Forecasting Attrition Volume: A Methodological Development

Abstract

Accurate attrition forecasting is crucial for properly planning the recruitment and training of Canadian Forces (CF) members and maintaining the CF strength as well as for managing the CF budget. This report documents a methodological development in forecasting attrition volume; new procedures for forecasting attrition based on years of service (YOS) have been proposed. The report provides a discussion regarding the rational for the new procedures and explanations why the predictions based on new procedures better reflect CF attrition behaviour. In the end, the new procedures were validated and compared with previous procedures using the real CF personnel data. The results from the new procedures showed a strong agreement between forecast and actual attrition. Compared with the previous forecasting method, the new procedures deliver predictions that better reflect CF attrition behaviour at many levels. The report recommends using the proposed procedures for forecasting CF attrition. These procedures can be applied to attrition analyses at many levels within the CF, for example, non-commissioned members (NCMs) and officers (OFFs), Army, Navy and Air Force, different military branches and different military occupations, etc. This report is targeted at the analysts within Defence Research and Development Canada. This work will equip them with a better approach for forecasting CF attrition, and improve the consistency and transparency of attrition analyses across different research groups. Given that forecasting attrition is so important for a number of relevant human resources initiatives, such as effective recruitment, promotion, planning, and budget management, this work will have a positive impact in all of these areas.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2009
Accession Number
AD1001569

Entities

People

  • M. Fang

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Agreements
  • Air Force
  • Attrition
  • Classification
  • Consistency
  • Databases
  • Engineering
  • Human Resources
  • Management Personnel
  • Military Personnel
  • National Security
  • Operations Research
  • Personnel Management
  • Security
  • Training
  • Transparencies

Readers

  • Computational Modeling and Simulation
  • Naval Personnel Management
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.