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<p>U.S. statutory policy requires the armed services to continuously balance manpower inventory with congressionally authorized requirements. Inaccurate forecasts put the Navy's budget at risk and degrade overall mission readiness. Navy policymakers must be able to rely on accurate inventory forecasts to develop necessary manpower plans that steer inventory to match planned authorizations. Strength planners, in turn, rely on forecasting models like the Officer Strategic Analysis Model (OSAM) in an attempt to accurately predict future inventory levels. This study utilizes applications of data farming to OSAM to simulate Unrestricted Line Officer (URL) inventory over a seven-year period. Additionally, the research utilizes applications of Design of Experiments (DOE) to project Surface Warfare Officer (SWO) inventory across a variety of assumptions, including a proposed Enhanced Probationary Officer Continuation and Re-designation (EPOCR) policy. Analysis finds that current policy will reduce FY2016 URL inventory by 8% over a seven-year period, and over-execute SWO inventory authorizations by 40%. We find that EPOCR reduces operating strength deviation (OSD) in total SWO inventory strength by 12% by FY2022. Additionally, implementing a low accession plan and a high transfer plan is the most robust in correcting OSD. When implemented correctly, EPOCR has the potential to decrease OSD to modest levels with minimal risk of under-execution.
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<br>Subjects: Manpower; end strength; design of experiments; simulation; Officer Strategic Analysis Model (OSAM); inventory projection; data farming. Robust Analysis; Meta-Modeling</div>
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Bazalaki, Peter</div>
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