A Revised Recruiting Resource Model for Achieving the Army Personnel Strategy

Accounting for Digital Advertising

Jason M. Ward, Jeffrey B. Wenger, Irineo Cabreros, Daniel Schwam, Craig A. Bond, Samuel Absher

ResearchPublished Nov 6, 2023

The U.S. Army uses a variety of resources and tools to achieve its recruiting mission each year. In this report, the authors present results from an updated version of RAND Corporation's Recruiting Resource Model (RRM), a multipart statistical model that explores how trade-offs between key recruiting resources (bonuses, advertising, and recruiters) affect the Army's ability to achieve recruiting goals and the cost of doing so. They use the RRM to analyze the mix and level of resources required to meet the recruiting mission under alternative recruiting environments and recruit eligibility policies.

The RRM was updated to include more recent data to analyze the relationship between resource inputs and recruiting outcomes while incorporating the use of digital advertising, which has become an increasingly important recruiting resource in recent years. Consistent with previous iterations of the model, the results indicate that television advertising and, to a lesser extent, recruiters have positive associations with contract production and that these inputs are relatively more cost-effective than bonuses.

This research can help inform how the Army might move resources in a variety of recruiting environments. Making marginal changes along these lines in a purposeful manner over time—either broadly or at a more local level (as might be done in an experimental setting)—would be an appropriate first step in implementing the recommendations that arose from this research.

Key Takeaways

  • Television advertising expenditures were lower than the optimal level indicated by the RRM over the 2013–2018 period analyzed.
  • Modest increases in spending on recruiters are generally recommended when the recruiting environment is difficult. Under less adverse recruiting conditions, advertising can substitute for recruiters to achieve recruiting goals at a lower cost.
  • Bonuses are a costly and inefficient way of achieving recruiting goals. According to the results of all scenarios estimated based on data from fiscal years 2013–2018, the optimal solution reduces bonus spending.

Recommendations

  • The Army should increase advertising expenditures relative to levels observed prior to 2019. Across all the different scenarios examined, the optimized model recommends an 80-percent increase in spending on television advertising.
  • The Army should consider shifting resource use modestly toward more recruiters. This is likely beneficial in more-difficult recruiting environments.
  • The Army should reduce spending on bonuses. The association of bonuses with contract production is relatively small, and a large portion of bonuses are paid to recruits who would have been willing to join for a lower (or no) bonus amount. The results of the analysis recommend a 40-percent decrease in spending on bonuses. However, military occupational specialty bonuses might play an additional and important role in the composition of occupations that are not fully accounted for in the modeling.
  • The Army should consider other policies, such as more flexibility in recruit eligibility. Doing so could save money and contribute to meeting recruiting goals in the short run, though this might have higher downstream costs, including increases in early attrition, lower performance, and lower reenlistment rates.
  • The Army should consider conducting controlled experimental research on the effectiveness of recruiting resources. A series of well-designed and rigorously implemented randomized controlled experiments could help determine the true causal effect of Army advertising and other resources on contract production and enlistments.

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Ward, Jason M., Jeffrey B. Wenger, Irineo Cabreros, Daniel Schwam, Craig A. Bond, and Samuel Absher, A Revised Recruiting Resource Model for Achieving the Army Personnel Strategy: Accounting for Digital Advertising. Santa Monica, CA: RAND Corporation, 2023. https://www.rand.org/pubs/research_reports/RRA2108-1.html.
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