Metrics That Matter: Core Predictive and Diagnostic Metrics for Improved Project Controls and Analytics

Abstract

Project progress and performance assessment is critically important to the successful delivery of capital facility projects. However, there is no standardized approach for the selection and use of project control metrics, making it difficult to analyze project progress and performance for transforming data into meaningful insights. This research identified core predictive and diagnostic metrics that may provide actionable insights into a project’s actual progress, performance, and forecast at completion. The methodology used for identifying these metrics included a literature review, surveys, expert evaluation utilizing the Delphi method, and statistical validation. The researchers analyzed 44 surveys and collected multiple rounds of responses from 16 subject matter experts to validate the findings. Results indicated there are 2 core metrics, seven validation metrics, seven innovative metrics, and 14 other significant metrics, which can be used for multiple project types, sizes, and contracting strategies. Statistical analyses of the survey data were used to further validate the core metrics and demonstrated that use of more core metrics corresponded with project cost performance and using more diagnostic metrics in projects led to better schedule performance.