Personnel and career management are critical to a well-trained U.S. Army Reserve (USAR), and end strength forecasts are an important input to recruiting and retention policy decisions. Currently, no single model is capable of providing such forecasts. The authors examined existing modeling tools and developed an Integrated Modeling Concept—a detailed plan for combining outputs from those tools to enable USAR to forecast 24-month end strength.
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Research Questions
- What paths do people take into and out of USAR?
- What capabilities for modeling these paths do existing tools provide?
- Where do gaps exist in the modeling landscape?
- How can existing data and modeling tools be combined to generate 24-month forecasts of USAR end strength?
The U.S. Army Reserve (USAR) is an integral part of the U.S. Army and the country's national defense. Its mission is to provide trained individuals who can serve as active duty soldiers when the mission calls for it. Well-trained service members are central to the USAR mission, and personnel and career management are critical to building a well-trained force.
End strength forecasts are an important input to recruiting and retention policy decisions, as well as resourcing and planning discussions with other Army components. However, generating these forecasts is a complex task due to the many paths into and out of USAR. Currently, no single model is capable of providing such estimates.
The authors examined available modeling capability and identified a set of modeling tools that can estimate portions of the personnel flows into and out of USAR. Most of these tools were designed to support policy analysis, not forecast end strength. Nevertheless, with the appropriate care and caution, the estimates generated by these tools can be combined to construct the desired 24-month end strength forecasts. A detailed plan for doing so—the Integrated Modeling Concept—is the primary product of this study.
Key Findings
- RAND has several modeling tools that are capable of predicting flows into and out of USAR, but none can generate 24-month forecasts of USAR end strength because none was designed for that purpose.
- Most of the relevant modeling tools were designed to estimate the effects of policy changes on recruiting and retention outcomes, holding all other factors constant; nevertheless, with appropriate care and caution, the estimates generated by these tools can be combined to construct the desired end strength forecasts.
- The Integrated Modeling Concept (IMC) assigns existing modeling tools to personnel flows based on the capabilities of each tool, with machine learning used to fill as many gaps as possible.
- The IMC performs best when forecasting total USAR end strength. Because the modeling tools do not predict changes in rank, end strength forecasts for subpopulations, such as enlisted reservists or reservist officers, are likely to be less accurate.
Recommendations
- The IMC, which provides some flexibility in the assignment of modeling tools to personnel flows, should be configured to deliver the outputs and capabilities that best support the Office of the Chief of the Army Reserve's planning processes.
- Any future implementation of the IMC should begin with a careful assessment of how IMC outputs will be used to inform USAR personnel management and resource planning.
Table of Contents
Chapter One
Introduction
Chapter Two
Personnel Flows and Career Paths
Chapter Three
Modeling Tools
Chapter Four
The Integrated Modeling Concept
Chapter Five
Conclusion
Appendix A
The Decomposition of Personnel Flows
Appendix B
The Clustering Approach to Understanding SELRES Career Paths
Appendix C
The Machine Learning Model
Research conducted by
The research described in this report was sponsored by the United States Army and conducted by the Personnel, Training, and Health Program within RAND Arroyo Center.
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