A simulation and evaluation of earned value metrics to forecast the project duration

In this paper, we extensively review and evaluate earned value (EV)-based methods to forecast the total project duration. EV systems have been set up to deal with the complex task of controlling and adjusting the baseline project schedule during execution, taking into account project scope, timed delivery and total project budget. Although EV systems have been proven to provide reliable estimates for the follow-up of cost performance within our project assumptions, they often fail to predict the total duration of the project. We present an extensive simulation study where we carefully control the level of uncertainty in the project, the influence of the project network structure on the accuracy of the forecasts and the time horizon where the EV-based measures provide accurate and reliable results. We assume a project setting where project activities and precedence relations are known in advance and do not consider fundamentally unforeseeable events and/or unknown interactions among various actions that might cause entirely unexpected effects in different project parts. This is the first study that investigates the potential of a recently developed method, the earned schedule method, which improves the connection between EV metrics and the project duration forecasts.