Decision-aid frameworks for an enhanced employability of the earned value management method by the construction contract engineer.

Abstract

Construction project control is a process that is concerned with attempting to complete the contracted works within the allocated timeframe and the pre-agreed budget, all in accordance with the set quality standards. To this end, the earned value management (EVM) method is undoubtedly recognized as a well-established technique offering an integrated approach for the efficient monitoring and controlling of the project’s cost and schedule targets during the course of execution. However, several limitations have been steadily reported in the literature concerning the underlying assumptions and practicability of this method, as perceived by key players in a number of industries, and more so in the construction industry. These implementation obstacles have led to the performance of extensive investigations dealing with ways and means that can improve the representation, usage, and measurements of the EVM sets of metrics. That said, this research aimed at investigating several decision-aid frameworks that can systematically guide the construction contract engineer in making the EVM tool better accustomed and suited for exercising project controls and administrating construction contracts, while making use of and benefiting from the enhanced capabilities of the technique that are widely spread in the archived literature. To this effect, the adopted multi-step methodology included: (1) the verification of the degree of importance of project controls in relation to project success, in order to establish the continued need for improving on the current practices related to putting in place effective project control processes; (2) the classification of the shortcomings and challenges reported to be encumbering EVM’s employability as a project controls tool; and (3) the compilation and synthesis of the encountered improvements, with the aim of gaining discernment on how the reported EVM shortcomings may probably be overcome. The main research outcomes involved developing several EVM-based frameworks, which shall