The Use of Time Series Forecasting in Contractor Performance Analysis.

Abstract

The application of time series forecasting is presented as a method of estimating either contract Estimates-at-Completion (EAC) or year-ahead contract costs based on information contained in monthly Contract Performance Reports (CPR). Considering the premise that the pattern of a contractor's expenditures becomes characteristic as the contract proceeds, a procedural approach is recommended for characterizing the cumulative Actual Cost of Work Performed (ACWP) using time series modeling. The recommended technique stresses the structuring of appropriate difference equations through the criterion of minimum residual variance. The main objectives of this report are: Development of a procedure for structuring forecasting models from non-stationary stochastic realizations. This specifically covers the identification and fitting of Autoregressive (AR), and integrated Autoregressive-Moving Averages (ARIMA) models; Illustration of the validity of the appropriate model through a sensitivity analysis using CPR information from two Communications-Electronics Command contracts.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1994
Accession Number
ADA288251

Entities

People

  • Richard J. D'accardi

Organizations

  • United States Army Communications-Electronics Command

Tags

DTIC Thesaurus Topics

  • Analyzers
  • Contracts
  • Cost Analysis
  • Costs
  • Data Analysis
  • Delphi Method
  • Difference Equations
  • Electronics
  • Equations
  • Identification
  • Probability Distributions
  • Random Variables
  • Residuals
  • Resource Management
  • Stationary
  • Statistics
  • Stochastic Processes

Readers

  • Computational Modeling and Simulation
  • Life Cycle Cost Analysis
  • Statistical inference.

Technology Areas

  • Microelectronics