Application of Logistic Regression to Predict Over Target Baseline of Software Projects

Earned Value Analysis (EVA) is a project management technique (Stephan and Mario, 2006). It is one of the most effective performance measurement tools for controlling and managing the development projects. EVAt assists, the project manager to cognize the project status and predicts future performance. The objective of this paper is to predict the Over Target Baseline (OTB) and Estimate At Completion (EAC) of the in-progress projects, based on the earned value analysis (EVA) using Logistic Regression techniques. For this purpose, we obtained ongoing data pertaining to projects from one of the major information technology (IT) company. The progressive estimates of projects, such as, baseline cost, Planned Value, Earned Value and Actual Cost are obtained for the real time data. This approach is applicable to have better forecast of the project cost and decreasing the risk of project cost overrun, and therefore it could be beneficial for planning preventive actions.