Statistical Methods Applied to EVM . . . the Next Frontier

An objective of Earned Value Management (EVM) is to provide a means for predicting the outcome of a project. Inherently, the outcome is largely determined in the planning, and of course completion forecasting commonly occurs with analysis of project performance. Having the project plan, management would like to be able to quantify its risk What is the likelihood for having a successful project with this plan? How much should be allocated to reserves to achieve a high probability of success? If reserves are constrained to maintain the bid price in the competitive range, what is the probability of having a successful outcome? During project execution management desires to answer this question Can we state with confidence when the project can be expected to complete and simultaneously describe its projected final cost? The application of statistical methods facilitates answering these questions. This paper describes the elements necessary for performing statistical analysis. The worth of Earned Value Management (EVM) has been demonstrated over the 35+ years of application to many, many projects. There is substantive evidence of its positive influence on project outcome results. EVM fosters several good management practices which contribute to successful project performance – organization, accountability, planning, risk assessment, tracking, reporting, controlling ....and more. But, overarching these elements, my opinion is that the most significant contribution to the improvement of the state of the practice is EVM has brought science to the management of projects. Without numbers, scientific management is not possible. Because of EVM, project managers have numbers with a sound basis. Performance of a project has a quantitative description with meaning. And, in turn, the numerical description provides project managers with information useful for guiding and controlling the project. From a relatively simple concept a quantum leap has been made for the management of projects – Earned Value Management. Several formulas, derived from EVM measures, are available for predicting the final cost of projects. These cost prediction formulas have been well studied over the last 15 years. From the research, the EVM community has an understanding of project behaviors. We now know how to calculate the most optimistic predicted outcome for cost. And, we understand that projects perform less efficiently as they progress toward completion. For very large projects, we know from early results the range of likely final cost outcomes. Significant strides have been made in project management from the use of EVM measures; project managers now have available a few research derived prediction tools. Is there a path to improved prediction? In truth, advancement of outcome prediction knowledge for EVM-based projects has remained stagnant for nearly a decade. The prediction findings cited previously were established several years ago and have not been improved upon. Although there is more than 35 years of numerical evidence of project performance for many types of applications (defense, construction, software ....) from several countries, this EVM data is not available for research. If we could only get by the unfounded worry that by divulging our