Using Earned Value Data to Detect Potential Problems in Acquisition Contracts

Abstract

Government contractors report earned value (EV) information to government agencies in monthly Contract Performance Reports (CPR). Though major differences may exist in the data between subsequent CPRs, we know of no government effort to detect these occurrences. The identification of major changes may locate and isolate problems and thus prevent million and billion dollar cost and schedule overruns. In this study, we develop an approach to identify changes in the Cost Performance Index (CPI) and the Schedule Performance Index (SPI) that may indicate problems with contract performance. We find the detection algorithm indentifies changes in the CPI and the SPI that correspond to large future changes in the Estimate at Complete (EAC). The ability to detect unusual changes provides decision-makers with warnings for potential problems for acquisition contracts.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2011
Accession Number
ADA539357

Entities

People

  • C. Grant Keaton

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Engineered Resilient Systems
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Algorithms
  • Change Detection
  • Contractors
  • Contracts
  • Data Mining
  • Data Science
  • Databases
  • Department Of Defense
  • Detection
  • Financial Management
  • Governments
  • Identification
  • Information Science
  • Probability
  • Statistics

Readers

  • Defense Acquisition Program Management
  • Government Contracting/Procurement.
  • Life Cycle Cost Analysis