A Data-Driven Approach for Identifying Project Manager Competency Weights

Competent project managers (PMs) are the backbone of any construction project. It is extremely important to constantly develop and enhance their competencies. However, to establish effective training and development plans for PMs, the relative importance of the key competencies that define a PM's performance should be first understood. Instead of subjectively weighting the relative importance of differing competencies, this paper aims at developing an automated model that uses real-life data to compute the PM competency weights. The rationale behind the model is to maximize the distance in a higher dimensional space between average and exceptional PM performances. The model solves an eigenvalue problem, and identifies a single data-based weight for each competency. The model is generic and can be applied to various research settings to alleviate the problems associated with opinion-based assessment and reduce individuals' subjectivity. Findings within this paper reveal the most critical competencies that enable PMs to perform their roles in construction projects exceptionally.