Earned Value and Cost Contingency Management: A Framework Model for Risk Adjusted Cost Forecasting
Keywords:
Project Management, Earned Value Management, Cost Contingency, S-curve, Gompertz Growth ModelAbstract
This paper proposes a novel framework model that considers different behaviors of cost contingency (CC) consumption in forecasting risk adjusted final cost during the project execution. The model integrates the dynamics of how project managers can spend their contingencies into three S-shaped cost growth profiles to compute risk adjusted cost estimates at completion (CEAC). The three cost curves are modeled by the Gompertz growth model using nonlinear regression. Respectively, the framework embeds three different CC consumption rates to represent three main categories of aggressive, neutral or passive managerial attitudes in responding to project risk. The usage and viability of the model is demonstrated via a earned value management (EVM) dataset. The paper contributes to the body of knowledge by bridging the gap between the theories of EVM and CC management and provides project managers with a model to estimate the range of possible cost estimates at completion depending on the managerial policies that can be activated driven by different risk attitudes.
References
Anbari, F. T. (2003). Earned value project management method and extensions. Project Management Journal, 34(3): 12–23.
Babar, S., Thaheem, M., and Ayub, B. (2016). Estimated cost at completion: Integrating risk into earned value management. Journal of Construction Engineering and Management, 10.1061/(ASCE)CO.1943-7862.0001245, 04016104.
Barraza, G. A. and Bueno, R. A. (2007). Cost contingency management. Journal of Management in Engineering, 23(3): 140-146.
Batselier, J. and Vanhoucke, M. (2015). Empirical evaluation of earned value management forecasting accuracy for time and cost. Journal of Construction Engineering and Management, 141(11).
Caron, F., Ruggeri, F., and Merli, A. (2013). A Bayesian approach to improve estimate at completion in earned value management. Project Management Journal, 44(1): 3–16.
Chao, L. C. and Chien, C. F. (2010). “A model for updating project S-curve by using neural networks and matching progress.” Automation in Construction, 19(1): 84–91.
Chen, H. (2014). Improving forecasting accuracy of project earned value metrics: Linear modeling approach. Journal of Management in Engineering, 30(2): 135-145.
Christensen, D. S., Antolini, R. D., and McKinney, J. W. (1992). A review of estimate at completion research. In Cost Estimating and Analysis, 207–224, Springer-Verlag, New York, NY.
Cioffi, D. F. (2005). A tool for managing projects: An analytical parameterization of the S-curve. International Journal of Project Management, 23(3): 215–222.
Cioffi, D. F. and Khamooshi, H. (2009). A practical method of determining project risk contingency budgets. Journal of the Operations Research Society, 60(4): 565–571.
De Koning, P. and Vanhoucke, M. (2016). Stability of earned value management do project characteristics influence the stability moment of the cost and schedule performance index. Journal of Modern Project Management, 4(1): 9-25.
De Marco, A. Rosso, M., and Narbaev, T. (2016b). Nonlinear cost estimates at completion adjusted with risk contingency. Journal of Modern Project Management, 4(2): 24–33.
De Marco, A., Rafele, C., and Thaheem, M. J. (2016a). Dynamic management of risk contingency in complex design-build projects. Journal of Construction Engineering and Management, 142(2).
Ford, D. N. (2002). Achieving multiple objectives through contingency management. Journal of Construction Engineering and Management, 128(1): 30-39.
Kerzner, H. (2013). Project management: A systems approach to planning, scheduling, and controlling, 11th Ed., Wiley, Hoboken, NJ.
Kwak, Y. H. and Anbari, F. T. (2009). Availability-impact analysis of project management trends: Perspectives from allied disciplines. Project Management Journal, 40(2): 94–103.
Lipke, W. (2003). Schedule is different. Measurable News, Summer, 31–34.
Narbaev, T. and De Marco, A., (2013). Combination of growth model and earned schedule to forecast project cost at completion. Journal of Construction Engineering and Management, 140(1).
Narbaev, T. and De Marco, A., (2014). An earned schedule-based regression model to improve cost estimate at completion. International Journal of Project Management, 32(6): 1007–1018.
Project Management Institute (PMI). (2011). Practice standard for earned value management, 2nd Ed., Newtown Square, PA.
Project Management Institute (PMI). (2013). A guide to the project management body of knowledge (PMBoK guide), 5th Ed., Newtown Square, PA.
Seber, G. A. F. and Wild, C. J. (1989). Nonlinear regression, Wiley, New York, NY.
Touran, A. (2003). Probabilistic model for cost contingency. Journal of Construction Engineering and Management, 129(3): 280-284.
Uzzafer, M. (2013). A contingency estimation model for software projects. International Journal of Project Management, 31(7): 981–993.
Xie, H., AbouRizk, S., and Zou, J. (2012). Quantitative method for updating cost contingency throughout project execution. Journal of Construction Engineering and Management, 138(6), 759-766.
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