Risk-Based ROI, Capital Budgeting, and Portfolio Optimization in the Department of Defense https://www.dau.edu
current and planned IT investments (DoD, 2005). DoDD 8115.02 (DoD, 2006) implements policy and assigns responsibilities for the management of DoD IT investments as portfolios within the DoD enterprise, where it defines a portfolio to include outcome performance measures and an expected ROI. The DoD Risk Management Guide for Defense Acquisition Programs (2014) requires that alternatives to the traditional cost estimation need to be considered because legacy cost models tend to inadequately address costs associated with information systems or the risks associated with them (Mun, Ford, & Housel, 2012). Literature Review Portfolio Modeling in Military Applications Optimization is a rich and storied discipline designed to use data and information to guide decision making in order to produce an optimal, or very close to optimal, outcome. However, “government agencies have been much slower to use these approaches to increase efciency and mission efectiveness, even though they collectmore data than ever before” (Bennett, 2017). For these government agencies, optimization solutions can utilize the large amounts of data fromdiferent sources to provide decisionmakers with alternative choices that optimally meet agency objectives. Greiner, McNutt, Shunk, and Fowler (2001) correctly stated that standard economic measures such as internal rate of return (IRR), net present value (NPV), and ROI are commonly used in evaluating commercial-based R&D projects to help identify optimal choices. However, such economicmeasures in their commercial form are of little use in evaluating weapon systems development eforts. Therefore, their paper examines the challenges faced by the DoD in determining the value of weapon systems during the R&D portfolio selection processes. Similarly, Burk and Parnell (2011) reviewed the use of portfolio decision analysis in military applications, such as weapon systems, types of forces, installations, and military R&D projects. They began with comparing military and commercial portfolio problems in general and discussing the distinguishing characteristics of the military decision environment: hostile and adaptive adversaries, a public decision process with multiple stakeholders, and high systemcomplexity. Based on their work, the authors observed that the “most widespread prominent feature of these applications is the careful modeling of value frommultiple objectives” (Burk & Parnell, 2011). What they found surprising was that “quantitative methods of measuring and valuing risk are surprisingly rare, considering the high level of uncertainty in the military environment” (Burk & Parnell, 2011). Their
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Defense ARJ, January 2020, Vol. 27No. 1 : 60-107
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