Statistical Characteristics of Cost Contingency in Water Infrastructure Projects
Publication: Journal of Construction Engineering and Management
Volume 140, Issue 3
Abstract
Cost contingency is one component of a project’s budget to cater for cost growth. The determination of a project’s cost contingency is a pervasive problem because the amount that is incorporated into an estimate is invariably insufficient to accommodate the cost growth of a project. This study analyzed the statistical characteristics of cost contingency and cost growth experienced in 228 similar Australian water infrastructure projects that were procured by using traditional lump contracts. It was revealed that mean project final costs exceeded the approved budgets that contained contingency. The mean contingency percentage addition was 8.46%, yet the mean contingency required for the final cost was 13.58% for the sampled projects. Thus, the deterministic percentage addition, used by the sponsor to accommodate for cost growth beyond their baseline budget, was inaccurate. To improve the accuracy of a contingency estimate, the empirical distributions of cost contingency and cost performance were examined to determine their best-fit probability distribution. The research presented in this paper demonstrates that determining the best fit probability distribution provides a more robust and defendable basis for selecting a cost contingency than the traditional deterministic percentage approach.
Get full access to this article
View all available purchase options and get full access to this article.
References
Ahmad, I. (1992). “Contingency allocation: A computer-aided approach.” AACE Trans., F4, 1–7.
Aibinu, A. A., and Jagboro, G. O. (2002). “The effects of construction delays on project delivery in Nigerian construction industry.” Int. J. Proj. Manage., 20(8), 593–599.
Arditi, D., Tarim, G., and Gurdamar, S. (1985). “Cost overruns in public projects.” Int. J. Proj. Manage., 3(4), 218–224.
Baccarini, D. (2009). “Critical success factors in construction engineering projects—A case study.” Australian Institute of Project Management Conf.
Chang, A. S.-T. (2002). “Reasons for cost and schedule increase for engineering design projects.” J. Manage. Eng., 29–36.
Chen, D., and Hartman, F. T. (2000). “A neural network approach to risk assessment and contingency allocation.” AACE Trans. Risk., 7, 1–6.
Clark, D. E. (2001). “Monte Carlo analysis: Ten years of experience.” Cost Eng., 43(6), 40–45.
Creedy, G. D., Skitmore, R. M., and Wong, K. W. (2010). “Evaluation of risk factors leading to cost-overrun in delivery of highway construction projects.” J. Construct. Eng. Manage., 528–537.
Curran, M. W. (1989). “Range estimating.” Cost Eng., 31(3), 18–26.
Department of Infrastructure, and Transport (DIT). (2011). Best practice cost estimation standard: Publicly funded road and rail construction, Australian Government, Canberra, ACT, Australia.
Dey, P., Tabucanon, M. T., and Ogunlana, S. O. (1994). “Planning for project control through risk analysis: A petroleum pipelaying project.” Int. J. Proj. Manage., 12(1), 23–33.
Diekmann, J. E. (1983). “Probabilistic estimating: Mathematics and applications.” J. Construct. Eng. Manage., 297–308.
Diekmann, J. E., and Featherman, W. D. (1998). “Assessing cost uncertainty: Lessons from environmental restoration projects.” J. Construct. Eng. Manage., 445–451.
EasyFit 5 [Computer software]. MathWave Technologies.
Flyvbjerg, B. (2004). Procedures for dealing with optimism bias in transport planning: Guidance document, U.K. Department of Transport, London.
Flyvbjerg, B. (2007a). “Policy and planning for large scale-infrastructure projects: Problems, causes, and cures.” Environ. Plann. Plann. Des., 34, 578–597.
Flyvbjerg, B. (2007b). “Cost overruns and demand shortfalls in urban rail and other infrastructure.” Transp. Plann. Tech., 30(1), 9–30.
Flyvbjerg, B. (2008). “Curbing optimism bias and strategic misrepresentation in planning: Reference class forecasting in practice.” Eur. Plann. Stud., 16(1), 3–21.
Gettinby, G. D., Sinclair, C. D., Power, D. M., and Brown, R. A. (2004). “An analysis of the distribution of extreme share returns in the U.K. from 1975 to 2000.” J. Bus. Finance Account., 31(5–6), 607–646.
Gkritza, K., and Labi, S. (2008). “Estimating cost discrepancies in highway contracts: Multistep economic approach.” J. Construct. Eng. Manage., 953–962.
Hackney, J. W. (1985). “Applied contingency analysis.” AACE Trans., B, 1–4.
Hartman, F. T. (2000). Don’t park your brain outside, Project Management Institute, Upper Darby, PA.
HM Treasury. (2010). Infrastructure cost review: Main report, Infrastructure U.K., London.
Jahren, C., and Ashe, A. (1990). “Predictors of cost overrun-rates.” J. Construct. Eng. Manage., 548–552.
Knight, K., and Fayak, A. R. (2002). “Use of fuzzy logic for predicting design cost overruns on building projects.” J. Construct. Eng. Manage., 503–512.
Leach, L. P. (2003). “Schedule and cost buffer sizing: How to account for the bias between project performance and your model.” Proj. Manage. J., 34(2), 34–47.
Lorance, R. B., and Wendling, R. V. (1999). “Basic techniques for analyzing and presenting cost risk analysis.” AACE Trans. Risk, 1, 1–7.
Love, P. E. D. (2002). “Influence of project type and procurement method on rework costs in building construction projects.” J. Construct. Eng. Manage., 18–29.
Love, P. E. D., Cheung, S. O., Irani, Z., and Davis, P. R. (2011). “Causal discovery and inference of project disputes.” IEEE Trans. Eng. Manage., 58(3), 400–411.
Love, P. E. D., and Sing, C-P. (2013). “Determining the probability distribution of rework costs in construction and engineering projects.” Struct. Infrastruct. Eng., 9(11), 1136–1148.
Love, P. E. D., Sing, C-P., Wang, X., Irani, Z., and Thwala, D. W. (2014). “Overruns in transportation infrastructure projects.” Struct. Infrastruct. Eng.: Maintenance, Management, Life-Cycle Design Performance, 14(2).
Love, P. E. D., Sing, C-P., Wang, X., and Tiong, R. (2013). “Determining the Probability of Cost Overruns in Australian Construction and Engineering Projects.” ASCE J. Constr. Eng. Manage., 139(3), 321–330.
Mak, S., and Picken, D. (2000). “Using risk analysis to determine construction project contingencies.” J. Construct. Eng. Manage., 130–136.
Mak, S., Wong, J., and Picken, D. (1998). “The effect on contingency allowances of using risk analysis in capital cost estimating: A Hong Kong case study.” Construct. Manage. Econ., 16(6), 615–619.
Matsumoto, M., and Nishimura, T. (1998). “Mersenne Twister: A 623-dimensionally equi-distributed uniform pseudo-random number generator.” ACM Trans. Modell. Comput. Sim., 8(1), 3–30.
Meredith, J. R., and Mantel, S. J. (2006). Project management: A managerial approach, Wiley, New York.
Merrow, E. W., and Schroeder, B. R. (1991). “Understanding the cost and schedule of hydroelectric projects.” AACE Trans., I3, 1–7.
Merrow, E. W., and Yarossi, M. E. (1990). “Assessing project cost and schedule risk.” AACE Trans., H6, 2–7.
Moselhi, O. (1997). “Risk assessment and contingency estimating.” American Association of Cost Engineers Trans., American Association of Cost Engineers, Morgantown, WV, 1–6.
Oberlander, G. D., and Trost, S. M. (2001). “Predicting accuracy of early cost estimates based on estimate quality.” J. Construct. Eng. Manage., 173–182.
Odeck, J. (2004). “Cost overruns in road construction—What are the sizes and determinants?” Transport Pol., 11(1), 43–53.
Patrascu, A. (1988). Construction cost engineering handbook, Marcel Dekker, New York.
Project Management Institute (PMI). (2012). A guide to the project management body of knowledge, 5th Ed., PMI, Newtown Square, PA.
Semple, C., Harman, F. T., and Jergeas, G. (1994). “Construction claims and disputes: Causes and cost/time overruns.” J. Construct. Eng. Manage., 785–795.
Standards Australia. (1992). “General conditions of contract.” AS2124, Sydney, Australia.
StatAssist 5.5 [Computer software]. MathWave Technologies.
Thompson, P. A., and Perry, J. G. (1992). Engineering construction risks, Thomas Telford, London.
Tversky, A., and Kahneman, D. (1974). “Judgment under uncertainty: Heurists and biases.” Science, 185, 1124–1131.
Waldron, B. (2011). “Scope for improvement 2011—Project risk getting the right balance and outcomes.” 〈http://www.ashurst.com/information.aspx?id_Content=6908〉 (Jan. 15, 2013).
Williams, T. P. (2003). “Predicting final cost for competitively bid construction projects using regression models.” Int. J. Proj. Manage., 12(8), 593–599.
Yeo, K. T. (1990). “Risks, classification of estimates, and contingency management.” J. Manage. Eng., 458–470.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 140 • Issue 3 • March 2014
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Feb 14, 2013
Accepted: Nov 6, 2013
Published online: Dec 13, 2013
Published in print: Mar 1, 2014
Discussion open until: May 13, 2014
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.