The U.S. Army Medical Service Corps Area of Concentration Matching System

Abstract

The purpose of this study is to develop an algorithm-based talent management system for designating midgrade U.S. Army Medical Service Corps (MSC) officers to specialized areas of concentration (AOCs). The AOC matching system (AOC-MS) utilizes machine learning classifiers to predict officer aptitude for specialized AOCs, informing early career MSC recruitment and talent development efforts. AOC-MS then utilizes matching algorithms and integer linear programs to create optimal matches between officers and AOCs that meet the needs of officers and of the MSC. During a pilot program, AOC-MS outperformed the current designation system. This study will serve as the basis for MSC AOC designation reform. Its implications are applicable to any large-scale military talent management problem.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2020
Accession Number
AD1126570

Entities

People

  • Diego A. Rincon

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Business Administration
  • Computational Science
  • Data Mining
  • Data Science
  • Dimensionality Reduction
  • Employment
  • Health Services
  • Information Science
  • Information Systems
  • Kernel Functions
  • Machine Learning
  • Mathematical Models
  • Network Science
  • Operations Research
  • Personnel Management
  • Students
  • Supervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Aerospace logistics and air mobility.
  • Military Leadership and Professional Education.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML