IT Project Variables in the Balance: A Bayesian Approach to Prediction of Support Costs

Abstract

In the context of Information Technology (IT) project management, it is commonly accepted that the costs associated with support actions are strongly influenced by the effort spent during their development and test phases. Despite the importance of systematically characterizing and understanding this relationship, little has been done in this realm mainly due to the lack of proper mechanisms for both sharing information between IT project phases and learning from past experiences. To tackle this issue, we present a Bayesian model to perform support cost predictions based on data from software development and test phases. In addition, we present a qualitative and quantitative analysis of the model, in order to demonstrate its effectiveness and efficiency, and also discuss its potentialities and limitations.