take up innovation

New innovation emerges, often adapting previous technologies; this starts a new innovation adoption cycle

A new innovation is developed

TIME

Figure 3.1  S-​curve of innovation adoption.

To date, there has been limited examination of whether cycles of innovation diffusion may be an enduring part of the megaproject development process. However, when patterns of megaproject development are viewed at a global scale and tracked historically over time, it is clear that such dynamics are not just present, but are a driving force in determining which projects get built, where, and when. Table 3.1 provides an overview of seven types of megaproject dating back to the turn of the nineteenth century that have each displayed a similar emerge–​surge–​purge pattern in the way that they were developed, gained widespread adoption, and then subsequently declined in application. The following sections draw on illustrative examples of different types of megaproject to show the dynamics of infrastructure development cycles.

3.2.1 Riding the Wave, Again and Again The century-​long development of baseball stadiums in North America highlights the wave-​like pattern of megaproject innovation. Baseball stadiums have been an enduring feature of the American landscape. However, the preferred design of these stadiums shifted abruptly when an innovator came along. As shown in Figure 3.2, baseball

 

Table 3.1 Selected waves of innovation in urban development, 1890–​2007 Date

Description

Antecedents

Trendsetters

Surge

Decline

1890–​1920

Electric tramways and streetcars

Animal-​pulled omni-​carts and trams in New York and New Orleans

Berlin electric demonstration tram in 1881

By the turn of the twentieth century, electrified trams were a common feature of the urban environment in cities on all six continents

Advances in bus and car technologies and spread of cities made trams less efficient, and they were removed from most cities by the 1960s

1900–​1910

American city beautiful movement (redevelopment of city centers and parks using monumental designs)

Baron Haussmann’s nineteenth-​ century redevelopment of Paris

Chicago 1893 “White City” Fair Grounds; Washington Mall redevelopment plan

City beautiful initiatives in Denver, New York, Seattle, Baltimore, Harrisburg, Philadelphia, and Chicago

Opposition to large expenses on urban aesthetics led to an increased emphasis on functionality of investments

1910–​1935

Construction of American British imperial city beautiful capitals using movement city beautiful techniques

Edwin Lutyens and Herbert Baker’s design of New Delhi, begun in 1912

Imperial capitals initiatives in Lusaka, Salisbury (Harare), Nairobi, and Kampala

Beginning of decline of the British Empire, leading to independence following World War II

1935–​1960

High-​rise, single-​use public housing megaprojects

Garden City; European Modernist movement, Le Corbusier

First Homes, New York City; Cabrini Green, Chicago; Boundary Estate, London; Stockholm Exhibition

St Louis, Chicago, Boston, Toronto, Birmingham, Paris, Stockholm, New Orleans, Glasgow, Sheffield, Atlanta, Detroit, Melbourne, and Sydney

Demolition of award-​winning Pruitt-​Igoe in St Louis sixteen years after it opened symbolized the failure of large housing projects; they have subsequently been demolished in many cities

1955–​1970

Regional transportation planning and urban freeway construction

City beautiful movement, suburbanization following the end of World War II

Chicago Area Transport Study, 1955, which used regional traffic and economic modeling to emphasize new highway developments

Washington, Baltimore, Pittsburgh, Hartford, Philadelphia, San Francisco, Toronto, and Vancouver

High-​profile protests opposing freeways in New York, led by urbanist Jane Jacobs, which spurred similar protests in other cities such as Toronto, San Francisco, and Vancouver (continued)

 

Cycles in Megaproject Development    43 Table 3.1 Continued Date

Description

Antecedents

Trendsetters

Surge

Decline

1980–​ current

Light rail lines (adaptation of trams, either running on-​street or on dedicated rights of way)

Nineteenth-​ century tramways; new urbanism emphasis on transit-oriented development

Rebranding and redesign of old trams as modern light rail in late 1970s: Gothenburg, San Francisco, Edmonton, and Portland

Between 1980 n/​a and 2000, more than sixty-​five new light rail lines were constructed in cities around the world, and the construction of light rail lines continues to the present

1997–​ current

Iconic museums and cultural-​ led urban regeneration

City beautiful movement; Frank Lloyd Wright’s 1959 Guggenheim Museum, New York

Bilbao Guggenheim New York, London, n/​a Museum, designed Washington, by Frank Gehry Berlin, Milwaukee, Houston, Sheffield, and Hull

Source: Siemiatycki (2013).

stadium design has changed from the classic era of downtown brick, concrete, and steel stadiums with natural grass fields, to the modern period of large suburban municipal fields that were multipurpose and had artificial turf playing fields, to a more recent wave of “retro” ballparks that were located in downtown locations and reimagined the classic stadium design aesthetic. The opening of the retro Camden Yards in Baltimore in 1992 sparked the most recent innovation wave of building retro baseball stadiums. Since that date, twenty-​three of thirty teams have built new stadiums using the retro design style, meaning that this current wave of innovation has nearly reached its saturation point. Many of the current wave of retro ballpark projects cost hundreds of millions of dollars or even more than $1 billion as they incorporated increasingly complex features such as retractable roofs, and received public subsidies which were approved by both Democratic and Republican governments. In a number of instances, projects seeking to emulate the Camden Yards experience had large cost overruns and have failed to deliver on forecasted benefits in terms of economic development, local urban regeneration, or long-​term increases in fan attendance. Nevertheless, Figure 3.2 shows the power of a wave of innovation across history: once a new ballpark design standard became in vogue, every single subsequent ballpark to be constructed over the subsequent two decades followed that style of design. Intriguingly, this wave of retro stadium design at the turn of the twenty-​first century has not extended beyond North American baseball parks. Globally, modern architecture and design has been the most common aesthetic for new stadiums constructed

 

44   Matti Siemiatycki 16

Number of stadiums opened

14 12 10

Retro Modern

8

Pre-Classic Classic

6 4 2

18 60 s 18 70 s 18 80 s 18 90 s 19 00 s 19 10 s 19 20 s 19 30 s 19 40 s 19 50 s 19 60 s 19 70 s 19 80 s 19 90 s 20 00 s

0

Decade

Figure 3.2  Number and type of Major League baseball stadiums constructed, 1860–​2010. (Source: http://​www.ballparksofbaseball.com.)

during this period, even when they are designed by the same global architecture and design firms that worked on the retro baseball parks in North America. This suggest that the confluence of factors that has driven the retro stadium trend is particular to North America (and perhaps even more specifically baseball in America), and may be rooted in national economic and cultural conditions that are not necessarily transferrable elsewhere or to other sports.

3.2.2 Innovation Cycles Transcend Political Systems The case of urban tram or streetcar systems provides an example of the diffusion of a technological innovation around the world to jurisdictions that have vastly different political systems, governance structures, and urban forms. This showcases how a single technology can serve to address a common global challenge, in this case the demand for mass urban mobility, in vastly different places. It also demonstrates the importance of symbolic messages. During a two-​decade period at the turn of the twentieth century, urban trams were built in cities on five continents, including New York and Chicago (strong mayor, federalist democracy), Toronto (weak mayor, federalist democracy), London (unitary democracy with strong involvement of the national government in urban policy), Budapest and Sarajevo (Austro-​Hungarian Empire), Calcutta and Alexandria (British rule of India and Egypt, respectively), and Rio de Janeiro (Portuguese colonial rule of Brazil). This rapid spread of trams was followed by the widespread abandonment of the technology in the mid-​twentieth century. Streetcars were removed from the streets

 

Cycles in Megaproject Development    45 of almost every city in the world as they became increasingly unprofitable, viewed as part of the old urban order, and an impediment to the modern free flow of the private automobile. In the United States, the demise of streetcars was expedited by competition from urban buses, which was exacerbated by a conspiracy on the part of National City Lines corporation and its backers General Motors, Standard Oil, and Firestone Tire to create a bus monopoly in the urban transit industry (Mees 2010). In the past quarter century, however, there has been a resurgence in the popularity of trams. Rebranded as light rail, tram systems costing hundreds of millions or billions of dollars have been built in dozens of cities globally. These tram systems are commonly promoted as a strategy to provide sustainable urban mobility alternatives to the private automobile, spur urban regeneration and smart growth, and attract creative industries and workers. Many of these new tram systems have faced significant challenges with construction cost overruns, delays, low ridership, and mixed evidence about whether they actually deliver development and environmental benefits (Pickrell 1992; Flyvbjerg 2007). Yet the wave of development has persisted despite the withering critiques. Light rail lines have been ascribed with a set of powerful symbolic meanings that transcend their tangible benefits, connoting messages of sustainable development, visionary leadership, and pride of place. The successful communication of these symbolic messages has enhanced the public popularity of light rail technology and lengthened the duration of this wave of investment.

3.2.3 New Technology Meets a Global Market Super-​tall skyscrapers provide an example of a class of megaproject that has surged in popularity as technology has evolved and it has been transposed to an eager market around the globe. As of 2015, there are ninety-​two super-​tall skyscrapers worldwide that are over 300 meters high—​the common cutoff used to identify the tallest of the world’s tall buildings (Council on Tall Buildings and Urban Habitat 2015). As shown in Figure 3.3, super-​tall buildings are in the midst of a major surge of development. In the five years from 2010 to 2015, more super-​tall buildings opened worldwide than in the previous eighty years, from the time that the first one was inaugurated. And super-​tall buildings are growing taller than ever: between 1930 and 2000 the world’s tallest building grew by 133 meters to 452 meters; and since 2000, the tallest building in the world grew by a further 377 meters to 828 meters. A closer examination of super-​tall buildings illustrates how the confluence of technological, geographic, and economic factors has supported the boom in their development. In their initial incarnation, super-​tall skyscrapers were exclusively an American phenomenon. The first eight buildings over 300 meters tall were built between 1930 and 1989, and all were located in the United States. Until the 1980s, steel was the main structural material used, and super-​tall skyscrapers were used for office towers. Classic buildings like the Chrysler Building and the Empire State Building in New York, and the Sears Tower (now Willis Tower) and the John Hancock Center in Chicago, came to be iconic

 

46   Matti Siemiatycki 60

Number of buildings

50 40

South America Australia

30

Europe Asia

20

North America

10

19 30 –1 93 9 19 40 –1 94 9 19 50 –1 95 9 19 60 –1 96 9 19 70 –1 97 9 19 80 –1 98 9 19 90 –1 99 9 20 00 –2 00 9 20 10 –2 01 5

0

Year of completion

Figure 3.3  Global development of super-​tall skyscrapers. (From Council on Tall Buildings and Urban Habitat, 2015.)

features of their city skylines and important symbols of American engineering and business prowess. Thus while the technology existed to build super-​tall buildings as early as the 1930s, very few were actually constructed, and there was not a market outside the United States. The surge in super-​tall building construction that began in the 1980s and really picked up in the 2000s coincided with three trends. First, new construction techniques have been developed to build super-​tall buildings using concrete or composite structural materials. These materials allow the buildings to be built taller while maintaining a slender base, which makes them more economically viable, as there is not a very large podium that can be difficult to find tenants for. Innovative elevators have also been developed to move people more quickly through taller buildings. Second, super-​tall buildings are now widely used for luxury residential or hotel uses, creating an entirely new market for tall buildings alongside offices. Third, super-​tall buildings have become a global phenomenon, with the most rapid growth concentrated outside the United States in a handful of countries in East and Southeast Asia and the Middle East. In particular, the largest building boom has been in China and the Emirates of Dubai, which now are respectively home to 37% and 23% of all super-​tall buildings. In these countries, super-​ tall buildings with iconic architecture have become important symbols of ascending global power and status—​part of a luxury property-​led economic development model, and a form of city marketing and branding. As such, the twenty-​first-​century boom in super-​tall buildings globally reflects an adaptation of their American antecedents based on new building technologies and the construction of locally sensitive symbolic narratives in emerging markets.

 

Cycles in Megaproject Development    47

3.2.4 Failure to Launch Of course, not all new innovative technologies catch on and surge in popularity. One interesting question is what happens to new megaproject technologies or designs that run counter to a cycle of development? In cases where the type of infrastructure is targeted at a local user base and still provides benefit, it will continue to be operated. Monorails, for instance, a transit technology that was first developed in the nineteenth century, gained some level of popularity in Germany at the turn of the twentieth century and have been consistently touted by promoters as a solution to urban transit problems ever since. Yet with the exception of a few brief moments of interest and some application at amusement parks and airports, few monorails have been built as urban transit systems relative to other transit megaproject technologies. Those monorails that were built generally continue to operate and serve their local market, in places where they provide an effective transportation service. At a global scale, however, the monorail technology was widely surpassed in popularity by subways and light rail lines that became the urban rail technology of choice. In other cases, missing a wave of innovation can be far more costly for project owners. In the case of emblematic sports stadiums, architecturally significant cultural facilities, large convention centers, and upscale waterfront redevelopments, the success of a megaproject is dependent on providing services to a local and international user base in a competitive market. For this type of asset, a megaproject that runs counter to a global wave of innovation and becomes uncompetitive may have diminished value to its owners and users, and thus require costly refurbishment or even complete replacement far earlier than the end of its technical lifespan. The experience with North American baseball stadiums highlights this point, as the last of the modern stadiums built just before the retro Camden Yards opened have become obsolete very quickly. In Toronto and Tampa Bay, large and expensive modern domed stadiums were considered technological wonders that would make their jurisdictions professional sporting hotspots when they first opened in the late 1980s and early 1990s. They are now seen as impediments to attracting the best players to play for the team and fans to attend games, as they lack the comfort of grass playing fields and the ambiance of the retro ballpark designs. In each city, the outdated stadiums have challenged the quality of the team on the field and the financial viability of the organization. Both teams are now exploring costly options to retrofit or build new stadiums to replace ballparks that are barely a quarter century old and still fully functional.

3.2.5 South to North Innovation Waves Thus far, the examples provided have primarily showcased megaproject technologies that have diffused from the Global North to the Global South. This has been the predominant direction that the spread of new megaproject technologies have followed over the past two centuries. In the nineteenth century and early twentieth century,

 

48   Matti Siemiatycki European colonial systems provided a key channel through which new technologies were transferred from North to South. For instance, in Africa at the turn of the twentieth century, European empires undertook a punctuated burst of railway construction in their multiple colonies on the continent. This investment in infrastructure was meant to improve colonial command and control by enabling better exploitation of natural resources and improve connectivity into global flows of trade (Jedwab and Moradi 2012). More recently, international financial aid and technical assistance through multinational institutions such as the World Bank or national development agencies has been an important mechanism by which megaproject technologies and project funds have spread to the Global South. As the historic experience with North to South diffusion demonstrates, the adoption of new infrastructure megaprojects in the Global South has not always been voluntary. In some cases, colonial governments imposed the development of specific technologies; and more recently, bilateral aid or development agency funding has been made conditional on the development of specific types of megaproject. Many of these imposed megaprojects have had poor outcomes or exacerbated levels of social inequality in the host country. While considerably less frequent, there are instances where megaproject innovations in the Global South have gained prominence and surged globally. The most prominent example is perhaps the wave of bus rapid transit systems (BRT). The first city to develop a BRT system on a large scale was Curitiba, Brazil, which in 1974 implemented an extensive network of high-​capacity bus lines on fixed dedicated routes with high-​quality stations. BRT provided a lower-​cost, faster-​construction, and more flexible alternative to urban rail technology. With high ridership and relatively low costs, Curitiba’s bus rapid transit system inspired the implementation of similar projects across Brazil and parts of Latin America, and by a number of other cities in the Global North, including Ottawa and Pittsburgh. These projects grew in scale and became megaprojects costing hundreds of millions of dollars when the rights of way, stations, and vehicle costs were included. However, the technology never fully caught on at the time as a global wave, because there were concerns about capacity constraints for bus-​ based transit systems, and in many countries, buses had a reputation for being a mode of travel of last resort. Then, in 2000, Bogota opened its TransMilenio BRT system, which changed the global paradigm regarding BRT. At $240 million, or $5.9 million per km for the 41-​km first phase of the system, TransMilenio was far cheaper than a comparable metro system that was being considered at the time. Bogota’s BRT also included passing lanes at each station and express services—​innovations that altered perceptions about the capacity of BRT. And the boldly branded red articulated buses and modern station areas captured popular attention (UNDP 2012). In quick succession following the successful opening of the first TransMilenio BRT line, many other cities followed Bogota’s lead and implemented similar BRT systems. In the 2000s, dozens of major cities in the Global South, including Jakarta, Delhi, Guangzhou, Johannesburg, Tehran, Istanbul, and Mexico City implemented bus rapid transit services. Bogota’s experience also initiated a wave of BRT projects in North American and European cities.

 

Cycles in Megaproject Development    49 In addition to innovative infrastructure technologies emerging in the Global South and spreading further afield, new patterns of South–​South investing are spurring a wave of specific types of megaproject in developing countries. In particular, China has become a major infrastructure investor and builder of African infrastructure megaprojects. For African countries where the stock of infrastructure lags well behind the global norm, outside investment in infrastructure provides an opportunity to broaden their economic base. Meanwhile, for China, infrastructure investing in Africa is part of a strategic initiative to develop closer political ties and secure access to natural resources. This has led to a wave of major road and railway building, port construction, and energy projects across Africa that are financed and built by Chinese firms or state-​owned enterprises. To date, more than thirty-​five African countries are engaging with China for infrastructure deals, the largest being in Nigeria, Angola, Sudan, and Ethiopia. Following the Chinese lead, Brazil, India, and some Gulf States have also turned their interest to infrastructure investing in developing countries, particularly in their own local regions, thereby furthering the wave of megaproject construction in developing countries (Foster et al. 2008). As such, the pattern of South–​South investing is not so much about the diffusion of a new technology, but rather in providing the financing, construction expertise, and motivation to initiate a surge in projects being built in places where infrastructure has tended not to be constructed previously.

3.2.6 Ending a Cycle The case of nuclear power plant construction illustrates how abruptly a wave of innovation can be halted in the face of changing views on the effectiveness of technology and public concerns about safety. The construction of multi-​billion-​dollar nuclear power plants rode a wave of development in the 1970s and 1980s, with many projects built in both Western democracies and Eastern communist countries (Figure 3.4). These projects met ever-​increasing global demand for power. Yet a confluence of factors contributed to a precipitous decline in new nuclear power plant development in the 1990s and 2000s, with relatively few new plants built in developed countries, and China being the primary market experiencing a mini-​boom in reactor development. Accidents in close succession at Three Mile Island and Chernobyl and later Fukushima raised global concern about the safety of nuclear power plants, and highlighted worries about the risks of both the production of nuclear power and the radioactive waste disposal process. Nuclear power plants had become widely known for major construction cost overruns and delays. And the promise of scaling up renewable power sources provided the glimmer of the possibility of a viable alternative energy source. While there has been a decline in the construction of new nuclear power plants, this has not led to a wholesale purging or shuttering of existing facilities. Most nuclear power plants constructed during the surge of popularity remain operational and provide an important source of electricity. Nuclear power accounts for around 12% of electricity produced globally, with thirteen countries deriving more than a third of their power

 

50   Matti Siemiatycki 120 Three Mile Island Chernobyl 100

80 Developed country 60

Developing country

40

20

19 50 –1 95 19 4 55 –1 95 19 9 60 –1 96 19 4 65 –1 96 19 9 70 –1 97 19 4 75 –1 97 19 9 80 –1 98 19 4 85 –1 98 19 9 90 –1 99 19 4 95 –1 99 20 9 00 –2 00 20 4 05 –2 00 20 9 10 –2 01 2

0

Figure 3.4  Boom and bust: Opening of new nuclear reactors worldwide. (International Atomic Energy Commission 2016.)

from nuclear sources (Nuclear Energy Institute 2015). Nevertheless, since the 1990s, a number of developed countries such as Germany, Italy, and Switzerland have introduced plans to phase out the use of their existing nuclear power plants. In 2012, after the accident at Fukushima, China announced a moratorium on nuclear plant construction, but following plant safety inspections, the country has since renewed initiatives to develop new reactors as it seeks to find alternatives to producing power through coal. Against this backdrop, the future for nuclear power megaprojects remains highly uncertain.

3.2.7 An Enduring Feature of Infrastructure Development Taken together, these examples show how waves of innovation are a common feature across a wide range of megaproject types, as new technologies are diffused from local initiatives, to national, regional, and even international cycles of development. The emerge–​surge–​purge (or at least decline) pattern of megaproject innovation and project development is a powerful enduring force that has been present for at least the past century. Cycles of project development transcend political ideology, economic systems, and governance structure, as new megaproject technologies have diffused between capitalist and communist countries—​jurisdictions ruled by governments following liberal

 

Cycles in Megaproject Development    51 or conservative ideologies, as well as those taking nationalist or separatist perspectives. Each cycle appears to last for at least twenty years, reflecting the long time horizon over which megaproject planning and building occurs, and the time period that it may take to observe flaws in previous models of megaproject development that precipitate their declining popularity. Even some of the most successful megaproject technologies such as subways or urban metro railway systems that have endured for over a century have still seen waves where there were bursts of development followed by periods of less construction, or when development was more concentrated in certain regions of the world than in others. To date, most cycles of megaproject development have been initiated in the Global North and have traveled south, but there are indications that this pattern may be beginning to change as countries in the Global South develop innovative solutions to problems that are widely applicable elsewhere. The inspiration for a wave of megaproject innovation can come from a place at the top of the global hierarchy of importance, such as London, New York, or Paris. Or a successful innovation may be initiated in a place that typically garners less global attention, such as Curitiba or Bogota in the case of BRT, Baltimore’s Camden Yards for baseball stadiums, or Bilbao’s Guggenheim in the case of the museum-​building boom. The duration of time and frequency with which the emerge–​surge–​purge pattern of megaproject development is observable suggests that it is not merely a function of corporate globalization, modern mass communication technologies, or increased ease of international travel, though these are all probable factors. There is something more fundamentally enduring about the way that infrastructure megaprojects fit into local and global political economies, and are promoted and consumed. Providing explanations for these cyclical patterns of infrastructure development is the topic of the next section.

3.3  Why Cycles of Megaproject Development? Cycles of megaproject development, be they brief punctuated fads or longer-​term trends, have multiple interrelated causes. They are driven by a complex mix of technological innovation, economics, social networks, ideologies, and interest groups that spur the diffusion of certain new megaproject approaches at punctuated moments in time. Moreover, the global diffusion of megaproject innovations is furthered by the political and policy lure of achieving major tangible benefits, as well as the potential to convey a powerful set of intangible symbolic messages that often get ascribed to certain megaproject technologies. A fulsome explanation for the causes of megaproject cycles of development requires the blending of insights on innovation, policy mobility, and technology diffusion from three diverse disciplinary perspectives. For economists, waves of innovation and

 

52   Matti Siemiatycki diffusion of new technologies are the result of a process of creative destruction, where new technologies that better meet demand at lower costs are constantly supplanting old ones. Political scientists observe that policy mobility results from the confluence of institutions, ideologies, and individuals that support the diffusion of certain technologies or policies at a given moment in time (Dolowitz and Marsh 2000). And geography and planning scholars have emphasized the importance of local cultures and unequal power dynamics in the policy transfer networks to explain how new ideas or technologies are reinterpreted and altered as they move from one place to another (McCann and Ward 2012). Examining each stage of the emerge–​surge–​purge innovation diffusion cycle that megaprojects pass through illustrates how certain actors, political economic interests, and ideologies come to predominate, thereby influencing which megaproject developments are transferred nationally or globally.

3.3.1 The Innovator The infrastructure development cycle begins with an “innovator” creating a new item, product, or activity. When studying megaproject innovators and the novel ideas they create, it is necessary to identify the extent to which the innovation is truly new, where in the world it is being developed, the motivations for developing a new megaproject approach, and the way that different stakeholders from the private and public sectors are involved. Each of these factors provides insights into the types of innovation that are developed, and ultimately how transferable they will be to other jurisdictions. As highlighted previously, the spark for a wave of innovation in the infrastructure sector can come from jurisdictions at the top of the global hierarchy that are well known, as well as less prominent locations. Importantly, both the public and private sectors are sources of megaproject innovations. Developing and implementing new technologies on a large scale carries significant risks that the private sector might not be willing or able to bear on their own. As such, it is quite common that some of the most audacious, innovative, daring, and risky megaprojects include a combination of government and private-​sector involvement in terms of research and development, funding, ownership, and operations. What is critical for an innovation to spark a cycle of development is that the novel approach addresses a common challenge being faced in a wide variety of jurisdictions. Some rare innovations, such as the motor vehicle, railway, airplane, computer, and Internet, are truly revolutionary in origin, in that they imagine a technology, entire product category, or idea that had never been tried before. These technologies have the capacity to entirely supplant previous infrastructural technologies and completely reorder spatial, social, and political relations. More often, an innovation is evolutionary in nature, reimagining or adapting technologies or ideas that existed for some time. These evolutionary innovations, like driverless trains or novel high-​rise building techniques, make an incremental improvement to an existing technology, which might increase its utility, lower costs, diminish risk, or minimize the externalities.

 

Cycles in Megaproject Development    53 There are diverse motivations for developing and implementing innovative infrastructure technologies at given times. Investments in novel megaprojects have the potential to deliver significant benefits by alleviating local problems and elevating the competitiveness of specific jurisdictions by tying them more closely into cross-​border spaces of flows. Depending on the type of megaproject, it can make a place more accessible, safe, healthy, efficient, productive, learned, livable, beautiful, sustainable, or resilient, driving economic growth and prosperity. As such, there can be a considerable advantage for first movers that successfully harness a new type of megaproject. There are also significant political gains to be had: the local mayors of both Curitiba and Bogota used their high-​profile leadership of successful pioneering BRT projects as a springboard to launch state-​level and national political careers. Another form of innovation is the construction of novel symbolic meanings for a megaproject. Infrastructure megaprojects become imbued with a wide set of powerful symbolic imageries that transcend their stated purpose, and are targeted at both a local and global audience. Official narratives developed by project planners and promoters tend to focus on themes of pride of place, an image of modernity and progress, optimism about the potential for collective action to deliver massive projects, and visionary leadership to execute plans on a large scale to solve pressing problems. The Delhi Metro provides a case in point. In their promotional material and public discourse, project planners presented the new electric train system as a megaproject that would provide tangible benefits of combating traffic congestion and ameliorating air pollution. They also carefully constructed the image of the Metro also as a sleek, clean, and well-​managed symbol of progress for modern Delhi that would put the city in line with the great capital cities of the world that all have extensive subway systems. On the day that the Delhi Metro opened, more than a million Delhiites lined up to ride the train that had become a point of pride in the city (see Siemiatycki 2006). Outside the officially constructed narrative, megaprojects also have the potential to convey more negative symbolic associations, including wasteful spending, blatant rent-​seeking, project management incompetence, and unchecked authority, power, and control. Against this backdrop, in many cases the construction of a lasting symbolic narrative to associate with a megaproject is hotly contested and evolves over time. In Boston, while the Big Dig to bury the central artery was initially viewed very negatively because of the high-​profile construction cost overrun that the project experienced, years later a more positive narrative is emerging that recognizes the broader city-​building benefits that have been achieved.

3.3.2 The Surge Given the major tangible and symbolic benefits associated with the implementation of certain trendsetting megaprojects, it is not surprising that imitators of a successful idea would follow. A critical question is why some megaproject innovations surge in popularity to become global waves or longer-​term trends, while others fail to catch on and

 

54   Matti Siemiatycki achieve further adoption. Put differently, at any given moment many innovative megaproject technologies are being developed and experimented with around the globe—​ some revolutionary and others evolutionary. So how do we explain which ones surge in popularity to become part of a global wave of development? The answer to this question is multifaceted, influenced by the type of new technology and the benefits they deliver, the status, cache, and influence of the innovators and their promoters, and the political economy of who benefits from the new type of megaproject. At the most basic level, megaproject innovations surge to wider uptake because they are superior to other alternatives in terms of the benefits they provide. These benefits can be diverse, including greater economic, environmental, or social benefits at lower costs than other alternatives, easier or lower risk to implement, and better adaptability to varied physical and governance contexts. Megaprojects that surge from local innovations to global phenomena are also those that fill a common pressing need faced by many societies at a given time, be it for improved mobility and congestion relief, sanitation and clean drinking water, reliable energy, security, trade, tourism, livability, and so forth. The type of megaproject and the need that it fulfills affects the rationales underlying a surge in popularity and implementation. Megaprojects providing hard infrastructural services such as public transit, urban road tunnels, water and waste-​water treatment, and public housing tend to be focused on fulfilling the basic needs of local users, which can have the knock-​on effect of making that place more externally competitive. And their success is not particularly impacted by different approaches taken elsewhere. The implementation of a novel BRT system in Bogota does not have a direct impact on the success of a subway system in Brussels. As such, the spread of these types of hard locally oriented infrastructures at any given time are largely driven by the availability of new technologies, governance capacity, the ability to mobilize the necessary resources, shifting priorities, and ideologies about the way to solve difficult collective problems, and the symbolic images associated with various technologies. In contrast to hard local infrastructure, the success of other types of facilities are much more dependent on their interoperability and integration into national or global networks of commerce or people to remain competitive. For this type of megaproject, a new wave of development can be quickly sparked if an innovative technology or design displaces previous approaches and requires others to make similar investments to remain competitive. Ports, for instance, are a hard infrastructure that must be constantly kept up to date with the global technology standard for deep-​water access, loading and unloading equipment, and surrounding ground transportation access, otherwise they will not be able to service the current types of ships or will become less efficient than competing facilities and ultimately lose market share to competitors. Some types of social infrastructure such as convention centers also exist within a context of intense global competition. There are only so many conventions globally that require major meeting facilities for thousands of people. To tap into this lucrative market, cities have built ever more elaborate convention centers to attract globally footloose business activity to their jurisdiction, while antiquated facilities face the pressure of declining patronage. In addition to the importance of the practical utility of an innovation, the rising tide of a cycle of infrastructure development is also part of a social, economic, and political

 

Cycles in Megaproject Development    55 process. Novel megaproject technologies or approaches are diffused through a series of interconnected networks and channels in such a way that they resonate with, and become adopted by, a wider following. With infrastructure megaprojects, an internationally connected group of prominent architects, designers, planners, consultants, and politicians has been central in uncovering novel technologies or project types, and communicating the merits of these infrastructures to a wider set of political and economic decision makers. There are various forums through which new megaproject ideas are disseminated, including media coverage of high-​profile projects, policy conferences, World’s Fairs and international sporting events, and international travel junkets. The importance of the networks through which new ideas are disseminated should not be underestimated; some of the recent megaprojects that sparked international cycles of development were initiated or funded by prestigious and well-​connected global organizations, even if they were located in less well-known locations. The Guggenheim in Bilbao that sparked a wave of museum megaprojects was designed by one of the world’s most famous architects and was part of a well-​established global museum franchise, which brought considerable international attention through their networks. Similarly, Bogota’s BRT system was backed by the World Bank as a lower cost alternative to light rail. The World Bank subsequently trumpeted the success to other potential markets, raising awareness and ascribing legitimacy to the technology in other developed countries. And Camden Yards stadium in Baltimore was designed by the prominent international architecture firm HOK, which was subsequently hired to design sixteen new American baseball stadiums over the ensuing two decades, thus playing an important role in spreading the retro design innovation across the continent, and profiting from it. As illustrated by these examples, the connections of the originators of new technologies and the networks through which new ideas are disseminated influences which projects are most likely to spread widely. Finally, there is a clear political economy to which megaprojects are diffused widely. Successfully diffused megaproject innovations are commonly those that appeal to individuals with elevated status, wealth, and prestige, and are part of local growth coalitions. The majority of megaproject technologies or approaches that have surged in popularity are those that provide the basis to make a jurisdiction more economically competitive, have the potential to generate large profits for key local interests such as property owners, developers, and industrialists, and project key messages of pride of place that appeal to important civic boosters and the mainstream media. To this end, megaprojects that surge in popularity are those that are consistent with the predominant ideology of the day, while making it possible for each jurisdiction to superimpose their own local symbolic narratives onto the megaproject.

3.3.3 The Cycle Ends The decline of a cycle of innovation and megaproject development begins for a variety of reasons, including the reaching of a saturation point, the usurping of the old approach by a new technology, and emerging evidence of flaws in the original model

 

56   Matti Siemiatycki of development. First, saturation may be reached, as the majority of markets where a specific type of technology is a viable option have taken it up and are benefiting from the original innovation. This applies most directly to globally oriented megaprojects that put facilities in one jurisdiction directly in competition with those in other places. Once every potential market has adopted the current state-​of-​the-​art technology—​for example, new stadiums or convention centers—​there is no need for a continued wave of development until a major new innovation disrupts the status quo. Instead, we may see more minor renovations and expansions of existing facilities. Second, the end of a megaproject development cycle may be initiated when a new technology emerges that provides greater tangible or symbolic benefits than the old approach. This is the classic case of creative destruction. It can be seen throughout the history of megaprojects: railways replaced canals for inland freight transportation in the nineteenth century; urban streetcars were largely replaced by the car and transit bus in the mid-​twentieth century; and downtown retro baseball stadiums displaced modern suburban fields at the turn of the twenty-​first century. Third, flaws in the original megaproject approach might become more apparent than they were during the period of rapid uptake, when symbolic or political benefits ascribed to a megaproject obscure careful analysis of its tangible benefits and costs, or winners and losers. Megaprojects that are appropriate in one context or delivered great benefit for the original innovator may not be as effective elsewhere. While initial underperformance observed with a surging megaproject technology is often blamed on local political conditions or poor implementation processes, over time, expert and local community opposition has been instrumental in highlighting systemic flaws and ultimately halting waves of megaproject development. Growing evidence of systemic cost overruns and benefit shortfalls on megaprojects such as light rail lines, iconic museum buildings, or power dams can lead to the cancelation of subsequent phases of existing projects, or halt adoption by other jurisdictions. Planning processes that lack transparency and accountability have been a source of community opposition. Changes in government or political power may halt waves of development by contributing to shifts in the types of project that are prioritized. And shifting economic conditions or public perceptions of a type of infrastructure can lead key megaproject supporters, such as local property developers and civic boosters that once supported a certain type of development, to switch their position if a technology comes to be seen as contradicting their interests. Indeed, opposition groups raising awareness about the negative externalities of megaprojects have been important in the decline of various technologies, especially the modernist transportation, public housing, and energy megaprojects of the mid-​twentieth century. Importantly, different types of megaproject are impacted differently by innovation and changing attitudes toward a specific technology, and therefore experience decline in different ways. Megaprojects are fixed capital, meant to last for generations. Yet some innovations impose complete creative destruction on the generation of infrastructure that came before, and the outdated technology is actively removed from the physical landscape. In the case of tramlines in the mid-​twentieth century and baseball stadiums

 

Cycles in Megaproject Development    57 at the turn of the twenty-​first century, at the end of their wave of development each was actively removed because they were no longer profitable, interfered with the technology that displaced them, and were symbolically representative of the old urban order. Conversely in other cases, once a surge in megaproject development is over, that technology may continue to be used for decades to come, with money continuing to be spent on maintenance and upgrades. Nuclear power reactors provide a case where although few new facilities have been built in developed countries since the 1990s, most facilities have continued to be operated to provide a necessary energy source. Intriguingly, in the case of elevated urban freeways that were popularized in the 1950s and 1960s, after decades of use their future is now being hotly debated. While these facilities have continued to operate long after the wave of development ended in the 1970s, politicians and community groups in many cities are debating both their ongoing utility and symbolic meaning in an era where cities are focusing more than ever on sustainability, walkability, and livability. In fact, a growing number of cities, such as Boston, Seattle, Seoul, and San Francisco, have undertaken megaprojects to replace these aging artifacts of an old urban order. As the experience with freeways suggests, shifting utility and perceptions of one type of megaproject often initiates a feedback loop where opinion leaders are again out searching for and implementing the next big thing.

3.4  Conclusions: Where on the Innovation Curve Is Your Megaproject? As demonstrated in this chapter, cycles of megaproject development are a common feature across a wide variety of locations, time periods, and infrastructure types. Over the past two centuries, new innovations in megaprojects have emerged in jurisdictions all around the world, have surged in popularity as they are adopted widely, and subsequently have seen declining implementation as they deliver on their promised benefits, fail to meet expectations in a large number of places, or are usurped by the next wave of development. The observation of the cyclical nature of megaproject development, as well as an understanding of the processes that drive them, provides powerful insights for public-​and private-​sector decision makers. Indeed, policy makers can learn about the probable success of a proposed project under review, and the risks involved, by studying three interrelated questions during the assessment phase of a project’s development. First, where in the cycle of development is a given type of infrastructure that is being considered, and how will it affect that particular type of megaproject? For some project types such as globally orientated cultural facilities, convention centers, or seaports, there is a significant first-​mover advantage that accompanies being the innovator, which outweighs the high costs and risks of developing a new megaproject technology. In other cases, such as investments in correctly located urban rapid transit megaprojects, telecommunications initiatives, or green energy projects, large benefits continue to accrue

 

58   Matti Siemiatycki from being a later adopter once the technology is perfected or a wave of development catches on. As megaproject technology reaches maturity with widespread adoption, project planners must consider the likelihood and impact on their project if a new wave of technology usurps the type of infrastructure they intend to develop. Second, how comparable are the places where a megaproject idea is coming from and being transferred to? A surprising observation is that megaproject technologies such as bus rapid transit or high-​tech bike-​sharing systems that can cost hundreds of millions of dollars to implement have often been successfully transferred between jurisdictions with significantly different political systems, governance structures, or ideologies, provided that they are designed to solve similar tangible and symbolic problems. At the same time, a megaproject such as a new light railway line that delivered significant benefits in one place may fail elsewhere if it is inappropriately located, not accompanied by complementary policies that made the originator successful, does not consider the local cultural or economic conditions, or is unpopular with the surrounding community. Third, what is the primary objective for the megaproject being developed? Is the project intended primarily to improve local conditions through the implementation of a hard piece of infrastructure, or is it mainly geared toward tying a region into global spaces of flows—​be it for transportation, capital, trade, tourists, image and attention, and so on. Internationally orientated megaprojects tend to be especially sensitive to innovations elsewhere, whereas locally orientated infrastructures may still provide significant local benefit even if the global state-​of-​the-​art has moved on. Taken together, answering these questions during the project assessment process will enable policy makers to take advantage of this understanding of the cycles of megaproject development. Decision makers can avoid the costly mistake of developing megaprojects that may be obsolete soon after construction is completed, or are inappropriate for the jurisdiction to where they are being transferred.

References Best, J. (2006). Flavor of the Month. Berkeley: University of California Press. Council on Tall Buildings and Urban Habitat. (2015). “100 tallest completed buildings in the world by height to architectural top,” . Dolowitz, D. P. and Marsh, D. (2000). “Learning from abroad: The role of policy transfer in contemporary policy-​making,” Governance, 13(1): 5–​23. Flyvbjerg, B. (2007). “Cost overruns and demand shortfalls in urban rail and other infrastructure,” Transportation Planning and Technology, 30(1): 9–​30. Foster, V., Butterfield, W., Chen, C., and Pushak, N. (2008). “Building bridges: China’s growing role as infrastructure financier for Sub-​Saharan Africa,” World Bank, . International Atomic Energy Commission. (2016). Nuclear Power Reactors in the World. Vienna: IAEC.

 

Cycles in Megaproject Development    59 Jedwab, R. and Moradi, A. (2012). “Colonial investments and long-​term development in Africa: Evidence from Ghanaian railroads,” NEUDC Conference Working Paper, . Lehrer, U. and Laidley, J. (2008). “Old mega-​projects newly packaged? Waterfront redevelopment in Toronto,” International Journal of Urban and Regional Research, 32(4): 786–​803. McCann, E. J. and Ward, K. (2012). “Policy assemblages, mobilities and mutations: Toward a multidisciplinary conversation,” Political Studies Review, 10: 325–​32. Mees, P. (2010). Transport for Suburbia. London: Earthscan. Nuclear Energy Institute. (2015). “World statistics,” . Pickrell, D. (1992). “A desire named streetcar: Fantasy and fact in rail transit planning,” Journal of the American Planning Association, 58(2): 158–​76. Siemiatycki, M. (2006). Message in a metro: Building urban rail infrastructure and image in Delhi, India,” International Journal of Urban and Regional Research, 30(2): 277–​92. UNDP. (2012). “Bogota, Colombia bus rapid transit project: Transmilenos,” .

 

Chapter 4

Big Is Frag i l e An Attempt at Theorizing Scale Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn

“There is nothing more deceptive than an obvious fact.” Sherlock Holmes in The Boscombe Valley Mystery, Sir Arthur Conan Doyle

4.1 Introduction Theories of big have advocated the proposition that “bigger is better” since the mid-​ nineteenth century, drawing especially on notions of economies of scale and scope (Stigler 1958; Silberston 1972; Chandler 1990), natural monopoly (Mill 1848; Mosca 2008), or preemptive capacity building (Porter 1980). Building big has traditionally been seen as necessary to secure efficient economies of scale and to lock competitors out of future rivalry (Ghemawat 1991; Ghemawat and der Sol 1998; Hayes and Garvin 1982: 78; Penrose [1959] 2009: 89–​92; Wernerfelt and Karnani 1987). Economies of scale in the production of electricity, for example, assume declining average cost curve as output expands (Ansar and Pohlers 2014: Fig. 1). Theories of big have held an enduring sway on management practice. Scaling is deemed necessary for survival and competitive advantage in many industries such as steel (Crompton and Lesourd 2008), shipping (Cullinane and Khanna 2000), banking (Cavallo and Rossi 2001), telecommunications (Majumdar and Venkataraman 1998; Foreman and Beauvais 1999), water, and electricity utilities (Kowka 2002; Pollitt and Steer 2012). Big ventures are witnessed when companies try to pursue new product or geographic markets: Motorola spent US$6 billion in technological rollout of its Iridium satellite constellation (Bhidé 2008); and the German steel company ThyssenKrupp spent over US$11 billion to enter the US and Brazilian markets (Ansar 2012). In the context of economic development, Sachs (2006) has popularized the view that big

 

Big Is Fragile    61 challenges—​such as poverty alleviation, energy and water scarcity, or urbanization—​ can only be solved with “big push” solutions. Theories of big are not universally accepted, needless to say. Schumacher (1973) championed “Small is beautiful.” Easterly (2002, 2006) has argued against the big push “megareforms” that Sachs favors. Perhaps the most persistent attack on theories of big has come from Lindblom, who advanced the notions of “muddling through” (1959) and “disjointed incrementalism” (1979) as an alternative to “bigger is better.” In the academic debate, a school of thought emerged around the notion of incrementalism, with concepts such as logical incrementalism (Quinn 1978), modularity (Baldwin and Clark 2000), real optionality (Copeland and Tufano 2004), and adaptive change (Heifetz et al. 2009). The key rationale for incrementalism is based on the well-​documented limits of rationality in decision making under uncertainty (Atkinson 2011: 9). Yet theories of big have maintained an enduring upper hand in mainstream business and government practice: megaprojects, justified on the bases of theories of big, are more ubiquitous and bigger than ever (Flyvbjerg 2014). A renewed enquiry into the validity of theories of big has become urgent because big capital investment decisions routinely fail in the real world. Motorola’s Iridium went bankrupt within three years of its launch, wiping off nearly US$10 billion of equity (Kerzner 2009: 351). ThyssenKrupp’s megaprojects in the Americas, initiated in 2005, suffered a worse fate. By June 2012, ThyssenKrupp’s survival was in doubt, and the company’s share price was a quarter of its May 2008 high. The company was forced to raise fresh capital in part by selling its ill-​fated US steel plant at a steep discount to its archrivals ArcelorMittal and Nippon-​ Sumitomo. ThyssenKrupp’s top management team, including the Chairman Gerhard Cromme, who initiated the big capital investments, was fired. Other cases of big bets gone awry abound. Losses from Boston’s Big Dig or Citigroup’s “bold bets” reach into the billions of dollars (Dash and Creswell 2008). Not only did the costs sunk into Japan’s Fukushima nuclear power plant become unrecoverable; its clean-​up costs rippled far into the economy. Beyond the financial calculus, even the reticent Chinese government is opening up to the profound and unforeseen human and environmental impacts of China’s Three Gorges Dam (Qiu 2011; Stone 2008, 2011). Over the last fifteen years, evidence from large datasets has mounted that the financial, social, and environmental performance of big capital investments, in the public and private sectors alike, is strikingly poor (see, for example, Nutt 1999, 2002; Flyvbjerg et al. 2002, 2003, 2005, 2009; Titman, Wei, and Xie 2004; Flyvbjerg and Budzier 2011; Van Oorschot et al. 2013; Ansar et al. 2014). In this chapter we characterize the propensity of big capital investments to systematically deliver poor outcomes as “fragility”—​a notion suggested by Taleb (2012). A thing or system that is easily harmed by randomness is fragile. We argue that, contrary to their appearance, big capital investments break easily—​that is, they deliver negative net present value—​owing to various sources of uncertainty that impact them during their long gestation, implementation, and operation. We do not refute the existence of economies of scale and scope. Instead, we argue that big capital investments have a disproportionate (non-​linear) exposure to uncertainties that deliver poor or negative returns above

 

62    Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn and beyond their economies of scale and scope. We further argue that to succeed, leaders of capital projects need to carefully consider where scaling pays off and where it does not. To automatically assume that “bigger is better,” which is common in megaproject management, is a recipe for failure. In the following sections, we first develop and draw linkages between three theoretical concepts: Big, Fragility, and Scale versus Scalability. Building on the relevant literature, we advance twelve propositions about the sources and consequences of fragility, which we then apply to big capital investments. Specifically, we develop the construct of “investment fragility”—​the threshold at which the cumulative losses from an investment exceeds the investment’s cumulative gains. Second, we substantiate our propositions about the fragility of big capital investments using evidence from a dataset of 245 big dams. Our theoretical propositions and evidence from big dams suggests that big capital investments fail to achieve the aspirations of scalability and efficiency set for them at the outset. Once broken, these investments become stranded, causing long-​ term harm to the companies and countries that undertake them.

4.2  Theory and Constructs 4.2.1 What Is Big? Whether something is big seems obvious enough. Yet the construct of big and the related ideas of large, large-​scale, major, mega, or huge, and so forth, prove deceptively elusive when subjected to scrutiny. A literature review of definitions of big and related words reveals a non-​exhaustive list of multiple dimensions of the construct of big, such as: • Physical proportions measured in height, length, mass, weight, area, or volume. • Inputs required to build and run the thing measured in terms of quantities (and quality) of land, labor, or equipment required. • Financial outlay measured in up-​front capital expenditure (Flyvbjerg 2014), recurrent operational expenditure, or end-​of-​life costs (Clark and Wrigley 1995, 1997). • Supply measured in the units of output that the thing can produce (Samuelson 1948; Stigler 1958) or the multiplicity of outputs (Chandler 1990). • Demand being served, measured not only in terms of units of demand but also the quality, speed, and functionality (Weinstock and Goodenough 2006). • Temporality measured in the time it takes to build the thing or the length of its life span (Gomez-​Ibanez 2003). • Spatial fixity or immobility and the cost of moving an asset—​big tends to “spatial fixity” (Ansar 2012). • Complexity measured, for example, with a focus on the technical aspects of the asset or its delivery (Simon 1962), or with a focus on the social and political complexity (Liu et al. 2007).

 

Big Is Fragile    63 • Impact measured in the number of people who might benefit or be harmed, the number of functions enabled or disabled, or the magnitude and pace of change that the thing can cause in its environment. The relationships among these multiple dimensions—​and even the indicators within each dimension—​are seldom straightforward. For instance, it is often taken for granted that in order to reduce the amount of time required to complete a venture, such as a software IT project, a manager would need to mobilize more programmers, which will also increase the capital expenditure of the venture (for a discussion, see Atkinson 1999; Williams 2005). Yet experienced managers report that such obvious relationships do not hold in practice. In contrast, Fred Brooks—​the IBM executive responsible for development of IBM’s System/​360 family of computers in the 1960s, from which computers today have descended—​formulated the famous “Brooks law:” “Adding manpower to a late software project makes it later” (Brooks 1995: 25). Bigness entails multiple and unpredictable interactions across the dimensions we have listed with which theories of big—​such as the notion of economies of scale—​have not meaningfully engaged. The risk of big is reflected in these interactions, which we turn to now.

4.2.2 What Is Fragility? Taleb (2012) proposes the construct of fragility, and its antonym antifragile, to capture the type of randomness and risk we talk about here. Taleb’s inspiration for the concept came from his observation that there is no random event that can benefit a porcelain cup resting on a table, yet a wide range of uncertain events—​such as earthquakes or human clumsiness—​can pose harm (Taleb 2012: 268). Fragile things, like the porcelain cup, are vulnerable to members of the “disorder family,” including, for example, randomness, uncertainty, volatility, variability, disturbance, or entropy—​terms we use interchangeably below1 to explore the fragility of big capital investments. Fragility as a construct has found increasingly diverse use, regarding, for example, construction (Shinozuka et al. 2000; Choi et al. 2004); human bones (Seref-​Ferlengez et al. 2015); global financial and banking crises (Davis 1995; Taleb et al. 2012; Klemkosky 2013; Calomiris and Haber 2014); mathematics (Taleb and Douady 2013); ecology and ecosystems (Nilsson and Grelsson 1995; Sole and Montoya 2001); interdependent networks (Callaway et al. 2000; Buldyrev et al. 2010; Vespignani 2010; Parshani et al. 2011; Gao et al. 2012; Morris and Barthelemy 2013); material sciences, such as in assessing properties of glass-​forming liquids (Scopigno et al. 2003; Mauro et al. 2014; Martinez-​ Garcia et al. 2015); conflict-​prone countries (USAID 2005; Ziaja 2012); democratic political systems (Mitchell 1995; Issacharoff 2007); and even personal ethics (Nussbaum 2001). Despite its diverse uses, fragility has certain common meanings across these fields. Taking our point of departure in Taleb’s work, because this is the most comprehensive, and supplementing this with other sources, we first distill a general definition

 

64    Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn of fragility. Second, we use this to develop a more specific concept called “investment fragility,” which we apply to big capital investments. Fragility describes “how [a]‌system suffers” when it encounters disorder (Taleb and Douady 2013: 1677, italics in the original). The outcome of fragility is typically an irreversible loss of functionality. Our preliminary proposition, which we will refine below, is as follows: Proposition 1. Fragility is typically irreversible. Once broken, the fragile cannot be readily restored to its original function. Fragility as a material property is signified by a material’s breaking point (Scopigno et al. 2003; Martinez-​Garcia et al. 2015). Mauro et al. (2014) call this unique intrinsic fragility threshold a “structural signature.” Buldyrev et al. (2010) conducted similar structural analysis on networks such as electricity grids (also see Vespignani 2010). They find that intrinsic structural features of networks—​such as number of nodes, whether a network is isolated or interdependent, and the number of interconnections with other networks—​can help determine the “critical threshold” at which the various networks break down.2 As a more generalizable proposition: Proposition 2. A thing (material, system, process, or network) has a unique “fragility threshold” which careful structural analysis and experimentation can reveal, at which it will break down under influence from stressor(s). All other things being equal, the lower the preset threshold the greater the fragility. An assumed benefit of big is that the fragility threshold increases with size. However, Taleb (2012: 278–​80) argues that larger organisms such as elephants tend to have a lower fragility threshold as a proportion of their size than do smaller organisms. Thus, for example, it might take a stone twice the body weight of a cat to cause a fatal outcome. But a boulder only half the bodyweight of an elephant might suffice for its fragility threshold. The source of this disproportionally greater fragility of bigger systems is to be found in the Nobel Prize-​winning physicist P. W. Anderson’s (1972) notion of “more is different.” As a more generalizable proposition, we advance: Proposition 3. As a system grows bigger, the relative size of a stressor required to break it will decline disproportionately. As suggested before, another source of fragility is the interconnectedness of systems. In other words, “inherited fragility.” Inherited fragility helps to map out the diffusion of harm in the event of fragility in a corner of an interconnected system of systems. As a generalizable proposition: Proposition 4. In an interdependent system of systems with no redundancy, the threshold of fragility for the whole system of systems is the same as the threshold of the system’s weakest component.

 

Big Is Fragile    65

Function recoverability Low

e.g., Fungi

Low

Fragility threshold

High

e.g., Diamonds

High

e.g., Humpty Dumpty the egg

e.g., Multi-use electric fuse

Figure 4.1  A map of fragility.

Figure  4.1 suggests a composite way to map different things on the spectrum of greater to lesser fragility. This constitutes two dimensions. First, the vertical axis shows how easily something breaks; that is, a high or low preset “fragility threshold.” Second, the horizontal axis shows how easily the broken thing can be recovered to its self-​same functional state once the fragility threshold is crossed; that is, high or low “function recoverability.” Humpty Dumpty, the egg of the children’s nursery rhyme, suffered from a double-​whammy of fragility (Quadrant 4 in Figure 4.1): it broke easily; that is, it had a low threshold against fragility. And it could not be put together again. However, not all things are as unlucky as Humpty Dumpty the egg. A multi-​use electric fuse also breaks easily but can also be easily restored to perform its sacrificial function (Quadrant 3). In contrast, a diamond has a high fragility threshold but once broken the damage is irreversible (Quadrant 2). Finally, fungi—​and many systems in nature (Taleb 2012)—​do not break easily and easily recover (Quadrant 1). Incidentally, as our discussion on scalability in the next section shows, systems in Quadrant 1 share many properties with highly scalable systems.3 Proposition 5. Systems with a low fragility threshold and low function recoverability (Quadrant 4) require a great deal of cushioning to protect them from breaking.

 

66    Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn Closely related to the distinction between “intrinsic” and “inherited” fragility is the distinction between “apparent” and “hidden” fragility. An egg’s vulnerability to breaking is apparent. We thus handle eggs with care when bought at the grocery to cook for tomorrow’s breakfast. We also do not act surprised when eggs break. Similarly, an electric fuse’s fragility is apparent and in fact intended. In contrast, hidden vulnerability is insidious and entails surprise. Vespignani (2010: 985) finds that in cases of highly interconnected networks breakage is typically “abrupt” at a relatively low critical threshold, which introduces an element of surprise: “This makes complete system breakdown even more difficult to anticipate or control than in an isolated network.” Hidden fragility has an interaction effect with inherited fragility: an Achilles heel is a reminder of this phenomenon when a small hidden weakness is inherited by an otherwise mighty system.4 Proposition 6. The information conditions necessary to make a system truly robust are very strong because some minor source of hidden fragility is likely to remain. In instances of hidden and inherited fragility, seemingly robust systems will break down abruptly at a surprisingly low critical threshold. Lack of preparedness in instances of hidden and inherited fragility will accentuate the consequent harm. Although Taleb (2012: 270–​1, for example) underplays the role of cumulative processes in creating fragility, hidden fragility is often created or exacerbated by them. Taleb typically focuses on fragility caused by one single blow. “Cumulative fragility,” in contrast, is death by a thousand cuts. Keil and Montealegre (2000) liken such an ill-​ fated investment to a frog being boiled to death without knowing it (see also Keil 1995; Royer 2003). Poorly understood dynamic changes often lower the fragility threshold without warning. Even a minor stressor, in such circumstances, leads to unexpected breakage. Seref-​Ferlengez et al. (2015), for instance, find that human bones are constantly exposed to microdamage from routine stressors. As people age, microdamage from routine wear and tear begins to accumulate that contributes “additively to reduced fracture toughness”—​that is, a lowering of the threshold at which the bone breaks (Seref-​Ferlengez et al. 2015: 1). In technological systems, accumulation of small errors is often behind human-​made disasters (Turner and Pidgeon 1997). Proposition 7. Cumulative hidden processes will increase the propensity of fragility of a system over time. Hidden fragility also has sociological and psychological features. Scholars of power relationships suggest that organizations can tacitly choose to ignore the obvious (Flyvbjerg 1998) or people in organizations “know that we do not want to know” (Ansar 2015). Psychological biases such as overconfidence also “bring fragilities” owing to “expert

 

Big Is Fragile    67 problems (in which the expert knows a lot but less than he thinks he does)” (Taleb 2012: 215). Psychological theories predict that hidden fragilities in systems designed by experts will be the norm, not the exception (Kahneman 2011). NASA lost its $125-​million Mars Climate Orbiter in September 1999 because one engineering team used metric units while another used imperial units for a spacecraft maneuver (Reichhardt 1999; see also Hodgkinson and Starbuck 2012: 2–​5, for discussion of NASA’s Space Shuttle disasters in light of theories of organizational decision making). “Our inability to recognize and correct this simple error has had major implications,” said Edward Stone, the Director of the Jet Propulsion Laboratory (JPL) at NASA that oversaw the mission, according to CNN (30 September 1999). Also see Proposition 6 on information conditions of correcting hidden fragility. Proposition 8. Behavioral and psychological biases will make the detection of hidden fragility more difficult. Hidden fragilities in systems designed by experts will be the norm, not the exception. Proposition 9. In sociological and organizational contexts, hidden fragility will be hidden in plain sight. Although Taleb has tended to focus on external causes of disorder, ecologists working on fragility pay equal attention to internal changes that cause fragility (see Nilsson and Grelsson 1995). Theorists of “broken symmetry” have also noted that as internal complexity increases, the threat of internal sources of disturbance—​often driven by entirely random processes—​grows non-​linearly, exposing a larger system to breakdown with no apparent cause (Anderson 2011). From a consequentialist perspective, the distinction between external and internal stressors is immaterial: it is the magnitude of the negative outcome that follows that matters. Taleb (2012: 136) argues: You can control fragility a lot more than you think … detecting (anti)fragility—​or, actually, smelling it [ … ]—​is easier, much easier, than prediction and understanding the dynamics of events, the entire mission reduces to the central principle of what to do to minimize harm (and maximize gain) from forecasting errors, that is, to have things that don’t fall apart, or even benefit, when we make a mistake … Not seeing a tsunami or an economic event coming is excusable; building something fragile to them is not.

From a consequentialist perspective, a generalizable proposition that can be advanced is as follows: Proposition 10. If a system or process is systematically delivering poor outcomes, it is an indicator of fragility. Discard or redesign the system. Proposition 11. It is easier to be robust against the magnitude of harm that fragility might bring than predict or control the sources of stressor(s).

 

68    Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn

4.2.3 The Special Case of “Investment Fragility” So far we have analyzed general features of fragility. Now we turn to the special case of “investment fragility,” which we define as the vulnerability of a financial investment to becoming non-​viable; that is, losing its ability to create net economic value. When applied to physical assets such as roads, oil refineries, bridges, factories, real estate developments, and so on, investment fragility causes them to become “stranded assets”; that is, where “assets suffer from unanticipated or premature write-​offs, downward revaluations, or are converted to liabilities” (Ansar et al. 2013a: 2). A broken or stranded asset is a net drag on the economy; that is, it consumes resources inefficiently that could have been put to alternative uses. An economy with too many assets prone to fragility is at a heightened risk of system-​wide failure owing to the domino-​like effect of inherited fragility that can spread from one corner of the system or systems to the whole.

4.2.3.1 Benefit-​to-​Cost Ratio (BCR): A Rule of Thumb to Detect the Investment Fragility Threshold The fragility threshold of an investment can be located by modeling the investment’s pay-​off structure. Figure 4.2 illustrates such a pay-​off structure graphically: the discounted stream of gain and the discounted stream of pain of a hypothetical investment is sorted in a descending order and then graphed. Since investments typically span long time horizons, it is imperative to incorporate the time value of money in the pay-​off structure by introducing an appropriate discount rate (see Souder and Shaver 2010). The point of fragility in Figure 4.2 is where the cumulative pain—​area “1”—​just exceeds the

Gain

Gain/pain F(X)

Investment fragility threshold when area 1> ~2

2

Variable X

Pain

1

Figure 4.2  Graphing “investment fragility.” (Adapted from Taleb 2012: 273.)

 

Big Is Fragile    69 cumulative gain—​area “2.” In other words, an investment is broken when the cumulative gain-​to-​pain ratio falls below 1, less gain in the numerator than the pain in the denominator. The gain-​to-​pain ratio, which is commonly thought of as benefit-​to-​cost ratio (BCR) in literature on capital budgeting, thus serves as a useful rule of thumb for detecting the fragility threshold of an investment. Like the more general case of fragility, an asset suffers from greater intrinsic investment fragility when the absolute threshold of disturbance required to “break” it is low—​ for example, a low ex ante benefit-​to-​cost ratio—​whereby a stressor easily pushes the benefit-​to-​cost ratio below 1. The stressor may be, for example, just one weather event in the sixty-​year life of the asset that causes so much mess that costs of dealing with it spiral out of proportion. As with many fragile things, there is an element of surprise in investment fragility, as well—​seemingly improbable, and often minor, stressor(s) can cause disproportionate harm. An investment is more fragile when once broken it is difficult or nearly impossible to reposition it to make recovery possible via alternative uses. Less specific assets—​for example, buildings that can change use—​are less prone to becoming irreversibly broken than assets with a higher specificity (see Gómez-​Ibáñez 2003 for a rich ground of interconnections between investment fragility and discussion on “hold up” in transaction cost economics). Similarly, an asset has higher intrinsic investment fragility when its gain (anticipated benefits and any windfall) is capped but the pain (anticipated cost and any unforeseen losses) is uncapped. This propensity exhibits itself in the shape of Figure 4.2, where the top left part of the curve (gain) is bounded and finite but the bottom right part of the curve (pain) is unbounded and potentially an infinite pit. Based on this observation, Taleb (2012: 158, italics in the original) proposed: “Fragility implies more to lose than to gain, equals more downside than upside, equals (unfavorable) asymmetry.”

4.2.4 What Is Scalability? The Oxford English Dictionary defines scalable and scalability in the following manner: scalable, adj. Able to be changed in scale. rare. 1977 Jrnl. Royal Soc. Arts 125 770/​1. Such lasers are scaleable since large volumes could be pumped uniformly. scalability n. the property of being scalable. 1978 Sci. Amer. Nov. 44/​2. It took demonstrations of the scalability of the technology and tests of improved beam focusing … to catalyze an effort that led to support by the AEC.

 

70    Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn We note, in particular, the unsatisfactory definition of the word scalable. What does the ability to be changed (or equally change without external force) in scale mean? In practice, scalability is most commonly discussed in the field of computer science, system architecture, and software programming (Hill 1990; Gunther 2007). This is insufficeint for our purposes. In academic literature, an understanding of whether, and under what conditions, something has the ability to be changed in scale has been deeply informed by advances in mathematics and particularly the field of fractal geometry. Mandelbrot’s research identified two primary dimensions of scale: temporal and spatial. A grain of sand, a pebble, a rock, a cliff, and the coastline of, say, Britain represent a continuum of finer to coarser grades of the spatial scale (see Mandelbrot 1967). Similarly, the price movements of a stock price over a scale between five seconds to five years represents finer to coarser grades of a temporal scale. Finer and coarser grades of scale can also be thought of in terms of degrees of zoom-​in (microscropic) and zoom-​out (macroscopic). To Madelbrot’s spatial and temporal scale, we introduce a third scale: “relational.” The relational scale not only refers to the number of end-​users (for example, few or many) but also to the heterogeneity of end-​users and their tailored need (see Ansar 2010; Ansar 2012, for a more extensive discussion on a spatial, temporal, and relational multiscalar framework).5 Based on this understanding of scale, we define scalability as the ability of a thing (a system, system of systems, process, or network, for example) to effortlessly transition back and forth from the very micro to the very macro spatial, temporal, and relational scales. Effortlessness connotes minimum friction in terms of the time, cost, and so on, that it takes to build up or remove capacity. Over longer timescales, effortlessness implies ability to quickly upgrade without losing compatibility. However, if scalability is understood and practiced as mainly the ability to scale up, with scant attention to scaling down—​which is the dominant approach today in both the academy and practice (Sutton and Rao 2014)—​then this in and of itself adds fragility. Here we therefore understand scalability as the ability to change in both directions; that is, both up and down.6 In contrasting big and scale we arrive at a key insight. Big typically possesses a degree of slack, which Weinstock and Goodenough (2006) call the “ability to handle increased workload (without adding resources to a system).” A  big power plant, for example, rarely operates at full capacity. If demand were to increase from one segment of the day to another, the power plant can be ramped up to meet some or all of the added demand. However, this limited slack is different from true scalability. Thus, although the big power plant might be able to meet some incremental demand in a spatially, temporally, and relationally narrow field, it cannot effortlessly be scaled up (or scaled back down) to resolve a national or global energy crisis. Linking big, scalability, and fragility, we therefore advance the following: Proposition 12. Fragility arises when big is forced into doing what was best left to the scalable.

 

Big Is Fragile    71

4.3  Fragility in Action: Evidence from Large Dams These twelve propositions about fragility are based on a literature study. We now test the propositions against evidence from capital investments in 245 large dams. Our study of large dams began as an inductive enquiry into an underresearched question: will the brisk building boom of hydropower megadams underway from China to Brazil yield a positive return? Our previous effort (Ansar et al. 2014) found strong evidence that most large dams were too costly and took too long to build to deliver a positive risk-​adjusted return. Our empirical results motivated us to begin theory development that would help us answer why investments in large dams might be particularly prone to what we have called “investment fragility;” that is, for the benefit–​cost ratio to fall below 1. Figure 4.3 presents an overview of the dataset by regional location of the dams, wall height, project type, vintage, and actual project cost. With a total value of $353 billion (2010 prices) built between 1934 to 2007 on five continents in sixty-​five different countries, our dataset on large dams is the largest of its kind. All large dams for which valid and reliable cost and schedule data could be found were included in the study. The data and the inductive study are described in Ansar et al. (2014).

4.3.1 Why Study Big Dams? We find that large dams serve a particularly useful empirical setting to develop theory on investment fragility, for the following reasons. First, big dams are archetypical megaprojects. Dams are bespoke, site-​specific constructions that have large physical proportions, require mobilization of vast quantities of inputs (materials, land, labor, or physical equipment), entail huge up-​front financial outlays, generate a large number of unit of outputs, take a long time to build, last a long time, are spatially fixated, and are highly complex not only in terms of number of constituent parts but also in terms of high interdependencies between constituent parts. Large dams typically also impact large numbers of people and the environment in their construction, operation, and eventual removal. Second, dams are indivisible and discrete assets. A 90% complete dam is as valueless as a dam not built at all. For this reason, the physical scope and costs associated with a dam are methodologically well-​defined and therefore particularly well-​suited for like-​ for-​like comparisons between planned and actual outcomes. Third, the main part of the whole-​life costs of a dam are rendered up front during the construction phase. Unlike thermal power plants, dams do not require large variable costs in subsequent time periods for feedstock. There is a degree of transparency possible with the cash flows (or streams of costs and benefits) associated with dams that is much more difficult to establish for other big capital investments.

 

72    Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn Location

Size—dam wall height (m)

South Asia 25 Europe 29 Africa 29 40

≥150 East Asia 72

30–44

50 Latin America

North America

15–29

100–149

60–99

45–59

Project vintage

Project type Irrigation & other 59 61

1990–2007

1934–1949

Hydropower 97

1980–1989

1950–1969

89 1970-1979

Multipurpose (with hydropower)

Actual project cost (2010 USD millions), percent 12.5% 10.0% 7.5% 5.0% 2.5% 0.0% 10

1,000 Millions of 2010 US dollars

40,000

Figure  4.3  Sample distribution of 245 large dams across five continents (1934–​2007), worth US$353 billion (2010 prices). (From Ansar et al. 2014.)

Finally, results from large dams are generalizable to other big ventures. Large dams are a widely studied engineering problem, or what conventional theory might consider “a standardized production technology” (Sidak and Spulber 1997), generating basic services, such as electricity or water, as outputs with seemingly established demand trends. Intuition would suggest that the overall planning uncertainties ought to be more limited in large dams than, for example, big capital investments based on revolutionary new technologies. A discovery of systemic errors in the building of dams would be indicative that the problems of investment fragility will be even more severe for less standardized capital investments.

 

Big Is Fragile    73

4.3.2 What Happens to Big Dams? Proposition 10 suggested that if a system or process is systematically delivering poor outcomes it is an indicator of fragility. Specifically, we are interested in testing whether benefit–​cost ratios fall below 1.

4.3.2.1 Cost Performance With respect to cost overruns, we make the following observations:7 • Three out of every four large dams suffered a cost overrun in constant local currency terms. • Actual costs were on average 96% higher than estimated costs (median 27%; IQR 0.86). The evidence is overwhelming that costs are systematically biased toward underestimation and overrun (Mann-​Whitney-​Wilcoxon U = 29646, p < 0.01); the magnitude of cost underestimation is larger than the error of cost overestimation (p < 0.01). The skew is towards adverse outcomes (that is, going over budget). • Graphing the dams’ cost overruns reveals a long tail, as shown in Figure 4.4; the actual costs more than double for two out of every ten large dams and more than triple for one out of every ten dams. The long tail suggests that planners have difficulty in establishing probabilities of events that happen far into the future. (Taleb [2007] 2010: 284)

Density trace

30%

20%

Median Mean

10%

0% 0%

250%

500% Cost overrun

750%

5,142%

Figure 4.4  Density trace of actual/​estimated cost (costs overruns) in constant local currency terms with the median and mean (N = 245). (From Ansar et al. 2014.)

 

74    Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn

4.3.2.2 Schedule Performance Not only are large dams costly and prone to systematic and severe budget overruns; they also take a long time to build.8 Large dams on average take 8.6 years. With respect to schedule slippage, we make the following observations: • Eight out of every ten large dams suffered a schedule overrun. • Actual implementation schedule was on average 44% (or 2.3 years) higher than the estimate (median 27%, or 1.7 years) as shown in Figure 4.5. A schedule overrun is detrimental to the benefit–​cost ratio, as it delays when much needed benefits come on line. This decreases the net present value of future benefits. Even without a cost overrun, a schedule delay in and of itself can cause investment fragility. As the bulk of the costs of a big dam are incurred up front they are not as sensitive to the discount rate as the benefits, which arrive farther in the future. • Like cost overruns, the evidence is overwhelming that implementation schedules are systematically biased towards underestimation (Mann-​Whitney-​Wilcoxon U = 29161, p < 0.01); the magnitude of schedule underestimation (that is, schedule slippage) is larger than the error of schedule overestimation (p