A Proposal to Improve the Earned Value Management Technique Using Quality Data in Software Projects

Abstract

Currently the Project Management Institute (PMI) estimates that approximately 25% of the world’s Gross Domestic Product (GDP) is spent on projects of various kinds and that about 16.5 million professionals are directly involved in project management worldwide. This volume of projects and changes in the world scenario, increasingly competitive, generate the need for faster results, with higher quality, lower costs and shorter deadlines. Among the main techniques for analyzing cost, time and scope performance, the Earned Value Management (EVM) technique is considered to be the most reliable. Several formulas derived from EVM’s measurements are available and have been studied over the past 15 years. However, EVM has a significant limitation regarding quality in its method. The technique is effective in providing cost and schedule related information but is still weak in taking the quality factor into account. The objective of this work is to improve the predictability of cost and schedule of software projects using the EVM technique, by adding quality variables and allowing EVM to integrate not only scope, schedule and cost but quality as well. This paper presents a proposal to enhance the EVM technique by integrating the quality component. The proposed technique is evaluated and compared to the traditional technique through different hypothesis tests, utilizing data from simulated projects. Hypotheses tests with 95% significance level were performed, and the technique was more accurate than the traditional EVM for the projection of the Cost Performance Index – CPI and the Schedule Performance Index – SPI.