A Revised Recruiting Resource Model for Achieving the Army Personnel Strategy: Accounting for Digital Advertising
Abstract
This research provides ongoing analyses of the resources required to meet the goals of the U.S. Army People Strategy under alternative recruiting environments; recruit eligibility policies; and recruiting resources, such as bonuses, advertising, and recruiters. This research report presents results from an updated version of the RAND Corporations Recruiting Resource Model (RRM), a multi-part statistical model that explores how trade-offs between key recruiting resources affect the Army's ability to achieve recruiting goals and the cost of doing so. This project significantly updates and extends prior work on the RRM by Knapp et al. (2018) by examining the relationship between resource inputs and recruiting outcomes particularly contracts and accessions using the revised model and more-recent data. The updated model also incorporates digital advertising, which has become an increasingly important recruiting resource in recent years. Consistent with previous iterations of the model, our results indicate that television advertising and recruiters have large, positive associations with contract production, and these inputs are more cost-effective than bonuses. We tested the RRM's predicted recruiting outcomes by comparing thousands of iterations of alternative levels of resource utilization. These optimization exercises consistently point to large increases in advertising (primarily television) and a significant reduction in bonus spending as a more effective use of financial resources than the baseline allocations of these resources. Across ten different scenarios to which we applied the model, the average recommendation was for an 80-percent increase in television advertising spending and a 40-percent decrease in bonus spending. The model generally recommends less spending on digital advertising, but because we were limited to less-than-optimal data, these results should be interpreted with caution.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2023
- Accession Number
- AD1214580
Entities
People
- Craig A. Bond
- Daniel Schwam
- Irineo Cabreros
- Jason M. Ward
- Jeffrey B. Wenger
- Samuel Absher
Organizations
- RAND Corporation