A Bayesian approach to improving estimate to complete

The capability to develop a reliable 'Estimate at Completion' from the earliest stage of project execution is essential in order to develop a proactive project management. In order to accomplish this aim, a model to formulate estimates at completion is presented which integrates through a Bayesian approach three knowledge sources: experts' opinions, data from past projects and the current performance of the ongoing project. The model has been applied to three Oil and Gas projects in order to forecast their final duration and cost. These projects are characterized by a high level of size, uncertainty and complexity representing a challenging test for the model. The results obtained show a higher forecasting accuracy of the Bayesian model compared to the traditional Earned Value Management (EVM) methodology.