A Comparative Analysis of the Cost Estimating Error Risk Associated with Flyaway Costs Versus Individual Components of Aircraft

Abstract

A shrinking workforce, unstable budgets, and rapidly changing objectives under stricter time constraints characterize today's cost analysis and acquisition environment. In concert with this environment, cost analyst positions have rapidly decreased as demonstrated by Aeronautical Systems Centers 54% decline in total authorized slots from 1992 to 2001. The question is how to deal with this more with less' mentality. The purpose of this research is to investigate and measure the risks associated with taking a macro versus micro approach to aircraft cost estimation. By analyzing the fidelity of a cost estimate developed at the flyaway cost level versus a cost estimate developed at the individual components level, this research provides guidelines for appropriate allocation of cost analyst resources, This objective is accomplished by looking at the cost estimation error risk of recurring costs at level one of the Work Breakdown Structure (WBS) and at level two of the WBS, Results show that there is a statistically significant difference between estimating at the differing WBS levels, However, from a practical standpoint, the difference in dollar terms is too small to be considered significant, As a result, program manager should allocate resources based on other constraints such as time allotted to complete the estimate or required level of visibility into the estimate

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2003
Accession Number
ADA415102

Entities

People

  • Jonathan D. Ritschel

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force
  • Aircraft Equipment
  • Aircrafts
  • Airframes
  • Computational Science
  • Cost Analysis
  • Cost Estimates
  • Data Analysis
  • Data Science
  • Databases
  • Fighter Aircraft
  • Information Science
  • Knowledge Management
  • Monte Carlo Method
  • Regression Analysis
  • Reliability
  • Test And Evaluation

Readers

  • Computational Modeling and Simulation
  • Economics