Managing project complexity: A study into adapting early project phases to improve project performance in large engineering projects

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Managing project complexity

A study into adapting early project phases to improve project

performance in large engineering projects

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Managing project complexity

A study into adapting early project phases to improve project

performance in large engineering projects

Proefschrift

ter verkrijging van de graad van doctor aan de Technische Universiteit Delft;

op gezag van de Rector Magnificus prof. ir. K.C.A.M. Luyben; voorzitter van het College voor Promoties

in het openbaar te verdedigen op dinsdag 15 november 2011 om 12.30 uur door

Maria Gerridina Catharina BOSCH-REKVELDT werktuigkundig ingenieur

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Dit proefschrift is goedgekeurd door de promotoren: Prof. dr. ir. A. Verbraeck

Prof. dr. H.L.M. Bakker Copromotor: Dr. ir. H.G. Mooi

Samenstelling promotiecommissie: Rector Magnificus, voorzitter

Prof. dr. ir. A. Verbraeck, Technische Universiteit Delft, promotor Prof. dr. H.L.M. Bakker, Technische Universiteit Delft, promotor Dr. ir. H.G. Mooi, Technische Universiteit Delft, copromotor Prof. L. Crawford DBA, Bond University

Prof. dr. ir. J.I.M. Halman, Universiteit Twente

Prof. mr. dr. J.A. de Bruijn, Technische Universiteit Delft Prof. dr. P. Storm, Open Universiteit Nederland

Prof. dr. C.P. van Beers, Technische Universiteit Delft, reservelid

Cover design by Marian Bosch-Rekveldt, using tagxedo.com for the word cloud. Printed by Ipskamp Drukkers BV.

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, electronic, mechanical, photocopying, recording, or otherwise, without the prior consent of the author.

ISBN 978-94-91005-00-8

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Acknowledgement

Achteraf moet ik concluderen dat ik eigenlijk niet wist waar ik aan begon: wat een project! In november 2006 begon ik mijn promotieonderzoek in het Delft Centrum voor Projectmanagement (DCP) aan de faculteit TBM van de TU Delft. Er ging een wereld voor me open: de boeiende wereld van sociaal wetenschappelijk onderzoek. Projectmanagement had ik al enige jaren in praktijk gebracht, nu mocht ik op zoek naar de achtergrond ervan. Deze zoektocht ging, zoals het een zoektocht betaamt, met vallen en opstaan, maar ik heb mijn weg gevonden, resulterend in dit proefschrift.

Veel mensen hebben mij ondersteund bij het tot stand komen van dit proefschrift en deze mensen wil ik dan ook heel hartelijk bedanken. Ten eerste mijn begeleidingscommissie: promotor Alexander Verbraeck (altijd een scherpe en kritische blik), promotor Hans Bakker (zeer praktische inslag en de bepalende link naar het NAP netwerk) en copromotor Herman Mooi (zonder jou was ik hier niet aan begonnen (sic!) en had ik het al helemaal niet afgerond). Heren, veel dank voor alle constructieve, chaotische en verwarrende discussies! Ten tweede wil ik iedereen bedanken die heeft bijgedragen door het leveren van input en data: de bedrijven van het NAP netwerk, alle enquêterespondenten (Fase II en IV) en alle mensen die hebben meegewerkt aan de interviews (Fase I en III). Daarnaast wil ik ook de studenten noemen die ik heb begeleid in hun afstudeeronderzoek, dat al dan niet een directe relatie had met mijn promotieonderzoek (Tim, Yuri, Gerbert, Roald, Sergio, Stephan, Jeroen, Jordy, Iris, Amin, Arsalan, Anne, Sjoerd, Freek en Jorden). Jullie directe betrokken-heid blijkt uit de gezamenlijke artikelen waarop een aantal hoofdstukken is gebaseerd. Door het sparren met een ieder van jullie heb ik enorme stappen voorwaarts kunnen zetten. Mijn collega’s bij TSE en de collega-minordocenten wil ik bedanken voor alle collegiale support. In het bijzonder wil ik noemen: Helen en El van het secretariaat (altijd aanwezig en behulpzaam), Claire en Elisa (vele zinvolle, gezellige en motiverende (eet)afspraken), Roland (boeiende ganggesprekken, van zeilen tot schaatsen tot werk gerelateerd), en ook de anderen op de gang: Patrick, Geerten, Victor, Cees, Sergey, Jafar, Fardad, Casper en Prap. Het belang van de gezamenlijke uitstapjes naar de koffieautomaat moet niet worden onderschat!

Ook wil ik mijn en onze vrienden en vriendinnen heel hartelijk bedanken: jullie waren vol belangstelling en begrip, ondanks de beperkte tijd die ik had in de afgelopen periode. De optimist in mij zegt dat het alleen maar weer beter kan worden…! Leden van het TBM-kelderkoor en alle “Connections”: veel dank voor de broodnodige muzikale afleiding! Mijn ouders, schoonouders, broers, zwagers en schoonzussen wil ik bedanken voor alle ondersteuning, op welke manier dan ook. Ik noem bijvoorbeeld het extra oppassen op Lieke en Nathan…enorm bedankt! Lieve Lieke, Lieve Nathan: ja, ik heb nu weer meer tijd voor poppen, DUPLO® en auto’s: mama’s boek is echt af!

Tenslotte, en hierbij geldt hoe cliché ook, “last but not least”: Hans! Je hebt me enorm ondersteund, begrip gehad en meer dan eens ingesprongen als ik weer eens belde of ik nog even door kon werken. Lieve Hans: veel dank voor je geduld, je flexibiliteit, voor alles. Ik hoop dat ik alle “brownie points” die je hebt verdiend terwijl ik mijn proefschrift schreef ooit kan compenseren.

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Table of content

ACKNOWLEDGEMENT...I LIST OF FIGURES ... VIII LIST OF TABLES ... IX LIST OF ABBREVIATIONS ... XI

CHAPTER 1 ... 1

INTRODUCTION ... 1

1.1 WHY DO CAPITAL PROJECTS STILL FAIL, WHAT CAN WE DO ABOUT IT? ... 2

1.2 RESEARCH OBJECTIVE, RESEARCH QUESTIONS AND SCOPE ... 3

1.3 RESEARCH APPROACH ... 5

1.3.1 Research in social science ... 5

1.3.2 Methods applied in this research ... 7

1.4 SCIENTIFIC AND SOCIAL RELEVANCE ... 11

1.5 DISSERTATION OUTLINE ... 11

CHAPTER 2 ... 13

LITERATURE REVIEW ... 13

2.1 WHAT IS A PROJECT? ... 13

2.2 THE DEVELOPMENT OF PROJECT MANAGEMENT ... 14

2.3 TRENDS IN PROJECT MANAGEMENT RESEARCH ... 18

2.4 HOW TO ASSESS PROJECT PERFORMANCE? ... 20

2.4.1 Project success dimensions ... 21

2.4.2 Operationalization of project success ... 21

2.4.3 Critical success factors ... 23

2.5 A CLOSER LOOK INTO PROJECT FRONT-END DEVELOPMENT ... 24

2.6 CONTINGENCY THEORY ... 28

2.6.1 History ... 28

2.6.2 Structural contingency research paradigm ... 29

2.6.3 Developments and criticisms to structural contingency theory ... 30

2.6.4 Towards a contingency approach to project management ... 30

2.7 PROJECT COMPLEXITY ... 34

2.7.1 Defining project complexity ... 34

2.7.2 Concepts of project complexity ... 35

2.7.3 Uncertainty, project risk and project complexity ... 37

2.7.4 Classification of projects based on their complexity ... 39

2.8 PROJECT RELATED STAKEHOLDERS – EXTERNAL & INTERNAL ... 41

2.9 STUDIES ON ADAPTING PROJECT MANAGEMENT TO PROJECT CHARACTERISTICS ... 42

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CHAPTER 3 ... 47

EXPLORATORY CASE STUDIES ... 47

3.1 METHODS ... 47

3.1.1 Case study design ... 48

3.1.2 Case study protocol ... 48

3.1.3 Case selection ... 50

3.1.4 Data analysis ... 50

3.2 CASE 1:DESIGN, CONSTRUCT AND START-UP OF A CHEMICAL PLANT (GOOD PROJECT PERFORMANCE) ... 52

3.2.1 Brief case description ... 52

3.2.2 Interview results on project complexity ... 52

3.2.3 Interview results on front-end activities ... 54

3.2.4 Overall case conclusion ... 55

3.3 CASE 2: DEVELOPMENT AND CONSTRUCTION OF A NEW FACILITY (GOOD PROJECT PERFORMANCE) ... 55

3.4 CASE 3: DESIGN AND CONSTRUCT OF CHEMICAL PLANT (MARGINAL PROJECT PERFORMANCE) ... 58

3.5 CASE 4:MODIFICATION OF CURRENT FACILITY (POOR PROJECT PERFORMANCE) ... 62

3.6 CASE 5: DEVELOPMENT OF NEW OFFSHORE ENERGY FACILITY (GOOD PROJECT PERFORMANCE) ... 65

3.7 CASE 6:CONSTRUCTION OF NEW FACILITY (MARGINAL PROJECT PERFORMANCE) .... 69

3.8 CROSS CASE ANALYSIS ... 72

3.8.1 In which way do project professionals consider their project as complex? . 72 3.8.2 Adapting the front-end development phase to the particular complexity? ... 74

3.8.3 Classification of projects according to their complexity level? ... 75

3.8.4 Dealing with project complexity in the front-end phase ... 75

3.9 DISCUSSION ... 76

3.9.1 The engineer as a project manager ... 77

3.9.2 Dynamics of project complexity ... 77

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CHAPTER 4 ... 79

GRASPING PROJECT COMPLEXITY: THE TOE FRAMEWORK ... 79

4.1 RESEARCH APPROACH ... 80

4.2 PROJECT COMPLEXITY ELEMENTS FROM LITERATURE... 80

4.2.1 Gathering elements from literature ... 80

4.2.2 Elaborating on the proposed structure for the framework... 81

4.3 PROJECT COMPLEXITY ELEMENTS FROM CASE STUDIES ... 84

4.4 THE TOE FRAMEWORK FOR PROJECT COMPLEXITY IN LARGE ENGINEERING PROJECTS ……….. 87

4.5 DISCUSSING THE FRAMEWORK ... 91

4.6 USE AND FURTHER DEVELOPMENT OF THE TOE FRAMEWORK ... 92

4.7 CONCLUSION & RECOMMENDATIONS ... 93

CHAPTER 5 ... 95

NAP SURVEY STUDY ... 95

5.1 METHODS ... 95

5.1.1 Survey ... 95

5.1.2 Sample ... 96

5.1.3 Validity ... 96

5.2 SURVEY DESIGN ... 97

5.2.1 Identifying the project’s complexity ... 97

5.2.2 What was done in the front-end phase of the project? ... 98

5.2.3 How did the project perform? ... 101

5.3 DATA TREATMENT ... 102

5.3.1 Data collection ... 102

5.3.2 Data analysis ... 103

5.4 GENERAL SURVEY RESULTS ... 104

5.4.1 The respondents ... 104

5.4.2 Project characterization ... 105

5.4.3 Project driver(s) ... 105

5.4.4 Project performance ... 106

CHAPTER 6 ... 109

EVALUATING PROJECT COMPLEXITY ... 109

6.1 ANALYSIS OF SURVEY DATA ... 110

6.2 CORRELATIONS BETWEEN PROJECT COMPLEXITY AND PROJECT PERFORMANCE ... 110

6.3 CORRELATIONS BETWEEN ELEMENT SCORES AND PERCEIVED COMPLEXITY ... 112

6.3.1 Correlation of T-elements and perceived complexity ... 117

6.3.2 Correlation of O-elements and perceived complexity ... 119

6.3.3 Correlation of E-elements and perceived complexity ... 122

6.3.4 Summary of element evaluation & proposal for adaptations to the TOE framework ... 124

6.4 COMPLETENESS OF THE TOE FRAMEWORK ... 127

6.4.1 Most complex element(s) in the project ... 127

6.4.1 What is lacking in the TOE framework? ... 130

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6.6 AGGREGATED SCORES FOR T,O AND E COMPLEXITY ... 133

CHAPTER 7 ... 137

EVALUATING FRONT-END ACTIVITIES ... 137

7.1 HIGH LEVEL RELATIONS BETWEEN COMPLEXITY, FRONT-END ACTIVITIES AND PROJECT PERFORMANCE ... 138

7.1.1 Results total complexity, VIP effort and project performance ... 139

7.1.2 Results for dimensions of complexity, VIP effort and project performance140 7.2 ACTIVITIES TYPICALLY PERFORMED IN THE FRONT-END PHASE ... 142

7.2.1 Activities in front-end: Value Improving Practices (VIPs) ... 142

7.2.2 Other activities in front-end development ... 144

7.3 DIRECT RELATIONS WITH PROJECT PERFORMANCE ... 146

7.4 MODERATED RELATIONSHIPS ... 148

7.4.1 Contingency theory ... 148

7.4.2 Analysis framework ... 149

7.4.3 Relations between front-end development and project complexity ... 150

7.4.4 Subgroup analysis to test for moderated relationships ... 153

7.5 SUMMARY OF RELATIONS FOUND BETWEEN FRONT-END ACTIVITIES, COMPLEXITY AND PROJECT PERFORMANCE ... 157

7.6 WHAT IS THE INFLUENCE OF THE RESPONDENTS’ ROLE? ... 160

7.6.1 Respondent’s role in the project ... 161

7.6.2 Role of the respondent’s company ... 163

7.7.1 Methodological limitations ... 167

7.7.2 Comparison with literature ... 167

7.7.3 Managerial implications ... 168

CHAPTER 8 ... 171

HOW DO VALUE IMPROVING PRACTICES CONTRIBUTE TO PROJECT PERFORMANCE? ... 171

8.1 METHODS ... 172

8.1.1 Case study design ... 172

8.1.2 Case selection ... 172

8.1.3 Case protocol, validity and analysis set up ... 174

8.2 THE 5 CASES AT FIRST GLANCE ... 175

8.2.1 Case A: A construction project by an owner organization (good project performance) ... 175

8.2.2 Case B: A turnaround project by a contractor (good project performance)……… 176

8.2.3 Case C: A public civil engineering and construction project by a contractor (very poor project performance) ... 177

8.2.4 Case D: A plant modification project by a contractor (poor project performance) ... 179

8.2.5 Case E: A Greenfield design and construction project by an owner (good project performance) ... 180

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8.3 CROSS CASE ANALYSIS ... 181

8.3.1 Findings on team design ... 182

8.3.2 Findings on goal setting... 183

8.3.3 Findings on monitoring project goals ... 183

8.3.4 Findings on risk management ... 184

8.3.5 Findings on external benchmarking ... 185

8.3.6 Findings on operations implementation planning ... 185

8.3.7 Comparing the 5 cases ... 186

8.4 TEAM INTEGRATION PAYS OFF ... 186

8.5 CONCLUSION AND RECOMMENDATIONS ... 187

CHAPTER 9 ... 189

VALIDATING THE TOE FRAMEWORK FOR POTENTIAL USE... 189

9.1 FINAL TOE FRAMEWORK ... 190

9.2 SURVEY DESIGN ... 190

9.3 DATA TREATMENT ... 192

9.3.1 Data collection ... 192

9.3.2 Data analysis ... 194

9.4 SURVEY RESULTS ... 194

9.4.1 Respondents work experience ... 194

9.4.2 Evaluation of the TOE framework ... 195

9.4.3 How to deal with complexity? ... 200

9.4.4 Application of the TOE framework ... 205

9.4.5 Added value of the TOE complexity framework ... 208

9.4.6 Further development of the TOE complexity framework ... 210

9.5 DISCUSSION AND CONCLUSIONS ... 211

9.5.1 The TOE complexity framework ... 212

9.5.2 Treating project complexity ... 213

9.5.3 An owner’s perspective versus a contractor’s perspective? ... 214

9.5.4 Foreseen use of the framework ... 214

9.5.5 Further development of the TOE framework ... 215

CHAPTER 10 ... 217

DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS... 217

10.1.1 Validity of the current research ... 217

10.1.2 Scientific contribution ... 219

10.1.3 Limitations of the research ... 220

10.2 CONCLUSIONS ... 221

10.2.1 Answers to the research questions ... 221

10.2.2 Overall conclusions ... 224

10.3 RECOMMENDATIONS ... 226

10.3.1 Recommendations for use of the results in project practice ... 226

10.3.2 Research recommendations ... 227

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APPENDICES ... 243

APPENDIXA:LIST OF INTERVIEW QUESTIONS EXPLORATIVE CASE STUDIES (CHAPTER 3) ……….. .. 244

APPENDIXB:INTERNET SURVEY PHASEII(CHAPTER 5) ... 247

APPENDIXC:TRANSLATION TABLE:TOE ELEMENTS & SURVEY QUESTIONS (CHAPTER 5) ………….. ... 256

APPENDIXD:CORRELATION RESULTS TOE ELEMENTS & DETAILED ANALYSIS (CHAPTER 6)…………. ... 259

D.1: Correlation of T-elements and perceived complexity ... 268

D.2: Correlation of O-elements and perceived complexity... 274

D.3: Correlation of E-elements and perceived complexity ... 285

D.4: Summary of element evaluations ... 292

APPENDIXE:REQUIRED ELEMENT TRANSFORMATIONS (CHAPTER 6) ... 294

APPENDIXF:INTERVIEW QUESTIONS PHASEIII(CHAPTER 8) ... 296

APPENDIXG:INTERNET SURVEY PHASEIV(CHAPTER 9) ... 299

APPENDIX H:ELEMENTS MOST/LEAST CONTRIBUTING TO PROJECT COMPLEXITY PHASE IV(CHAPTER 9) ... 304

SUMMARY ... 307

SAMENVATTING ... 313

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List of figures

FIGURE 1.1:THE WHEEL OF SCIENCE (WALLACE,1971) ... 6

FIGURE 1.2:MODEL PROJECT COMPLEXITY / FRONT-END ACTIVITIES / PROJECT PERFORMANCE ... 7

FIGURE 1.3:OVERVIEW OF THE EMPIRICAL PART OF THE RESEARCH ... 10

FIGURE 1.4:DATA COLLECTION WITHIN THE NAP NETWORK – COMPANY INVOLVEMENT ... 10

FIGURE 1.5:OVERVIEW OF THE DISSERTATION ... 12

FIGURE 2.1:THE INFLUENCE OF FRONT-END DEVELOPMENT (PHASE 1,2,3) ON THE VALUE OF A PROJECT (HUTCHINSON &WABEKE,2006) ... 25

FIGURE 2.2:OVERVIEW OF DIMENSIONS OF PROJECT COMPLEXITY (WILLIAMS,2002) ... 36

FIGURE 2.3:STAKEHOLDER TYPOLOGY ACCORDING TO (MITCHELL ET AL.,1997) ... 41

FIGURE 3.1:SUMMARY OF SELECTED CASES, CASE 1 TO 6 ... 50

FIGURE 4.1:“NEW” AND TOTAL NUMBER OF ELEMENTS MENTIONED BY THE INTERVIEWEES. ... 85

FIGURE 5.1:TIME SPENT TO COMPLETE THE SURVEY ... 103

FIGURE 5.2:YEARS OF WORK EXPERIENCE (LEFT) AND EXPERIENCE AS PROJECT MANAGER (RIGHT) ... 104

FIGURE 5.3:PROJECT DRIVERS: QUALITY, SCHEDULE, COST ... 106

FIGURE 5.4:CUMULATIVE SCORE FOR PROJECT PERFORMANCE (N=54) ... 107

FIGURE 5.5:NUMBER OF CASES AGAINST PERFORMANCE SCORES (N=54) ... 107

FIGURE 6.1:SURVEY RESULTS: PERCEIVED COMPLEXITY (N=67 FOR T AND O,N=66 FOR E) ... 113

FIGURE 6.2:ANSWERS RELATED TO APPLICATION OF A COMPLEXITY FRAMEWORK ... 132

FIGURE 6.3:ANSWERS RELATED TO THE BENEFIT OF APPLYING A COMPLEXITY FRAMEWORK AND ITS FORESEEN USE TO CREATE AWARENESS ABOUT PROJECT COMPLEXITY AMONGST ITS STAKEHOLDERS ... 132

FIGURE 6.4:USE OF THE COMPLEXITY FRAMEWORK IN DIFFERENT PROJECT PHASES ... 133

FIGURE 7.1:C(COMPLEXITY) AS A MODERATOR OF THE RELATIONSHIP BETWEEN A(FRONT-END ACTIVITIES) AND B(PERFORMANCE) ... 149

FIGURE 7.2:OVERVIEW OF POTENTIAL RELATIONSHIPS ... 150

FIGURE 7.3:RELATIONSHIPS INFLUENCING PROJECT PERFORMANCE: RESULTS CURRENT DATASET ... 158

FIGURE 7.4:RELATIONSHIPS COMPLEXITY, FRONT-END ACTIVITIES AND PERFORMANCE IN MORE DETAIL (DASHED BLOCK FROM FIGURE 7.3) ... 159

FIGURE 8.1:OVERVIEW OF SELECTED CASES: SCORES ON PROJECT PERFORMANCE ... 174

FIGURE 9.1:TIME SPENT TO COMPLETE THIS SURVEY ... 193

FIGURE 9.2:YEARS OF EXPERIENCE AS PROJECT MANAGER (LEFT) AND AT THE COMPANY (RIGHT) ... 194

FIGURE 9.3:CUMULATIVE ELEMENT SCORES,N=64 ... 195

FIGURE 9.4:CUMULATIVE ELEMENT SCORES PER GROUP, DISPLAYED IN AVERAGE NORMALIZED SCORES ... 199

FIGURE 9.5:HOW TO DEAL WITH PROJECT COMPLEXITY (%): MOST CONTRIBUTING T-ELEMENTS ... 201

FIGURE 9.6.HOW TO DEAL WITH PROJECT COMPLEXITY (%): MOST CONTRIBUTING O-ELEMENTS ... 203

FIGURE 9.7:HOW TO DEAL WITH PROJECT COMPLEXITY (%): MOST CONTRIBUTING E-ELEMENTS ... 204

FIGURE 9.8:VISUAL REPRESENTATION OF THE FINAL TOE FRAMEWORK ... 213

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List of tables

TABLE 2.1:DIRECTIONS FOR SOLVING PROJECT MANAGEMENT PROBLEMS FROM DIFFERENT PERSPECTIVES

(SHENHAR &DVIR,2007A) ... 18

TABLE 2.2:SUCCESS MEASURES (SHENHAR ET AL.,2001) ... 22

TABLE 2.3:CRITICAL SUCCESS FACTORS, DIFFERENT LITERATURE SOURCES ... 24

TABLE 2.4:NAMES FOR TYPICAL FED PHASES ... 26

TABLE 2.5:STANDARD RECOMMENDED FRONT-END ACTIVITIES IN THE PROCESS INDUSTRY: ... 27

TABLE 2.6:VALUE IMPROVING PRACTICES AS IDENTIFIED BY IPA AND CII ... 28

TABLE 2.7:OVERVIEW OF CONTINGENCY FACTORS FOUND IN LITERATURE, DIVIDED INTO 5 MAIN CATEGORIES AND A SIXTH CATEGORY “OTHERS” ... 32

TABLE 3.1:INTERVIEWEES AND THEIR INVOLVEMENT IN THE PROJECT ... 52

TABLE 3.2:SUMMARY INTERVIEW RESULTS ON PROJECT COMPLEXITY, PROJECT 1 ... 53

TABLE 3.3:SUMMARY INTERVIEW RESULTS ON FED, PROJECT 1 ... 54

TABLE 3.14:RELEVANT FRONT-END ASPECTS ... 76

TABLE 4.1:ELEMENTS CONTRIBUTING TO PROJECT COMPLEXITY FROM LITERATURE SOURCES ... 82

TABLE 4.2:ELEMENTS (49) CONTRIBUTING TO PROJECT COMPLEXITY BASED ON 6 CASES,18 INTERVIEWS . 86 TABLE 4.3:SUBCATEGORIES OF TOE ... 87

TABLE 4.4:TOE FRAMEWORK (50 ELEMENTS IN TOTAL) ... 88

TABLE 5.1:OVERVIEW OF VIPS /BEST PRACTICES AND SELECTION FOR INCLUSION IN THIS STUDY ... 99

TABLE 5.2:EXPLANATION OF VIPS CONSIDERED IN THE SURVEY ... 100

TABLE 5.3:OTHER FRONT-END ACTIVITIES CONSIDERED IN THE SURVEY (BASED ON CHAPTER 3) ... 101

TABLE 6.1:SIGNIFICANT CORRELATIONS BETWEEN PROJECT PERFORMANCE AND PROJECT COMPLEXITY.... 111

TABLE 6.2:SIGNIFICANT CORRELATIONS BETWEEN PROJECT PERFORMANCE AND PROJECT COMPLEXITY ELEMENTS ... 112

TABLE 6.3:INTER-CORRELATIONS FOR THE PERCEIVED COMPLEXITY SCORES FOR T,O AND E COMPLEXITY 113 TABLE 6.4:SPEARMAN CORRELATIONS BETWEEN ... 115

TABLE 6.5:CORRELATION RESULTS T-ELEMENTS ... 118

TABLE 6.6:CORRELATION RESULTS O-ELEMENTS ... 120

TABLE 6.7:CORRELATION RESULTS E-ELEMENTS ... 123

TABLE 6.8:TOE WITH PROPOSED ADAPTATIONS ... 126

TABLE 6.9:THE MOST COMPLEX ELEMENTS AND THEIR LINK TO THE TOE FRAMEWORK ... 128

TABLE 6.10:ASPECTS OF PROJECT COMPLEXITY NOT IN TOE FRAMEWORK IN VIEW OF RESPONDENTS ... 130

TABLE 6.11:RELIABILITY STATISTICS ... 134

TABLE 6.12:CORRELATIONS BETWEEN AGGREGATED COMPLEXITY SCORES AND PERCEIVED COMPLEXITY .. 134

TABLE 7.1:DESCRIPTIVE STATISTICS (VIP EFFORT, TOTAL COMPLEXITY, ON PROJECT PERFORMANCE) ... 139

TABLE 7.2:DESCRIPTIVE STATISTICS (VIP EFFORT,T-COMPLEXITY, ON PROJECT PERFORMANCE) ... 140

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TABLE 7.4:DESCRIPTIVE STATISTICS (VIP EFFORT,E-COMPLEXITY, ON PROJECT PERFORMANCE) ... 141

TABLE 7.5:SURVEY RESULTS OF VIP QUESTIONS ... 143

TABLE 7.6:SURVEY RESULTS OF QUESTIONS ABOUT THE “OTHER” FRONT-END ACTIVITIES ... 145

TABLE 7.7:OVERVIEW OF SIGNIFICANT CORRELATIONS ... 146

TABLE 7.8:SIGNIFICANT CORRELATIONS BETWEEN PROJECT PERFORMANCE AND FRONT-END ACTIVITIES .. 147

TABLE 7.9:SIGNIFICANT CORRELATIONS BETWEEN COMPLEXITY AND FRONT-END ACTIVITIES ... 152

TABLE 7.10:SIGNIFICANT CORRELATIONS WITHIN SUBGROUPS ... 155

TABLE 7.11:KRUSKAL-WALLIS TEST RESULTS: SIGNIFICANT DIFFERENCES BETWEEN PROJECT MANAGERS, BUSINESS REPRESENTATIVES AND TEAM MEMBERS (N=67) ... 161

TABLE 7.12:KRUSKAL-WALLIS TEST RESULTS: SIGNIFICANT DIFFERENCES BETWEEN OWNERS,(MANAGING) CONTRACTORS, SUBCONTRACTORS (N=60)... 164

TABLE 8.1:CASE SELECTION PROCEDURE ... 172

TABLE 8.2:SUMMARY OF SELECTED CASES ... 173

TABLE 8.3:SUMMARY OF CASE RESULTS ... 182

TABLE 9.1:FINAL TOE FRAMEWORK,47 ELEMENTS IN TOTAL ... 191

TABLE 9.2:SURVEY QUESTION ON ADDITIONAL EFFORT FOR ELEMENT(S) MOST CONTRIBUTING TO PROJECT COMPLEXITY... 192

TABLE 9.3:OVERVIEW OF RESPONSES ... 193

TABLE 9.4:MOST CONTRIBUTING ELEMENTS (MAX 3 SELECTIONS PER PARTICIPANT) ... 196

TABLE 9.5:LEAST CONTRIBUTING ELEMENTS (MAX 3 SELECTIONS PER PARTICIPANT) ... 197

TABLE 9.6:SIGNIFICANT RESULTS FOR MANN-WHITNEY TEST (DISTINGUISHING OWNERS AND CONTRACTORS) ... 198

TABLE 9.7:SUMMARY OF SURVEY FINDINGS ON APPLICATION OF THE TOE FRAMEWORK ... 206

TABLE 9.8:SUMMARY OF SURVEY FINDINGS ON ADDED VALUE OF THE TOE COMPLEXITY FRAMEWORK ... 208

TABLE D.1:CORRELATIONS T-ELEMENTS AND PERCEIVED COMPLEXITY ... 268

TABLE D.2:CORRELATIONS O-ELEMENTS AND PERCEIVED COMPLEXITY ... 276

TABLE D.3:CORRELATIONS E-ELEMENTS AND PERCEIVED COMPLEXITY ... 285

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List of abbreviations

ACAT Acquisition Categorisation Framework ADM Asset Development Manager

APM Association of Project Management ANOVA Analysis of Variance

BDP Basic Design Package

CAPEX Capital Expenditure

CIFTER Crawford-Ishikura Factor Table for Evaluating Roles CII Construction Industry Institute

CO Change Order

CoPS Complex Products and Systems CPM Critical Path Method

CRC Cooperative Research Centre CRI Construction Research Innovation DCP Delft Centre for Project Management DMO Defence Materiel Organisation

ENAA Engineering Advancement Association of Japan EPC Engineering Procurement Construction

EPCC Engineering Procurement Construction Commissioning EPCM Engineering Procurement Construction Management

FED Front-End Development

FEL Front-End Loading

FID Final Investment Decision

FPO Future Plant Owner

GAPPS Global Alliance for Project Performance Standards HS(S)E Health, Safety, Security, Environment

JV Joint Venture

IBC Industry Benchmarking Consortium

ICB IPMA Competency Baseline

IPA Independent Project Analysis

IPMA International Project Management Association NAP Nederlands Apparatenbouw en Procesindustrie NCTP Novelty, Complexity, Technology, Pace OIP Operations Implementation Planning PERT Program Evaluation Review Technique PM Project Manager / Project Management PMI Project Management Institute

UCP Uncertainty, Complexity, Pace

USAF US Air Force

SHE Safety, Health, Environment TOE Technical, Organizational, External VIP Value Improving Practice

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Chapter 1 Introduction

Capital projects delivered us the large facilities and assets needed to live our modern lives. Energy supply, infrastructure, transportation, telecommunication, buildings, and consumer electronics: all were established as a tangible result of projects, in one way or another. Benchmarking data across all industry sectors, however, is indicating that there is still a problem with the successful delivery of capital projects (IPA, 2011). Amongst 300 global megaprojects (budget for each project larger than 1 billion 2010 US$), 65% failed to meet their business objectives (Merrow, 2011). Investigating about 600 projects in business, government and nonprofit sectors, with budgets between $40.000 and $2.5 billion, Shenhar and Dvir reported a failure of even 85% when looking at meeting time and budget goals (Shenhar & Dvir, 2007b). Hence across the board, from small projects to mega projects, serious problems are reported.

Specific examples of projects that don’t progress according to their plans (money wise or time wise) are numerous; think for some examples from the Netherlands of the construction of the underground “Noord-Zuidlijn” in Amsterdam, the renovation of the “Rijksmuseum” in Amsterdam, the construction of the cargo railway “Betuweroute” between Rotterdam and Germany, and the implementation of new ICT services for the Dutch Police Forces. All these projects are late and over budget and in case of the new ICT-services project even without properly meeting the project scope (Stuiveling & van Schoten, 2011).

Despite a rather poor track record of project performance, the “projectification” of the world is continuing (Maylor, Brady, Cooke-Davies, & Hodgson, 2006). With the capital market looking for predictability and strong returns, poor project performance in terms of delivering late and above budget is not acceptable (Mc Kenna, Wilczynski, & van der Schee, 2006). Therefore, improving project performance is of vital importance.

Capital projects, as introduced above, can be considered as projects that aim to deliver so-called complex products and systems (Hobday, 1998). Such complex products and systems (CoPS) are defined as “high cost, engineering-intensive products, systems, networks and constructs (…) (where) the term ‘complex’ is used to reflect the number of customized components, the breadth of knowledge and skills required and the degree of new knowledge involved in production, as well as other critical product dimensions (p.690). Research into CoPS also shows the necessity to improve project performance (Barlow, 2000; Hobday, Rush, & Tidd, 2000).

This chapter sets the scene for the research undertaken. First, the research background is provided. Next, the research objective and research questions are formulated and the research scope is defined. How to answer these research questions within the scope is described subsequently in the research approach. Next, the relevance of the research is explained. To conclude this chapter, the structure of the dissertation is presented.

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1.1 Why do capital projects still fail, what can we do about it?

Project failure in terms of cost overrun and time delay is being investigated for years now (Flyvbjerg, Bruzelius, & Rothengatter, 2003; Hall, 1981; Morris & Hough, 1987; Sauser, Reilly, & Shenhar, 2009; Thamhain & Wilemon, 1986). Numerous reasons for such project failures can be found in project management literature. More than a decade ago, the Handbook of Project-Based Management already listed several pitfalls of project management (Turner, 1999):

- “Pitfalls in establishing the project (project plans are not aligned with business plans, procedures for managing projects are not defined, priorities are not communicated to parties involved, there is no shared vision)” (p. 74)

- “Pitfalls in project planning (plans developed on a single level, using cumbersome tools, creativity discouraged, unrealistic estimates)” (p. 75)

- “Pitfalls in organizing and planning (lack of co-operation, resource providers not committed, resources not available when required, management responsibility not defined, poor communication, technical vs project management)” (p. 77)

- “Pitfalls in control (purpose of control is not understood, progress not monitored against the plan, ineffective review meetings, responsibility without authority)” (p. 79)

These pitfalls are all in the management area and, in the words of Turner, can be considered as “management mistakes”. More often, managerial reasons are suggested to be a cause for project failure (Lindahl & Rehn, 2007; Sauser et al., 2009).

According to literature, another reason for project failure would be the increasing complexity of projects and underestimation of this complexity (Neleman, 2006; Williams, 2002, 2005). The complexity of projects is assumed to increase as a result of rapid changes in environment, increased product complexity and increased time pressure (Williams, 1999). Therefore research has been undertaken to better understand project complexity (Bosch-Rekveldt & Mooi, 2008; Dombkins & Dombkins, 2008; Geraldi & Adlbrecht, 2007; Hass, 2007; Maylor, Vidgen, & Carver, 2008; Vidal & Marle, 2008; Williams, 2002). At this stage, however, common understanding of the concept of project complexity is lacking. Research even expressed the need for “the development of new models and theories which recognize and illuminate the complexity of projects and project management, at all levels” (Winter, Smith, Morris, & Cicmil, 2006b), p. 642.

Given the high number of project management handbooks, such as (Cleland & King, 1983; Kerzner, 2003; Meredith & Mantel, 2006; Pinto, 1988, 2004; Turner, 2008; Turner & Simister, 2000), one could conclude that there is an enormous amount of knowledge on project management available to deliver projects on time and within budget. Other recent literature, however, still provides examples of “failed” projects: the RandstadRail project (Koppenjan, Veeneman, Van der Voort, Ten Heuvelhof, & Leijten, 2011), the Mars Climate Orbiter (Sauser et al., 2009) or the Channel Tunnel project (Chang & Ive, 2007). These studies have in common that they advocate for a broader approach in the management of projects, focused beyond the “old” project management control perspective. To improve the current situation, traditional project management approaches could be complemented by process approaches (de Bruijn, ten Heuvelhof, & in 't Veld, 2003) and program management approaches (Pellegrinelli, 2011).

Why would the traditional project management not be suitable for today’s projects? Nowadays, projects are performed in highly dynamic environments, involving multiple stakeholders with different perspectives and encountering technological challenges. Hence

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projects are characterized by uncertainties, whereas “the traditional, formal approach to project management is based on a predictable, fixed, relatively simple, and certain model” (Shenhar & Dvir, 2007b), p. 9. Similarly, most mainstream textbooks still “promote this normative view of the field” (Hodgson & Cicmil, 2006), p.2.

Where to look then for improvement in the field of project management? The good thing of a poor track record in current project performance is the potential room for improvement. The poor track record, however, also illustrates the difficulty to improve (…if the solution would have been easy, it probably already had been implemented…). Nevertheless, literature provides suggestions where to look for improvement in the field of project management in order to improve project performance.

Prominently, the importance of the front-end development (FED) phase for improving project performance is suggested (Artto, Lehtonen, & Saranen, 2001; Flyvbjerg et al., 2003; Morris, 1994; Morris, Crawford, Hodgson, Shepherd, & Thomas, 2006a; Thamhain & Wilemon, 1975). Particularly in early project phases (front-end phases), effort needs to be thoroughly spent in, amongst others, defining project goals, building the project team, assessing project risks and aligning stakeholders. Although the importance of thorough front-end development has been stressed for years now, the fact that projects still fail could be related to spending insufficient (and/or inadequate) effort in particular the early project phases (Kolltveit & Grønhaug, 2004).

Another prominent theme in literature is the fact that all projects require a specific, tailored management approach (Shenhar & Dvir, 2007a): project management could (should?) be made contingent upon the project’s context or environment (Engwall, 2003; Howell, Windahl, & Seidel, 2010; Sauser et al., 2009; Shenhar, 2001; Smyth & Morris, 2007; Williams, 2005). This basically means that based on certain project characteristics, the project management approach is to be adapted.

1.2 Research objective, research questions and scope

Given the need to improve project performance (Mc Kenna et al., 2006) , the increasing project complexity as one of the contributors to project failure in terms of overspent budget and late delivery (Williams, 2002, 2005), the importance of the front-end phase (Artto et al., 2001; Flyvbjerg et al., 2003; Morris, 1994; Morris et al., 2006a), and the potential of applying a contingency approach to project management (Engwall, 2003; Howell et al., 2010; Sauser et al., 2009; Shenhar, 2001; Smyth & Morris, 2007; Williams, 2005), we come to the threefold objective of this PhD research.

The first objective is to investigate what project complexity actually comprises and how it influences project performance. The second objective is to investigate how front-end activities could be adapted to the project’s complexity and how this influences project performance. The third objective is to investigate the relations between these variables (project complexity, front-end activities and project performance), amongst others by using a contingency approach. The aim is to come to an effective and sufficient front-end development phase, fitted to the project’s complexity. In this context effective means that the activities in the front-end phase will enable a good project performance in terms of meeting the technical specifications within cost and schedule estimates. Sufficient is referring to the fact that not too little, but also not too much effort should be spent in the front-end phase.

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The main research question to be answered is:

How could the front-end phase be adapted to the project’s complexity in order to improve project performance?

In order to answer this main research question; the following sub-questions are addressed: 1. What is project complexity as experienced by project professionals?

2. How can we characterize project complexity in large engineering projects? 3. How does project complexity influence project performance?

4. What are the relevant front-end activities to deal with project complexity? 5. How do front-end activities contribute to better project performance?

6. How can contingency theory be used to fit the front-end phase to the complexity of a project?

7. How could a framework to grasp project complexity be used to improve project performance?

To tackle a complex problem like this, it is wise to limit the scope. Therefore in this dissertation we focus on the process industry in the Netherlands. How can current projects in the process industry be characterized in very general terms? Such projects typically have a technological component, leading to technological as well as commercial risks. They have certain impact on the environment, either because it is a greenfield location (new facility, not so common) or because it is a brownfield location (extension or modification of existing facility, very common). A lot of parties are involved, including (sub)contractors, (local) communities and non-governmental organizations. Projects differ largely in size and content, ranging for example from several thousand Euro (small maintenance project) to over 1 billion Euro (major unique investment project). And last but not least, projects are performed by multidisciplinary project teams. These very diverse project characteristics, together with the earlier mentioned poor track record that also holds for this sector (IPA, 2011), suggests an interesting playing field for research into managing project complexity. Moreover, projects in the process industry can be characterized as projects that aim to deliver CoPS (Hobday et al., 2000): highly customized products with the involvement of multiple disciplines and parties.

More specifically, this research is focused on technologically complex engineering projects in the process industry, undertaken in dynamic environments with multiple stakeholders, with a budget between approximately 1 to 500 million Euro. The selected budget range was chosen because the projects under consideration should have some serious “content” (hence the lower range value was set to 1 million Euro), but not be overly unique (hence upper range value was set to 500 million Euro). The owner’s perspective is taken as a starting point, but in later stages of the research also the contractor’s perspective is included. The research is performed within the NAP network, which brings together companies from the entire value chain in the Dutch process industry, including engineering agencies and the academic community (NAP, 2009). It consists of about 100 member organizations. For the different stages of the research, different selections of companies are included. The interest of the NAP network in (improving) the front-end phase of projects is evident from their publications on the 2x2 principle: delivering projects twice as cost effective and twice as fast (de Groen, Dhillon, Kerkhoven, Janssen, & Bout, 2003) and subsequently a front-end loading strategy to achieve the 2x2 goals (Oosterhuis, Pang, Oostwegel, & de Kleijn, 2008).

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This proven interest in front-end activities makes the NAP network very well-suited for participation in our research.

1.3 Research approach

To answer the research questions, a research approach is developed. First some background information is provided on research approaches in social science and particularly in project management research. Subsequently, the methods applied in this dissertation are presented.

1.3.1 Research in social science

Research in the field of project management often has a positivist character (Smyth & Morris, 2007; Williams, 2005), e.g. it is assumed that there is one reality that can be described by laws with causal relationships, observed by an objective observer (Braster, 2000). Positivism attempts to control the context by isolating the phenomenon under study. Also the systemic view on project management has a positivist character. However, particularly the interaction of the project (management) with its environment is important since we aim to study adapting the project management to the project complexity. Therefore a pure positivist approach is not sufficient in the current research: inclusion of the environment would ask for a more constructivist approach (Pellegrinelli, 2011). In constructivism (or interpretivism), there can be more views of reality, without underlying causal relationships and the context is inseparably connected with the phenomenon under study (Braster, 2000). Whereas in positivism events are explained based on linear thinking in one reality (Smyth & Morris, 2007), in constructivism understanding by in-depth analysis of the different realities prevails. An example of a constructivist approach is found in the equifinality view expressed in the contingency theory (Donaldson, 2001). An equifinality view means there is no unique solution but there are more ways in which improvement can be achieved and contingency theory by definition includes the environment in some way.

To investigate the management of complex projects, a pure positivist research approach would limit the directions for resolving the complex management problem beforehand. On the other hand: a positivist approach might also provide a starting point to handle complex problems; for example by providing a model, method or a tool. This then should not be considered as the end-point, but the starting point for solving the complex problem at hand by including more constructivist principles. Such “mixed” approaches are suggested more often (Blaikie, 2009; Tashakkori & Teddlie, 1998). Hence the current research aims to use a constructivist approach in which positivist aspects are embedded.

In a research approach, two main methods of logic can be distinguished: deductive and inductive reasoning. These are described in the well-known “Wheel of Science” (Wallace, 1971), see Figure 1.1. In a deductive approach the starting point is a theoretical basis. From the theory, the hypotheses are derived that are checked by observations. This can lead to confirmation or non-confirmation of the original or new theories. In an inductive approach, the starting point is the observation. From specific observations, patterns are searched for and preliminary hypotheses are formulated, leading to the development of new theory. Eisenhardt, for example, successfully shows how an inductive approach can lead to new theory building (Eisenhardt, 1989). She indicates that theory resulting from such an inductive approach “is often novel, testable and empirically valid” (p.532), despite original skepticism about qualitative inquiry that is often associated with inductive research (Miles & Huberman, 1994).

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Figure 1.1: The Wheel of Science (Wallace, 1971)

In the Wheel of Science, phases of inductive and deductive research are naturally following each other. For example, when there is no theory available, one starts with observations, which via empirical generalizations can lead to new theory (induction). From this newly developed theory, hypotheses are formulated which are then tested by, again, observations (deduction). Although there is no single, unified theory on project management, different disciplines in project management do have a firm theoretical basis from which hypotheses can be formulated. Subsequently, these hypotheses are tested based on observations, which is at the deductive side of the deductive/inductive spectrum. Often, positivism and deductive reasoning are associated with the hard paradigm of project management and interpretivism and inductive reasoning with the soft paradigm of project management (Pollack, 2007). The Wheel of Science nicely connects these paradigms.

Pollack distinguishes practices based on the hard and soft paradigm in project management as follows (Pollack, 2007). In the hard paradigm, practices “tend to emphasize efficient, expert-led delivery, control against predetermined goals and an interest in underlying structure”, p.267. In the soft paradigm, practices “emphasize learning, participation, the facilitated exploration of projects, and typically demonstrate an interest in underlying social process”, p.267.

Dependent on the research approach, multiple research instruments can be used within one research project, such as experiments, surveys and/or case studies (Braster, 2000). In project management research, an experiment could have the form of a simulation or a game. Professionals could be asked to participate in such a simulation or a game to study how they would behave in a simulated project environment. Surveys could provide global information on large numbers of projects, whereas in-depth information, post-project or even longitudinally, could be obtained by case studies. Different types of case studies can be distinguished, such as exploratory, descriptive and explanatory (Yin, 2003). In an exploratory case study, the focus is on exploration, whereas this is on description and explanation (causality) in case of a descriptive or explanatory case study, respectively. Explorative case studies are often done in initial phases of the research in a certain area, having the most inductive character of the different types of case studies. Case studies would be useful in both deductive and inductive approaches, as “the case study is useful for both generating and testing of hypotheses but is not limited to these research activities alone” (Flyvbjerg, 2011), p.306. Empirical generalizations Hypotheses Observations Theory Induction Deduction

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Often interviews are part of a case study or a survey study. Interviews can have a structured or an unstructured character (and all steps in-between). In unstructured interviews there is no standard questionnaire but questions arise during the interview, giving the possibility to elaborate on the answers of the respondent. In structured interviews, there is a strict protocol or questionnaire to be followed. Where case studies more often use the unstructured or semi-structured interviews, surveys more often use structured interviews. The use of different research instruments and sources of information within one research is called “triangulation (Tashakkori & Teddlie, 1998).

1.3.2 Methods applied in this research

The basic underlying conceptual model of this research consists of three building blocks, see Figure 1.2. Project performance is considered the dependent variable and project complexity as well as front-end development activities are the independent variables.

Figure 1.2: Model project complexity / front-end activities / project performance Where do the arrows in Figure 1.2 stem from? In this high level conceptual model, we assume that performing front-end activities positively contributes to project performance (…that’s what you do project management for...). Putting significant effort in the front-end development phase is often recommended as a vital part of project management, with a high influence on the final project result (Bakker, 2008; de Groen et al., 2003; Flyvbjerg et al., 2003; Morris, 1994; Morris et al., 2006a; Oosterhuis et al., 2008; van der Weijde, 2008). Therefore we assume that front-end activities have this (direct) relationship with project performance. Project performance is hypothesized to be negatively influenced by project complexity (Flyvbjerg et al., 2003; Hall, 1981; Morris & Hough, 1987; Neleman, 2006; Williams, 2002, 2005). Hence, we assume that project complexity has a (direct) -negative- relationship with project performance. Next to these two direct relations; a third moderated relation is hypothesized: the front-end development phase of a project should be adapted or fitted to the specific project complexity and a fit between these would positively contribute to project performance. This is based on literature that suggests the application of contingency theory to project management (Engwall, 2003; Shenhar & Dvir, 1996; Smyth & Morris, 2007). Here project complexity acts as the moderator: based on the project complexity, the front-end activities should be adapted.

The fact that the starting point of this PhD research is a model suggests that this research is at the deductive side of the deductive/inductive spectrum (see also Figure 1.1). The model,

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however, is a high level one and these main variables first need further operationalization and hence exploration of the field, which is at the inductive side of the spectrum. Therefore this research starts with an exploratory character and progresses towards more evaluative phases, as the detailed phase description shows.

In the first phase of the research, the concept of project complexity is explored and a model representation of project complexity is developed. Also relevant front-end activities are explored and it is investigated to what extent the front-end phase currently is adapted to the particular project complexity. Although from literature there are some starting points on modeling project complexity (Dombkins, 2008; Geraldi, 2008b; Hass, 2007; Williams, 2002) in-depth investigations towards real projects are not yet reported. To gather in-depth information on activities in the front-end development phase and the factors determining and influencing project complexity an exploratory case study approach is chosen. In a limited number of exploratory case studies, semi-structured interviews are held with project team members and written materials (official reports, project archives) are investigated. To prepare for the case study, all building blocks from Figure 1.2 are explored by means of a literature review. The exploratory case study is performed in one company, an active member of the NAP network, with a very structured project management approach. By choosing different projects from one company -all projects were executed based on the same project management process- variations in the standard front-end activities applied in a project were limited.

For the case study, a multiple-cases embedded design (Yin, 2002) is used, in which each case represents a completed project. The embedded design refers to the different dimensions to be analyzed within one case: project complexity, the activities in the front-end development phase and the project performance. The multiplicity refers to the inclusion of a number of projects opposed to inclusion of a single project. The inclusion of multiple cases in an embedded design is assumed to give a broader view on the dimensions under consideration (Yin, 2002). Per case, semi-structured interviews are held with multiple people involved in the project. The information obtained from the case studies is used for development of the project complexity framework and for defining the relevant front-end development activities to deal with project complexity. In the development of these frameworks, the empirical findings are confronted with literature findings.

The second phase of the research is focused on finding the potential relationships between the building blocks in Figure 1.2. Relations between project complexity, the activities in the front-end development phase and the project performance are investigated. To obtain sufficient data to draw statistically relevant conclusions from, a survey study is done amongst a large number of completed projects in the Dutch process industry. The survey is distributed via the NAP network. Despite NAP’s interest in improving the front-end development phase, not all the companies are at the same level of application of front-end development activities. However, they do speak the same language and are well aware of developments in improving project management in their sector.

The survey study is used to investigate and quantify potential relationships between project complexity, project management (e.g. front-end activities) and project performance, hence to further develop and operationalize the conceptual model of Figure 1.2. Also the newly developed complexity framework is evaluated in detail. The research in this phase is quantitatively oriented and, together with Phase I, follows an exploratory mixed methods

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approach (Blaikie, 2009; Tashakkori & Teddlie, 1998): the qualitative part (Phase I), is followed by a quantitative part (Phase II).

The third phase of the research consists of in-depth case studies. Multiple cases are studied, exploring contractor and owner perspectives and following again a multiple cases embedded design (Yin, 2002). Based on the quantitative outcomes of the second phase, this case study investigates more deeply in what way specific front-end activities contributed to the project performance. Actually this phase focuses on the assumed direct relation between front-end activities and project performance in Figure 1.2. Phase III has a more explanatory character and is qualitatively oriented.

The second and the third phase together are again an example of mixed methods approach, but now it is explanatory rather than exploratory (Blaikie, 2009; Tashakkori & Teddlie, 1998). Some of the quantitative findings of Phase II are further explained by means of the qualitative in-depth case studies in Phase III.

The fourth and final phase of the research is a validation survey, in which it is investigated to what extent the different aspects of complexity indeed contribute to project complexity and how the newly developed framework to grasp project complexity (Phase I en II) could help in improving project performance in future projects. The questions in this survey are not project specific but sector specific to enable generalization of the results outside the specific companies involved. The survey is sent to two owner companies and two contractor companies, all of which are participating in the NAP network. The research in this concluding phase is partly quantitative and partly qualitative. Quantitative, as to what extent each of the elements of the complexity framework indeed would contribute to project complexity and qualitative in how the framework could help in improving project performance.

A summary of these four phases, the methods used, the main content and main results is provided in Figure 1.3.

Across the different phases, the Wheel of Science (Figure 1.1) is followed several times. The case study in the first phase starts with observations, which are generalized and confronted with theory, resulting in a framework to characterize project complexity. The second phase evaluates the complexity framework and explores relations between complexity, front-end activities and project performance. Again results are confronted with literature findings. Based on the results of the second phase, the Wheel of Science was followed again in the third and the fourth phase. In the third phase to deepen the Phase II results by means of qualitative in-depth interviews and in the fourth phase to validate the developed complexity framework. To strengthen the results, links with literature are established where possible.

The constructivist character of the research consists of the appreciation of different perceptions and dimensions of project complexity. The constructivist character of this research is also reflected in including broader discussions on the use of the models developed and the mere fact that projects are investigated with particular attention for their context.

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Figure 1.3: Overview of the empirical part of the research

To conclude this section, Figure 1.4 summarizes how the data is collected from the different companies in the NAP network, across the four project phases. Phase I is focused on projects from one company in the NAP network (a key player) whereas Phase II aims to include projects from as many as possible NAP companies. In Phase III some cases from the Phase II sample are studied in-depth and hence a few of the Phase II companies are involved. Finally, Phase IV is focused on cases from a few key companies.

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1.4 Scientific and social relevance

The underlying problem of this research is the continuing existence of cost and time overruns in (increasingly complex) projects. This dissertation therefore focuses on an understanding of project complexity. Different dimensions of project complexity are investigated, as well as different perspectives on project complexity including the dynamic character of project complexity. Because of the assumed importance of the early project phases in project management literature, we focus on the so-called front-end development phase of projects. Moreover, it is investigated how a contingency approach could be used to fit the activities in the front-end development phase of a project to the project complexity in order to reduce cost and time overruns in projects. With the new model to grasp project complexity in engineering projects, recommendations for use of this model and recommendations on the most relevant front-end activities for projects with specific types of complexity, this study aims to contribute to a better understanding of how to improve project performance. Due to a lack of large scale empirical research on project management in business environments (Hodgson & Cicmil, 2006; Kloppenborg & Opfer, 2002; Söderlund, 2004a), sound scientific evidence for either of the above suggestions is lacking up to now.

In terms of scientific relevance; this research explores the use of a contingency approach to project management. The use of a contingency approach is sometimes suggested in literature as the way to go to improve project management, but at this stage mainly conceptual papers in this area are available (Howell et al., 2010). This PhD research investigates the application of a contingency approach to project management. By gathering new empirical data and combining qualitative and quantitative techniques, this research contributes to the further development of project management research. This study aims to contribute to the development of project management theory based on business practice, by applying and combining qualitative as well as quantitative research methods.

In terms of social relevance, this research could contribute to improving business practice by improving the understanding and implications of project complexity. Also the possibilities of adapting, or fitting, the front-end development phase of a project to the project complexity is an expected result of this study: what can project managers do in the early project phases to improve their projects? Improved understanding of the early project phases is expected to result in improved project performance in terms of effectiveness and efficiency, hence providing financial benefit for organizations delivering projects.

1.5 Dissertation outline

Figure 1.5 links the different chapters of this dissertation with the previously identified research phases. It all starts with the literature survey on project management research in Chapter 2. Subsequently, the exploratory case studies are presented in Chapter 3. The findings of Chapter 2 and Chapter 3 come together in Chapter 4, in which a framework is developed based on the literature and the case study results. Chapters 3 and 4 together comprise the first phase of the research.

In Chapter 5 we describe how quantitative data is gathered by means of a survey study within the NAP network. Results of this survey are presented in Chapter 6 (evaluation of project complexity) and in Chapter 7 (evaluation of the relations between project complexity, front-end development and project performance). These chapters together comprise the second phase of the research.

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Based on the findings of Chapter 7, another case study is performed to study in-depth how the relevant front-end activities actually are applied and contribute to project performance, which is presented in Chapter 8. This chapter comprises the third phase of the research. Subsequently, results of a second survey are presented in Chapter 9. With this survey study, the developed complexity framework is further evaluated and validated. This chapter comprises the fourth phase of the research.

Finally, Chapter 10 provides the discussion as well as the conclusions and recommendations for further research.

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Chapter 2 Literature review

This chapter presents the literature review which was performed to build knowledge and find current gaps in the literature. First, a project is defined and the development of project management over the years is sketched, followed by observed trends in project management research. Based on these trends and identified gaps, the focus areas for the current research are further elaborated: project performance, front-end activities, contingency theory, project complexity and stakeholders’ perspectives. This chapter concludes with summarizing the starting points for the empirical work, described in the subsequent chapters.

Throughout this dissertation, we focus on engineering projects: projects that create a technical artifact. Therefore also general project management literature was read in view of such engineering projects.

2.1 What is a project?

The second edition of the handbook of project-based management provides a rather generic definition of a project (Turner, 1999):

“A project is an endeavor in which human, financial and material resources are organized in a novel way to undertake a unique scope of work, of given specification, within constraints of cost and time, so as to achieve beneficial change defined by quantitative and qualitative objectives” (p. 3).

In the third edition of this handbook, he limits the definition of a project to the key features (Turner, 2008):

“A project is a temporary organization to which resources are assigned to do work to deliver beneficial change” (p.2).

PRINCE2, a well-known, structured project management method, gives a similar definition of a project (Murray, 2009):

“A project is a temporary organization that is created for the purpose of delivering one or more business products according to an agreed Business Case.” (p. 3).

All definitions indicate that a project is characterized by its temporary character, in which a (unique) scope of work is undertaken, within certain constraints and for a particular reason.

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During a typical project life-cycle, the following project phases or stages are distinguished (Turner, 2008):

- “Proposal & initiation (concept and feasibility) - Design & appraisal

- Execution & control

- Finalization & close out” (p.14)

A similar distinction of these general project phases is presented by others (Cleland & King, 1983; Leybourne, 2007; Murray, 2009), albeit with some different names. In spite of the unique character of projects, elements of these phases are present in all projects. The “proposal & initiation” and “design & appraisal” phases of the typical project life cycle are often called the front-end development phase of a project. The ultimate goal of a project is the creation of value for the project stakeholders, with the content of the term “value” being different for the various stakeholders (Achterkamp & Vos, 2008).

The importance of the front-end development phase (FED) for the value creation or project performance is expressed in literature (Flyvbjerg et al., 2003; Morris, 1994; Morris et al., 2006a). However, this claim is rarely accompanied by hard scientific evidence or underlying data. Some institutes do claim such evidence (IPA, CII), but do not make it publicly available. Effort spent in the front-end development phase is called front-end loading (FEL). The challenge would be to balance FEL and effort spent during project execution, such that sufficient front-end development is done for an optimal project result after project execution. Here sufficient refers to enough, but not too much.

Between the typical project phases, stage gates are defined where the outcome of a certain phase is independently evaluated against pre-set conditions (Murray, 2009; Winch, 2002), resulting in go / no go decisions. Based on the evaluation, the project can continue in the next phase, can be adjusted or is stopped. Reviewing the project after every project phase enables the possibility of early failure detection which is crucial in controlling project costs. A rule of thumb from most industries says that costs of correcting a mistake non-linearly increase when the project progresses (Turner, 2008). Therefore, serious attention should be paid to the early project phases. When progressing through the different stages of the project life cycle, generally uncertainties are reduced. Generally, uncertainties and risks play a major role in today’s project management (Hillson & Simon, 2007).

2.2 The development of project management

Where did project management come from? Project management evolved from “craft”, into a profession, into a (semi-) discipline, but still theory development in project management is in its early years (Shenhar, 2001). Because of the multidisciplinary nature of project management, there is no unified theoretical basis (Smyth & Morris, 2007). Instead, one could speak of “pluralism” in project management theory (Söderlund, 2011). The historical development of project management can be summarized in three major stages (Maylor, 2005):

- Pre-1950s: no generally accepted or defined methods,

- 1950s: “One best way” approach, based on numerical methods established in the USA for managing large scale projects,

- 1990s: A contingent approach based on strategy.

Before the 1950s, project management as such was not recognized. In the 1950s, tools and techniques were developed to support the management of complex projects, mainly based on a systems approach, treating the project as a mechanical activity. The timing (1950s) is closely related to the rise of the computer, the development of systems engineering and