Improving the Forecasting Process in Project Control

Chapter
First Online:
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Abstract

Among the typical project management processes, planning plays a decisive role in reducing a project’s uncertainty. Project planning may be thought of as resulting from the interaction of the project team with the project and the project context.

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References

  1. F. Anbari, Earned value project management method and extensions. Project Manage. J. 34(4), 12–23 (2003)Google Scholar
  2. D. Christensen, Determining an accurate estimate at completion. Nat. Contract. Manage. J. 25, 17–25 (1993)Google Scholar
  3. D. Christensen, Project Advocacy and the estimate at completion problem. J. Cost Anal. Manage. 35–60 (1996)Google Scholar
  4. G. D’Agostini, Overcoming priors anxiety, in Bayesian Methods in the Sciences, ed. by J.M. Bernardo. Revista de la Real Academia de Ciencias, Madrid, 33(3) (1999)Google Scholar
  5. P. Davidson, Is probability theory relevant for uncertainty? A post Keynesian perspective. J. Econ. Perspect. 5(1), 129–143 (1991)CrossRefGoogle Scholar
  6. D. Dvir, T. Lechler, Plans are nothing, changing plans is everything: The impact of changes on project success. Res. Policy 33, 1–15 (2004)CrossRefGoogle Scholar
  7. Q. Fleming, Cost/Schedule Control Systems Criteria: The management guide to C/SCSC (Probus Press Inc, Chicago, 1992)Google Scholar
  8. B. Flyvberg, From nobel prize to project management: Getting risk right. Project Manage. J. 37, 5–15 (2006)Google Scholar
  9. B. Flyvberg, Survival of the un-fittest: Why the worst infrastructure gets built—and what we can do about it. Oxford Rev. Econ. Policy 25(3), 344–367 (2009)CrossRefGoogle Scholar
  10. P. Goodwin, How to integrate management judgment with statistical forecasts. Foresight 1(2005), 8–12 (2005)Google Scholar
  11. K.C. Green, J.S. Armstrong, Structured analogies for forecasting. Int. J. Forecast. 23, 365–367 (2007)CrossRefGoogle Scholar
  12. R.M. Hogarth, S. Makridakis, Forecasting and planning: An evaluation. Manage. Sci. 27(2), 115–138 (1981)CrossRefGoogle Scholar
  13. D. Kahneman, A. Tversky, Intuitive prediction: Biases and corrective procedures. TIMS Studies in Manage. Sci. 12, 313–327 (1979)Google Scholar
  14. R. Kleim, I. Ludin I, Project Management Practitioner’s Handbook (AMACOM 1998)Google Scholar
  15. W. Lipke, A study of the normality of Earned Value Management indicators (The Measurable News, 2002a) Dec 2002, pp. 1–16Google Scholar
  16. W. Lipke, Statistical process control of project performance. Crosstalk J. Def. Soft. Eng. 13, 16–20 (2002b)Google Scholar
  17. W. Lipke, Schedule is different (The Measurable News, 2003) Summer 2003, pp. 31–34Google Scholar
  18. W. Lipke, In: Earned Schedule Leads to Improved Forecasting. Proceedings of the 3rd international conference on project management (PROMAC 2006) Sept 2006, (2006a)Google Scholar
  19. W. Lipke, Statistical methods applied to EVM ...the next frontier (The Measurable News, 2006b) Winter 2006, pp. 18–30 Google Scholar
  20. L. Liu, K. Zhu, Improving cost estimates of construction projects using phased cost factors. J. Constr. Eng. Manage. 133, 1 (2007)CrossRefGoogle Scholar
  21. D. Lovallo, D. Kahneman, Delusion of success: How optimism undermines executives’ decisions. Harvard Bus. Rev. 81, 56–63 (2003)Google Scholar
  22. S. Makridakis, N. Taleb, Decision making under low levels of predictability. Int. J. Forecast. 25, 716–733 (2009)CrossRefGoogle Scholar
  23. S. Makridakis, R.M. Hogarth, A. Gaba, Forecasting and uncertainty in the economic and business world. Int. J. Forecast. 25, 794–812 (2009)CrossRefGoogle Scholar
  24. R.A. Marshall, P. Ruiz, C.N. Bredillet, Earned value management insights using inferential statistics. Int. J. Proj. Manage. 1(2), 288–294 (2008)Google Scholar
  25. E.W. Merrow, (Oil Industry Megaprojects: Our Recent Track Record (Offshore Technology Conference, Houston, 2011), pp. 2–5Google Scholar
  26. J. Palomo, F. Ruggeri, D. Rios Insua, E. Cagno, F. Caron, M. Mancini, On Bayesian forecasting of procurement delays: a case study. Appl. Stochastic Models Bus. Ind. 22, 181–192 (2006)MathSciNetMATHCrossRefGoogle Scholar
  27. Project Management Institute, A Guide to the Project Management Body of Knowledge, 5th edn. (PMI, Newtown Square, 2012)Google Scholar
  28. N.D. Savio and K. Nikoloupolos, A strategic forecasting framework for governmental decision making and planning. Int. J. Forecast. Available on line (2011)Google Scholar
  29. A. Soderholm, Project management of unexpected events. Int. J. Project Manage. 26, 80–86 (2008)CrossRefGoogle Scholar
  30. T. Williams, K. Samset and K.J. Sunnevag (eds.) Making Essential Choices with Scant Information, Palgrave Macmillan (2009)Google Scholar
  31. T. Williams, K. Samset, Issues in front-end decision making on projects. Project Manage. J. 41(2), 38–49 (2010)CrossRefGoogle Scholar
  32. T. Williams, O.J. Klakegg, D.H.T. Walker, B. Andersen, O.M. Magnussen, Identifying and acting on early warning signs in complex projects. Project Manage. J. 43(2), 37–53 (2012)CrossRefGoogle Scholar

Copyright information

© The Author(s) 2013

Authors and Affiliations

  1. 1.Management Economics and Industrial EngineeringPolitecnico di MilanoMilanItaly

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