Resources Required to Meet the U.S. Army's Enlisted Recruiting Requirements Under Alternative Recruiting Goals, Conditions, and Eligibility Policies

by David Knapp, Bruce R. Orvis, Christopher E. Maerzluft, Tiffany Berglund


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Research Questions

  1. What are the tradeoffs among recruiting resources (e.g., recruiters, advertising, enlistment incentives)?
  2. How do these tradeoffs depend on overall accession goals, recruiting environment, recruit eligibility policies, and monthly training seat targets?
  3. What is the optimal mix of recruiting resources?
  4. How does the optimal mix depend on overall accession goals, recruiting environment, recruit eligibility policies, and monthly training seat targets?

The purpose of this research is to enhance the effectiveness and efficiency of the Army's use of recruiting resources and policies. A theoretical model was estimated based on the Army's recruiting experience. Using this model, a tool was created for the Army's use in assessing alternative courses of action and optimizing resource levels and mix under alternative enlisted accession goals, labor market conditions, and recruit eligibility policies. Understanding how recruiting resources and recruit eligibility policies work together as a system under varying recruiting requirements and environments is critical for decisionmakers who want to use their limited resources to efficiently and effectively achieve the Army's accession requirements. The recruiting resource model developed in this report considers the relationship among the monthly level and mix of recruiting resources, recruit eligibility policies, accumulated contracts, and training seat targets. It models how these factors combine to produce monthly accessions and the number of enlistment contracts at the fiscal year's end that are scheduled to access in the following fiscal year.

Key Findings

Recruiters, TV advertising, and enlistment incentives exhibit a positive relationship with enlistment contract production.

  • The return on investment depends on recruit eligibility policy, recruiting environment, and, most critically, on the accession goal.

The Recruiting Resource Model (RRM) represents a step forward in helping Army leaders shape a cost-efficient strategy capable of achieving the Army's accession requirements.

  • The RRM can be used to predict how a chosen set of recruiting resources, recruit eligibility policies, and the recruiting environment combine to produce accessions, an entry pool for the following year, and a resourcing cost.

Army planners can use the RRM tool (the RRM paired with its optimization algorithm) to consider the potential cost and resourcing requirements for a range of recruiting contingencies.

  • The optimization algorithm of the RRM tool is designed to find the cost-minimizing portfolio of recruiting resources for a target accession goal conditional on the recruiting environment and Army-established recruit eligibility policies.
  • The RRM tool can determine a cost-minimizing resourcing plan for a fiscal year.
  • It can be used to compare the sensitivity of resourcing plans under alternative recruiting environments.
  • It can be used to compare alternative resourcing plans.
  • It can be used to compare cost tradeoffs of alternative eligibility policies.
  • It can be used to consider within-year changes in resourcing plans necessary to achieve an accession mission.
  • It can be used to consider multiple-year resourcing scenarios.

Table of Contents

  • Chapter One


  • Chapter Two

    Overview of Recent Resource Use and Eligibility Policies

  • Chapter Three

    Data Used for This Study

  • Chapter Four

    Recruiting Resource Model

  • Chapter Five

    Model Demonstration and Optimization

  • Chapter Six


  • Appendix A

    Example of Changes in Production Elasticities

Research conducted by

The research described in this report was sponsored by the Assistant Secretary of the Army for Manpower & Reserve Affairs and conducted by the Personnel, Training, and Health Program within the RAND Arroyo Center.

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