Enhanced earned value analysis - improving visibility and forecasts in projects by introduction of clusters

Abstract

Earned Value Analysis (EVA) is a performance measurement tool that has been used in project management for decades. It is simple to use, but at the expense of its simplicity it has its limitations, such as an assumption that variance in one task can be extrapolated to all other tasks in the project. In this paper, Enhanced Earned Value Analysis (EEVA) is presented. EEVA is an extension to EVA and Earned Schedule (ES) by the introduction of clusters. The clusters provide EEVA with the capability to make new estimates more reliable, as extrapolations on actual data gathered, only is done to a selection of tasks sharing the same resources. It will also provide a higher visibility in projects, that helps when looking for root causes of deviations. The method of EEVA is developed based on a thorough search through literature, and the paper will present at stepwise description on how EEVA can be carried out. A preliminary validation of the model is being carried out through the application of EEVA to a test project. Because of confidentiality reasons, the results from this is presented in the appendix. As defined by the end of this paper, additional validation activities is needed to fully validate the model. However preliminary perception of stakeholders involved, suggest an initial validation of the developed model.