A Bayesian approach to improving estimate to complete

The capability to develop a reliable ‘Estimate at Completion’ from the earliest stage of project execution is essential in order to develop a proactive project management. In order to accomplish this aim, a model to formulate estimates at completion is presented which integrates through a Bayesian approach three knowledge sources: experts' opinions, data from past projects and the current performance of the ongoing project. The model has been applied to three Oil and Gas projects in order to forecast their final duration and cost. These projects are characterized by a high level of size, uncertainty and complexity representing a challenging test for the model. The results obtained show a higher forecasting accuracy of the Bayesian model compared to the traditional Earned Value Management (EVM) methodology.

[1]  Paul Goodwin,et al.  How to integrate management judgment with statistical forecasts , 2005 .

[2]  Dan Lovallo,et al.  Delusions of Success , 2003 .

[3]  Kirti Peniwati,et al.  Aggregating individual judgments and priorities with the analytic hierarchy process , 1998, Eur. J. Oper. Res..

[4]  Christophe Bredillet,et al.  Earned value management insights using inferential statistics , 2008 .

[5]  Walt Lipke,et al.  Statistical Process Control of Project Performance , 2022 .

[6]  Tuomo Kuosa,et al.  The Evolution of Strategic Foresight: Navigating Public Policy Making , 2012 .

[7]  F.T. Anbari,et al.  Earned Value Project Management Method and Extensions , 2003, IEEE Engineering Management Review.

[8]  Paolo Gardoni,et al.  A Probabilistic Framework for Bayesian Adaptive Forecasting of Project Progress , 2007, Comput. Aided Civ. Infrastructure Eng..

[9]  Bent Flyvbjerg,et al.  From Nobel Prize to Project Management: Getting Risks Right , 2006, ArXiv.

[10]  W. Duncan.  A GUIDE TO THE PROJECT MANAGEMENT BODY OF KNOWLEDGE , 1996 .

[11]  D. Kahneman,et al.  Delusions of success. How optimism undermines executives' decisions. , 2003, Harvard business review.

[12]  Martin J. Eppler,et al.  Harvesting project knowledge: a review of project learning methods and success factors , 2003 .

[13]  B. D. Finetti.  La prévision : ses lois logiques, ses sources subjectives , 1937 .

[14]  Ray Bert.  Book Review: Industrial Megaprojects: Concepts, Strategies, and Practices for Success , by Edward W. Merrow. Hoboken, New Jersey: John Wiley & Sons, 2011 , 2011 .

[15]  A. Tversky,et al.  Intuitive Prediction: Biases and Corrective Procedures , 1982 .

[16]  Dov Dvir,et al.  Plans are nothing, changing plans is everything: the impact of changes on project success , 2004 .

[17]  Byung-Cheol Kim,et al.  Integrating Risk Assessment and Actual Performance for Probabilistic Project Cost Forecasting: A Second Moment Bayesian Model , 2015, IEEE Transactions on Engineering Management.

[18]  Mauro Mancini,et al.  On Bayesian forecasting of procurement delays: a case study , 2006 .

[19]  Li Liu,et al.  Improving Cost Estimates of Construction Projects Using Phased Cost Factors , 2007 .

[20]  Walt Lipke,et al.  Statistical Methods Applied to EVM: The Next Frontier , 2006 .

[21]  B. Reich,et al.  How knowledge management impacts performance in projects: An empirical study , 2014 .

[22]  David S. Christensen,et al.  Project Advocacy and the Estimate at Completion Problem , 1996 .

[23]  Kenneth F. Reinschmidt,et al.  Probabilistic Forecasting of Project Duration Using Bayesian Inference and the Beta Distribution , 2009 .

[24]  Dan Lovallo,et al.  Robust analogizing and the outside view: two empirical tests of case‐based decision making , 2012 .

[25]  Franco Caron,et al.  Managing the Continuum: Certainty, Uncertainty, Unpredictability in Large Engineering Projects , 2013 .

[26]  Quentin W. Fleming,et al.  Earned Value Project Management , 1996 .

[27]  Konstantinos Nikolopoulos,et al.  A strategic forecasting framework for governmental decision-making and planning , 2013 .

[28]  B. Flyvbjerg.  Survival of the Unfittest: Why the Worst Infrastructure Gets Built-And What We Can Do About it , 2009, 1303.6571.

[29]  Spyros Makridakis,et al.  Forecasting and Planning: An Evaluation , 1981 .

[30]  J. Scott Armstrong,et al.  Structured Analogies for Forecasting , 2007 .

[31]  T. Saaty.  Fundamentals of Decision Making and Priority Theory With the Analytic Hierarchy Process , 2000 .

[32]  Franco Caron,et al.  A Bayesian Approach to Improve Estimate at Completion in Earned Value Management , 2013 .

[33]  Shankar Sankaran.  Industrial Megaprojects: Concepts, strategies and practices for success , 2016 .