PhD student wins research prize

Annually the Defense Acquisition University (DAU) holds a research paper competition. This year first-prize (making it a “Hirsh Prize Recipient”) was awarded to the paper “Calculating Return on Investment for US Department of Defense Modeling and Simulation,” authored by, among others, William E. Waite, a UConn 2nd year PhD student. The paper will be presented during the DAU Acquisition Community Symposium on Tuesday 12 April 2011, and published in April’s edition of Defense Acquisition Research Journal.

Within any complex organization there exists a need to measure and monitor the effectiveness of expenditures; that is, there is a ubiquitous necessity to monitor how well agents allocate limited resources between the many potential projects they are presented, within a specific institutional context. Such measurement is particularly challenging for institutions (or, in situations) where a market mechanism for pricing different outcomes is not available. The United States Department of Defense (US-DoD) is one such institution.

Each year, the US-DoD allocates billions of dollars to external contractors, as well as internal departments, to pursue modeling-and-simulation (M&S) projects. The benefits of these initiatives are generally not monetary – or easily convertible to a specific monetary value. Rather, the desired results are seen in measures of increased readiness of the country’s armed forces, better trained individuals, improvements in procedures or approaches that result in fewer human casualties during combat missions, and the like. Given the nature of these benefits, it is not surprising that measuring the “return-on-investment” (ROI) of a US-DoD M&S project presents government officials with a formidable challenge.

In “Calculating Return on Investment for US Department of Defense Modeling and Simulation,” the authors provide a systematic methodology to approach address this particular challenge. By utilizing a decision analysis framework based on the economic principle of utility maximization, the authors create a framework in which the US-DoD can obtain ROI-like results for ranking and evaluating projects, which can then be used in resource allocation decisions and analysis.