Measuring and benchmarking managerial efficiency of project execution schedule performance

Though managerial efficiency is considered to be a key driver for successful execution of projects, not much study is reported to measure and benchmark this efficiency. In this study, a basket of 57 projects is selected and configured as Decision Making Units (DMUs) in a Data Envelopment Analysis (DEA) procedure which is then integrated with Principal Component Analysis (PCA). Suitable modifications are made in this DEA-PCA engine to factor in the overall and relative performance of DMUs to measure and rank their managerial efficiency. On the basis of combination of the inputs and managerial efficiency scores, DMUs are then classified using alternative methods of clustering into a five category benchmarking model: “excellent”, “good”, “fair”, “unsatisfactory” and “poor”. Distinguishing features of the model and the findings are discussed in representative DMUs that enable practitioners and policy makers to implement the model and objectively institute a multi-sector managerial performance recognition systems.