Predicting the Number of Potential Military Recruits over the Next Ten Years with Application to Recruiter Placement

Abstract

The object of this thesis was to evaluate Navy recruiter placements, as resource allocation directly affects organizational efficiency and mission success. In order to produce a model to assist decision makers, this study analyzed (1) demographic characteristics of past military applicants; (2) recruiter assignment histories; (3) station ZIP codes; and (4) predicted populations within each ZIP code. ZIP code-level analysis was performed on more than 4 million records provided by the Defense Manpower Data Center (DMDC). The records consisted of all military applicants (those who applied for military service with the intention of enlisting) and accessions (those who reported to basic training) from October 1998- September 2006. Records contained home of record ZIP code and demographic information including age, race, gender, and education. Woods and Poole population data, provided by Navy Recruiting Command (CNRC), was then merged in order to incorporate the 990 possible combinations of demographic characteristics for each ZIP code of the national population from 2000-2020. Computation of service-specific propensities (that is, expected numbers of military applicants) showed that the Navy has been successful in its attempt to effectively place recruiters in order to exploit the available target market. A series of comparison tables was developed to aid decision makers.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2007
Accession Number
ADA473810

Entities

People

  • Donald L. Britton

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Basic Training
  • Data Analysis
  • Data Centers
  • Data Sets
  • Demography
  • Department Of Defense
  • Education
  • Geographic Regions
  • Manpower
  • Military Science
  • Navy
  • Personnel Management
  • Recruiting
  • Training
  • Uncertainty Principle
  • United States

Readers

  • Computational Modeling and Simulation
  • Naval Personnel Management