Measuring Time (eBook)

Prof Dr Mario Vanhoucke is associate professor at Ghent University and Vlerick Leuven Gent Management School (Belgium). He teaches Project Management, Business Statistics and Applied Operations Research. He is program director of the Bachelors and Masters in Business Engineering and the advanced Master in Operations and Technology Management and is a partner of OR-AS. His main research interest lies in simulation and optimization models in project scheduling and scheduling in the health care sector. This November he was awarded the 2008 International Project Management Association Research Award for the research project upon which this proposed book is based -(http://www.ipma.ch/awards/resawards/Pages/winnersandhonours2008.aspx).  

Preface 7
Introduction 12
Contents 15
List of Acronyms 18
List of Figures 22
List of Tables 25
Chapter 1 The EVM Fundamentals 27
1.1 Earned Value Management (EVM) 28
1.1.1 The metrics 28
1.1.2 Performance measures 31
1.1.3 Forecasting formula 35
1.2 A fictitious project example 44
1.3 Conclusion 47
Chapter 2 Beyond the EVM Fundamentals 51
2.1 The p-factor concept for schedule adherence 52
2.1.1 Activity overlapping 55
2.1.2 EV/PV accrue deviation 55
2.1.3 Ahead or delays in activities 56
2.2 Rework due to lack of schedule adherence 56
2.3 Conclusion 60
Chapter 3 A Case Study 62
3.1 Project 1. Revamp check-in 65
3.2 Project 2. Link lines 68
3.3 Project 3. Transfer platform 68
3.4 Conclusion 72
Chapter 4 A Simulation Study 75
4.1 Test methodology 77
4.1.1 The project generation 78
4.1.2 Project data 86
4.2 Simulation 1: A forecast accuracy study 87
4.2.1 Simulation model 87
4.2.2 The forecast accuracy under 9 scenarios 91
4.2.3 The forecast accuracy and the completion stage of work 94
4.2.4 The influence of the network structure on the forecast accuracy 97
4.3 Simulation 2: A schedule adherence study 102
4.3.1 Simulation model 102
4.3.2 The p-factor evolution and topological structure 104
4.3.3 The p-factor and the duration forecasting accuracy 106
4.3.4 The effective forecasting accuracy 108
4.4 Conclusion 109
Chapter 5 Time Sensitivity 111
5.1 Introduction 111
5.2 Literature overview 112
5.2.1 Activity-based sensitivity measures 112
5.2.2 An illustrative example 115
5.2.3 A critical view on sensitivity measures 119
5.3 Simulation 3: An activity sensitivity study 121
5.3.1 Test design 122
5.3.2 Corrective actions 122
5.3.3 Action threshold = average sensitivity value 124
5.3.4 Action threshold = xth percentile sensitivity value 125
5.4 Conclusion 128
Chapter 6 Top-down or Bottom-up Project Tracking 130
6.1 Introduction 130
6.2 Project scheduling and monitoring 131
6.3 Simulation 4: A top-down/bottom-up tracking study 133
6.3.1 Simulation model 133
6.3.2 Effect of the project structure 136
6.3.3 Effect of time uncertainty 137
6.3.4 Effect of action threshold 139
6.4 Conclusion 141
Chapter 7 ProTrack: A Software Tutorial 143
7.1 Project scheduling with ProTrack 143
7.1.1 Precedence relations 144
7.1.2 Activity constraints 144
7.1.3 Earliest/Latest start schedule 147
7.1.4 Baseline schedule 149
7.2 Tracking progress with ProTrack 149
7.2.1 Earned value/earned schedule 151
7.2.2 Retained or overridden logic 153
7.2.3 Project reports 155
7.3 ProTrack engines 155
7.3.1 Project generation engine 156
7.3.2 Simulation engine 156
7.3.3 Time forecasting engine 158
7.4 Demo experiment 160
7.4.1 Determinants of forecast accuracy 161
7.4.2 ProTrack simulation experiment 165
7.5 Conclusion 168
Chapter 8 Conclusions 170
8.1 Forecast accuracy 171
8.2 Schedule adherence 172
8.3 Time sensitivity 173
8.4 Summary 174
References 177
Index 183