Investigating Navy Officer Retention Using Data Farming

Abstract

The allocation of nearly 30% of the Navys budget to personnel costs, and the importance of manning fleet requirements to maintain operational readiness create a critical need for the Navy to effectively manage the size of the force. The Navys personnel planners use the Officer Strategic Analysis Model (OSAM) to project officer end-strength based on policies, plans, and historical loss rates. The application of data farming to this model allows for investigation of different scenarios that can provide insight into both the behavior of the model and the behavior of the officer corps under various conditions. This study uses Design of Experiments (DOE) techniques to develop and implement an experimental design that determines the degree of stochastic variation in OSAM and explores the effect of a three-year period of poor retention of Unrestricted Line (URL) officers in pay grades O3 through O6. Analysis of results across multiple replications of a single design point indicate that OSAM produces very little stochastic variation. Regression modeling of the results allows planners to accurately and precisely predict the effect of this poor retention scenario on specific groups. This predictive capability provides the opportunity for proactive approaches to solving potential retention problems.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2015
Accession Number
AD1008911

Entities

People

  • Aurel N. Dehollan

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Engineered Resilient Systems
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Basic Programming Language
  • Computer Programs
  • Computers
  • Data Science
  • Data Sets
  • Databases
  • Department Of Defense
  • Descriptive Analytics
  • Experimental Design
  • Graphical User Interface
  • Information Science
  • Officer Personnel
  • Operations Research
  • Personnel Management
  • Statistics
  • Strategic Analysis
  • Test Sets

Readers

  • Computational Modeling and Simulation
  • Naval Personnel Management