Forecasting Marine Corps Enlisted Attrition Through Parametric Modeling

Abstract

The Marine Corps, as with any organization with a large workforce, must accurately monitor and more importantly predict the transition rates among personnel entering and exiting the enlisted and officer ranks. This emphasis is even more appropriate given that the Marine Corps has been authorized to increase the current authorized end strength by 13,000 personnel from Fiscal Year 2008 to Fiscal Year 2010. The purpose of this thesis is to apply parametric modeling (specifically survival analysis) to historical data sets of enlisted personnel in order develop a more efficient forecasting tool for military planners. It is the intent to include in the model those characteristics that significantly influence attrition behavior, and aggregate these findings to an efficient, yet effective forecasting model. Therefore, this thesis will analyze the interaction of time, individual characteristics, and those causal attributes that determine whether a Marine completes his or her contracted service. The current forecasting method used by the Marine Corps forecasts enlisted attrition annually. This study forecasts enlisted attrition monthly within occupational field. Hence, the data was structured to provide this depth of analysis. In comparison to the current forecasting method of exponential smoothing this study found that the use of survival analysis could be beneficial to not only forecast attrition, but also provide a descriptive assessment of attrition rates amongst occupation fields without loss of information due to averaging or weighting probabilities.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2009
Accession Number
ADA496756

Entities

People

  • Jeremy T. Hall

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Attrition
  • Business Administration
  • Coast Guard
  • Contracted Services
  • Data Sets
  • Enlisted Personnel
  • Management Personnel
  • Marine Corps
  • Military Organizations
  • Military Personnel
  • National Security
  • Organizational Structure
  • Personnel Management
  • Probability
  • Recruiting
  • United States
  • Warfare

Readers

  • Computational Modeling and Simulation
  • Personnel Management and Statistics in the Military and Department of Defense