Applying Forecasting Models Through Estimate at Completion Cost of Project in Using Earned Value Analysis

Abstract

Earned Value Management (EVM) is the process of integrating the time and cost management within the framework of project scope management. The earned value has provided methods for predicting the cost for projects. In large part, these methods have not been improved upon since their beginnings and remain unsubstantiated as to accuracy. In this direction, several mathematics formulas have been developed by a number of researchers. However, there is no agreement on the usage of the particular formula for all the projects. In addition, the estimation of the final cost of project has been emphasized by all previous studies and it was no attention made to the time frames of the project. On this base, the aim of this research is to complete and expand the completion cost forecasting methods of a project and improve the capability of project managers for making informed decisions by providing a reliable forecasting method of the costs. In this paper, the cost completion forecasting methods are divided into two general categories, namely Performance Index Methods and Regression and Time Series Methods. Regression models are established on the basis of linear relationship between some EV parameters. For models comparison, forecasting errors (e.g., MAPE, MSE, MA, increasing and decreasing trends of error percentage value in different periods, R2, analysis of variance and comparative analysis) are used. Some of regression models have shown the reliable results. In order to determine the best cost forecasting method by utilizing the real data from four different projects with different criteria, the fore-mentioned methods are employed.