Enhancing Reliability of Construction Contingency Estimation at the Scoping Phase through Historical Cost Data Analysis

Abstract

Accurate estimates of construction contingency, a vital element that accounts for unforeseen additional expenses during building, are crucial for construction project agencies. In the initial planning phase, with project specifics still under development, the top-down method is a popular approach for estimating contingency. This method employs a straightforward approach to calculating contingency, using a fixed percentage or a sliding scale based on project variables. While such a method offers simplicity, it suffers from constraints, notably the absence of rigorous evaluation and the challenges of considering project-specific risks. Hence, this research conducts a comprehensive analysis of historical highway project cost performance data to refine the applicability of the sliding scale methodologies and strengthen current top-down approaches. Using various statistical methods, the study creates probability distribution curves that show the likelihood of different contingency costs occurring, along with their associated confidence levels. These probability distribution curves provide cost estimators and project managers with a reliable way to improve the accuracy of early cost estimates during critical planning phases. This study will benefit project agencies by providing a more accurate and informed approach to budgeting and contingency management, thereby improving project cost reliability.