A COMPARISON OF DIFFERENT COST FORECASTING METHODS USING EARNED VALUE METRICS

Scope, Time and Cost are the three main attributes of a Project and they should be continuously monitored on their performance. Efficient decision making mandates the accuracy of forecasted estimations of a Project's final value termed as Cost Estimate At Completion (CEAC) in Earned Value Management. The greatest benefit gained by use of EVM is its ability to predict project outcome and potentially prevent project failure. To develop project management proficiency, organizations need to look at the critical elements of EVM as pragmatic stepping stones to prioritizing which project management processes are most important for successful delivery. In this paper the most commonly used predictive tools based on the performance indices, which are compared with a nonlinear regression based CEAC. Gompertz growth model is adopted, the input data is modified with cost variance and schedule variance. The output is modified with earned schedule which helps in predicting CEAC more accurately. Five data sets are used in the comparative study of CEAC methods. The model based on nonlinear regression is found to be the most accurate and precise method in the early stages of the Project as compared to other Index based methods.