Risk-based earned value management with cost–time mutual effect to enhance construction forecasts and management

Abstract

Earned Value Management (EVM) traditionally provides single-value forecasts of project cost and schedule that often underestimate real-world complexities—particularly the correlation between delays and cost over- runs, as well as the evolution of risk over time. This paper introduces an augmented EVM approach that incorporates (i) a monthly correlation factor linking extended task durations to higher expenditures, and (ii) interval-based risk factors driving probability distributions of final cost and schedule. By merging Monte Carlo simulation with traditional EVM metrics (planned value, earned value, actual cost), this method produces robust forecast bands instead of single-value estimates, enabling proactive contingency planning. Two ac- tual construction projects—one with 10-month planned vs. 12-month actual duration, another with 18 vs. 22 months—demonstrate how the augmented EVM captures worst-case scenarios significantly better than traditional EVM, while clarifying the likelihood of potential overruns. Though sometimes conservative, the distribution-based outputs give project managers a fuller picture of uncertainty, improving resource allocation and stakeholder communication in high-volatility construction environments.