Grabbing the Air Force by the Tail: Applying Strategic Cost Analytics to Understand and Manage Indirect Cost Behavior

Abstract

Recent and projected reductions in defense spending are forcing the military services to develop systematic approaches to identify cost reduction opportunities and better manage financial resources. In response, the Air Force along with her sister services are developing strategic approaches to reduce front-line mission resources, commonly referred to as the Tooth . However, an underemphasized contributing source of costs are mission support activities, commonly referred to as the Tail . With the tail historically representing a sizable portion of the annual Air Force budget, strategically managing cost behavior of these indirect activities has the opportunity to generate significant cost reductions. However, very little applied or academic research have focused on advancing the knowledge behind the economics of, or the analytic techniques applied to, these activities for cost management purposes. To address this concern, this dissertation investigates i) how organizations use analytic methodologies and data sources to understand and manage cost behavior, ii) how to identify underlying cost curves of concern across tail activities, iii) how to distinguish historical relationships between the tooth and tail, iv) how to improve the performance assessment of tail activities for improved resource allocation, and v) how to provide a decision support tool for tooth-to-tail policy impact analysis.

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Document Details

Document Type
Technical Report
Publication Date
Sep 17, 2015
Accession Number
ADA621827

Entities

People

  • Bradley C. Boehmke

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • C4I
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Business Administration
  • Computational Science
  • Data Mining
  • Data Science
  • Databases
  • Information Processing
  • Information Science
  • Knowledge Management
  • Management Personnel
  • Mathematical Programming
  • Network Science
  • Organizational Structure
  • Predictive Modeling
  • Recreation
  • Supply Chain Management
  • Systems Engineering

Readers

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