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As budgets decrease, it becomes increasingly important to determine the most effective ways to invest in modeling and simulation (M&S). This article discusses an approach to comparing different M&S investment opportunities using a return on investment (ROI)-like measure. The authors describe methods to evaluate “benefit” (i.e., increased readiness, more effective training, etc.) received from an investment and then use those metrics in a decision analysis framework to evaluate each M&S expenditure. Finally, they conclude by discussing the importance of viewing M&S investments from a Department of Defense (DoD) Enterprise view, evaluating investment over multiple years, measuring well-structured metrics, and using those metrics in a systematic way to produce an ROI-like result that DoD can use to evaluate and prioritize M&S investments.
Systems acquisition inherently contains elements of uncertainty that must be effectively managed to meet project cost, schedule, and performance objectives. While the U.S. Department of Defense has a record of employing systems engineering technical management processes (including risk management) to address these uncertainties for major weapon systems acquisition, the application of risk management to Military Construction (MILCON) projects is a recent development. This research studies the use of a formal risk management program on a MILCON project and assesses whether such use influences the project’s total cost growth relative to that of U.S. Army Corps of Engineers’ historical data. A case study methodology is employed assessing the National Geospatial-Intelligence Agency (NGA)’s multibillion dollar NGA Campus East program.
Government contracting is rife with opportunities for miscommunication and misperception. This can undermine trust and fuel spirals of conflict. For this article, the authors interviewed participants and analyzed Government Accountability Office (GAO) bid protest decisions involving Department of Defense source selections. They found agency, vendor, and GAO practices that trigger and fuel these spirals. Contracting agencies and GAO can take steps to improve communication, reduce inconsistencies, and reduce perceptions of bias, thereby mitigating costly bid protests.
Evaluating how best to invest government information technology (IT) dollars means making choices. Should agencies strengthen infrastructure with energy-efficient servers and increased network bandwidth, purchase software to cut costs, increase collaboration, or invest more to meet stakeholders’ future needs? Is there a connection between the way agencies invest IT dollars and successful mission accomplishment? In this article, the authors show a connection between IT investment allocations and organizational performance in federal government agencies, and demonstrate how higher performing agencies invest differently in IT than lower performing agencies. Federal managers can compare their organization’s IT investment portfolio with high-performing agencies and compare their investment allocations with other federal organizations with similar missions to determine optimum IT investment allocations for their agencies.
The impact of organizational culture, management leadership style, and employee commitment on organizational outcomes has long been studied, but no clear answer exists for which concepts most affect acquisition outcomes and increase organizational productivity. A key contribution of this study is the notion that they are interrelated and may work synergistically in improving acquisition outcomes. The author claims that the interaction of these elements, when combined, may produce a total effect that is greater than the sum of their individual elements. A conceptual model was identified and used as the foundation for building hypotheses. Structural Equation Modeling was used to analyze the data gathered, and a path diagram was developed for this study using Analysis of Moment Structures (AMOS).
Publisher: Cambridge, MIT Press
Copyright Date: 2002
Hard/Softcover: Hardcover: 217 pages
Reviewed by: Dr. Shannon Brown, Associate Professor of National Security Studies, Industrial College of the Armed Forces, Washington DC