Evaluating the Bias of Alternative Cost Progress Models: Tests Using Aerospace Industry Acquisition Programs

Abstract

This study evaluates the quality of cost estimates produced by each of four cost progress models: a random walk model, the traditional learning curve model, a production rate model (fixed-variable model), and a model incorporating both learning curve and production rate effects (Bemis production rate adjustment model). Emphasis is placed on assessing the level of bias associated with these models and determining the influence of various factors on model performance. Findings indicate, on average, that the learning curve and Bemis models underestimate unit costs, while the random walk and fixed-variable models overestimate unit costs. Different factors are evaluated to determine their significance in explaining variations in the bias of unit cost predictions. The author also describes the relationships between the significant variables and model cost prediction bias. Overall findings indicate that the Bemis model is superior to the other cost progress models because it exhibits the least bias and is not significantly influenced (in terms of bias) by variations in the factors considered.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA262870

Entities

People

  • David A. Tagg

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Airframes
  • Analysis Of Variance
  • Budgets
  • Correlation Analysis
  • Cost Analysis
  • Cost Estimates
  • Cost Overruns
  • Data Science
  • Federal Budgets
  • Information Science
  • Knowledge Management
  • Regression Analysis
  • Statistical Analysis
  • Surveys
  • Test And Evaluation
  • United States

Readers

  • Computational Modeling and Simulation
  • Life Cycle Cost Analysis
  • Regression Analysis.

Technology Areas

  • Space