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It has become more complex for the U.S. Air Force to manage its rated officer population, due to the lengthy and costly training pipelines, declining availability of aircraft to train the rated officer force, and the effects of external factors that affect the retention of Air Force rated officers. The Air Force has always had to manage the rated officers in the regular Air Force, balancing the flows into the force, distributing them among the various rated officer career fields and aircraft, and monitoring the flows out of the force. However, it has not had to manage the flows into the two reserve components, the Air Force Reserve and the Air National Guard, quite as diligently because the supply of rated officers into those components was both abundant and cheap. Recent changes, such as the overall reduction in the number of aircraft, the pending elimination of the A-10 aircraft, the arrival of the F-35 aircraft, and the increase in civilian pilot hiring from the major airlines, have made it more challenging to manage rated officers in all components. As a result, it has become increasingly important to adopt an overall — or Total Force — perspective on the rated officer force. In this report, the authors document efforts to develop a long-term career field planning model for all rated officers across the Total Force — the Total Force Blue Line model — that can be used to assess policy alternatives and inform decisionmaking in managing the rated officer force.

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This report introduces the Aim Point Investment Model, an optimization model for portfolio-level resource allocation across U.S. Army programs and time. The report is intended to provide a technical overview of the model and its capabilities while also detailing the motivation for creating the model and recommendations from related research. The recommendations should be of interest to decisionmakers and those interested in improving decision support tools for asset allocation problems. In brief, the project's objective was to develop a method and tool to support quick-turn exploration of modernization investment portfolios in light of changing budget constraints and operational priorities in order to develop rough-order optimal investment strategies across a preestablished set of investment options and set of budget and requirement assumptions. Given the enormous complexity of the decision space, some sort of automated decision support tool was required. To develop that decision support tool, the authors explored alternative approaches to extracting the information needed about programs' relative utility and any constraints on the Army's ability to procure the capability from existing Army data sources. This report describes one of these approaches, which uses Army prioritization guidance—synthesized from several sources—combined with plausible constraints to produce resource allocation solutions that are consistent with the Army's stated modernization strategy.