Influence of cost contingency management on project estimates at completion

Abstract

The Earned Value Management (EVM) methodology provides an index-based Estimate at Completion (EAC) formula to forecast the final cost of an ongoing project. However, neither the EVM methodology nor the literature in cost forecasting considers the occurrence of risks and how the cost contingency reserve (CC) is used to mitigate them. This study proposes a risk-adjusted cost EAC methodology based on nonlinear regression that captures the CC spending profile and exploits it to improve the EAC forecasting performance. The CC spending profile reflects the preventive, neutral, or reactive risk management strategy (RMS) adopted, which dictates how the CC reserve is depleted throughout the project execution. The framework was tested on a dataset comprising 79 constructions and engineering projects to evaluate its performance across the projects’ early, mid, and late stages. Results show that the proposed methodology provides timely forecasts—mean absolute percentage error (MAPE) improves as the project progresses—and that a proactive RMS is the most reliable one in all stages, with MAPE values of 14.57%, 12.28%, and 11.42%, respectively.