Grey Earned Value Management: Theory and Applications

Abstract

Project stakeholders always investigate possible approaches to monitor project progress closely and further, taking necessary actions during the whole phases of the project in order to manage delays. Earned value management (EVM) is one of the methods, which can forecast the required costs for accomplishment of the project. The data collected from projects undertaken in order to update the master schedule often suffer from a level of uncertainty. Ignoring these uncertainties may even lead to project failure. Fuzzy theory has been previously used in the EVM for taking uncertainties into account. A major disadvantage of using fuzzy approaches is the need for incorporating expert judgments to construct a suitable membership function for all activities in the project undertaken. A potential approach for overcoming this issue lies in Grey theory. In this article, the current study deals with the EVM method in grey systems paradigm. Also, the performance of the proposed method, called grey earned value management (EVM-G), is evaluated through some numerical examples and a case study. The results demonstrate that the proposed approach has a unique performance in highly uncertain environments when experts have become unavailable. Comparisons between EVM-G and the fuzzy earned value management approaches reveal the superior performance of EVM-G.