Integrating risk in project cost forecasting

Abstract

Estimating duration and cost at completion based on Earned Value Management (EVM) data and managing risk contingency accounts in ongoing projects are typically treated by both scholars and practitioners as separate processes of project monitoring. However, project risk is claimed to significantly impact on project schedule and cost performance. As an attempt to combine these two management areas, the paper illustrates a methodology for improved schedule-based cost estimates at completion with the added nonlinear profile of risk contingency cost consumption. In particular, the model builds upon a Gompertz S-curve shaped cost profile equation. The model is applied to a sample of real project datasets. Its estimate accuracy and stability are tested at various early, middle, and late stages of project development. The proposed schedule-cost-risk estimate methodology proves to be a viable and effective tool to compute refined estimates at completion of complex projects involving formal management of contingency escrow accounts. The theoretical contribution is about creating a stronger connection between EVM and risk contingency management theories. Practical implications are inherent with the ability of the methodology to integrate cost contingency (CC) management into cost and schedule monitoring processe