Nonlinear Cost Estimates at Completion Adjusted with Risk Contingency

Authors

  • Alberto De Marco Politecnico di Torino - Dept. of Management and Production Engineering Italy
  • Marta Rosso Politecnico di Torino - Dept. of Management and Production Engineering Italy
  • Timur Narbaev Kazakh British Technical University Kazakhstan

Keywords:

Earned Value Management, Cost Estimate at Completion, Project Monitoring

Abstract

Forecasting the final cost with Earned Value Management (EVM) and managing contingency budgets during the project execution have been traditionally considered as two separate streams of project management research. In an attempt to combine the two areas for the purpose of reflecting the risk impact on the cost forecast, this paper presents a cost estimate at completion (CEAC) methodology adjusted with risk contingency. The proposed method is a refined Earned Schedule (ES) based nonlinear CEAC model modified with a new parameter representing the S-shaped contingency consumption as a portion of the project budget at completion. The model is validated on eight construction projects and its estimates’ accuracy and stability with a varying contingency parameter value in the early, middle, and late stages are evaluated. The cost–schedule-risk relationship represented in the model is a contribution to creating a stronger connection between EVM and contingency cost management theories through capturing the interconnected dynamics between a cost baseline and contingency accounts of ongoing projects. As a practical implication, the model is a tool for integrating the contingency consumption into nonlinear CEAC models for accurate and stable cost forecasting especially during the early and middle stages of project execution.

Author Biography

  • Alberto De Marco, Politecnico di Torino - Dept. of Management and Production Engineering Italy

    Alberto De Marco earned his Master of Science Degree and PhD in Building Engineering from Politecnico di Torino after attending part of his courses at the Grande Ecole Nationale des Ponts et Chaussées/ParisTech in Paris. He is an Associate Professor with the Dept. of Management and Production Engineering at Politecnico di Torino. He is appointed professor at the Tongji University of Shanghai and the Tashkent Polytechnic University. He has been an invited Visiting Lecturer at the Massachusetts Institute of Technology (MA, USA). He worked as a professional consultant and was founder and executive manager of a start-up company developing own-patented IT solutions for the industry. He teaches Project Management, Project Financing, and Logistics at various other national and international institutions. He works as part of the Research Group for Engineering Systems and Logistics (http://www.reslog.polito.it). He acts as a researcher and consultant in the fields of supply chain management, sustainable logistics, urban freight distribution, intelligent mobility, and smart cities, integrating the experience in project financing and public-private partnerships to develop infrastructure and mobility services.

References

Acebes, F., Pereda, M., Poza, D., Pajares, J., and Galán, J.M. (2015). “Stochastic earned value analysis using Monte Carlo simulation and statistical learning techniques.” Int. J. Proj. Manage., 33(7), 1537-1609.

Anbari, F.T. (2003). “Earned value project management method and extensions.” Proj. Manage. J., 34(4), 12-23.

Baloi, D. and Price A.D.F. (2003). “Modelling global risk factors affecting construction cost performance.” Int. J. Proj. Manage., 21, 261-269.

Barraza, G.A. and Bueno, R.A. (2007). “Cost contingency management.” J. Constr. Eng. Manage., 23(3), 140-146.

Christensen, D.S. (1993). “The estimate at completion problem: a review of three studies.” Proj. Manage. J., 24, 37-42.

Christensen, D.S., Antolini, R.D., and McKinney, J.W. (1995). “A review of estimate at completion research.” J. Cost Analys. Manage., Spring, 41-62.

Cioffi, D.F. (2005). “A tool for managing projects: an analytical parameterization of the S-curve.” Int. J. Proj. Manage., 23(3), 215-222.

Cioffi, D.F., and Khamooshi, H. (2009). “A practical method of determining project risk contingency budgets.” J. Oper. Res. Soc., 60(4), 565-571.

De Marco, A., Briccarello, D., and Rafele, C. (2009). “Cost and schedule monitoring of industrial building projects: Case study.” J. Constr. Eng. Manage., 135(9), 853-862.

De Marco, A., Rafele, C., and Thaheem, M.J. (2016). “Dynamic management of risk contingency in complex design-build projects.” J. Constr. Eng. Manage., 142(2).

Du, J., Kim, B., and Zhao, D. (2016). “Cost performance as a stochastic process: EAC projection by Markov Chain simulation.” J. Constr. Eng. Manage., 142, Just Released.

Fleming, Q.W., and Koppelman, J.M. (2006). Earned value project management, 3rd Ed. Project Management Institute, Inc., Newtown Square, PA.

Ford, D.N. (2002). “Achieving multiple objectives through contingency management.” J. Constr. Eng. Manage., 128(1), 30-39.

Gutierrez, G. J., and Kouvelis, P. (1991). “Parkinson's law and its implications for project management.” Manage. Scie., 37(8), 990–1001.

Hazir, T. (2015). “A review of analytical models, approaches and decision support tools in project monitoring and control.” Int. J. Proj. Manage., 33 (4), pp. 808-815.

Khamidi, M. F., Ali, W., and Idrus, A. (2011). “Application of earned value management system on an infrastructure project: A Malaysian case study.” Proc., Int. Conf. Manage. Service Sci., International Association of Computer Science and Information Technology, Singapore, 1–5.

Kim B.C., and Reinschmidt, K.F. (2011). “Combination of project cost forecasts in earned value management.” J. Constr. Eng. Manage., 137(11), 958-966.

Kim, B., and Kim, S. (2015). “Credibility evaluation of project duration forecast using forecast sensitivity and forecast-risk compatibility.” J. Constr. Eng. Manage., 141(8)

Kim, E., Wells, W.G., and Duffey, M.R. (2003). “A model for effective implementation of earned value management methodology.” Int. J. Proj. Manage., 21(5), 375-382.

Lipke, W. (2003). “Schedule is different.” Measurable News, Summer, 31-34.

Lipke, W., Zwikael, O., Henderson, K., and Anbari, F. (2009). “Prediction of project outcome: the application of statistical methods to earned value management and earned schedule performance indexes.” Int. J. Proj. Manage., 27(4), 400–407.

Mak, S., and Picken, D. (2000). “Using risk analysis to determine construction project contingencies.” J. Constr. Eng. Manage., 126(2), 130–136.

Narbaev, T., De Marco, A. (2013). “Combination of growth model and earned schedule to forecast project cost at completion.” J. Constr. Eng. Manage., 140(1).

Narbaev, T., De Marco, A. (2014). “An earned schedule-based regression model to improve cost estimate at completion”. Int. J. Proj. Manage., 32(6), 1007-1018.

Pajares, J., and Lopez-Paredes, A. (2011). “An extension of the EVM analysis for project monitoring: The cost control index and the schedule control index.” “, 29(5), 615-621.

PMI (Project Management Institute). (2013). A guide to the project management body of knowledge, 4th Ed. Project Management Institute, Inc., Newtown Square, PA.

Seber, G.A., and Wild, C.J. (1989). Nonlinear Regression. John Wiley & Sons, New York, NY.

Shokri-Ghasabeh, M., and Akrami, N. (2009). “How does a new set of earned value management schedule control work? A case study in Iran.” Trans. Environ. Dev., 5(2), 136–145.

Singletary, M. R. (2006). “Assessing the financial feasibility of implementing wireless technologies for construction management.” M.S. thesis, Florida State Univ., Tallahassee, FL.

Smith, G.R., and Bohn, C.M. (1999). “Small to medium contractor contingency and assumption of risk.” Journal of Construction Engineering and Management. 125(2), 101–108.

Touran, A. (2003). “Probabilistic model for cost contingency”. J. Constr. Eng. Manage., 129(3), 280-284.

Valle, J. A., and Soares, C. A. P. (2006). “The use of earned value analysis (EVA) in the cost management of construction projects.” Proc., Project Management Institute Global Congress, Newtown Square, PA, 1-11.

Vandevoorde, S., and Vanhoucke, M. (2006). “A comparison of different project duration forecasting methods using earned value metrics.” Int. J. Proj. Manage., 24 (4), 289–302.

Vanhoucke, M. (2011). “On the dynamic use of project performance and schedule risk information during project tracking.” Omega, 39(4), 416–426.

Willems, L.L., and Vanhoucke, M. (2015). “Classification of articles and journals on project control and earned value management.” Int. J. Proj. Manage., 33(7), 1610-1634.

Xie, H., Rizk, S., and Zou, J. (2012). “Quantitative method for updating cost contingency throughout project execution”. 138(6), 759-766.

Yeo, K.T. (1990). “Risks, classification of estimates, and contingency management.” J. Constr. Eng. Manage., 6(4), 458–470.

Zwikael, O., Globerson, S., and Raz, T. (2000). “Evaluation of models for forecasting the final cost of a project”. Proj. Manage. J., 31 (1), 53–57.

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Published

2022-05-20

Issue

Vol. 4 No. 2 (2016): The Journal of Modern Project Management

Section

Articles-JMPM

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Copyright (c) 2022 Alberto De Marco, Marta Rosso, Timur Narbaev

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Nonlinear Cost Estimates at Completion Adjusted with Risk Contingency. (2022). The Journal of Modern Project Management, 4(2). https://journalmodernpm.com/manuscript/index.php/jmpm/article/view/242

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