Investigating Schedule Slippage

Abstract

Past research shows that schedule slippage within the acquisition community often adversely affects the cost and performance characteristics within a program. To minimize the risk of underestimating schedule growth, a program manager needs a reliable initial schedule estimate. Statistical models can provide such estimates; however, they require accurate historical data and predictive drivers. Many archival studies have investigated potential drivers of schedule growth. In this article, we review several of those studies that investigated schedule slippage and highlight common potential drivers of schedule growth, ending with a list of variables for estimators to consider for incorporating into future predictive models.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA441770

Entities

People

  • Edward D. White Iii
  • James V. Monaco

Organizations

  • Defense Acquisition University

Tags

Communities of Interest

  • Air Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Air Force Research Laboratories
  • Air Launched
  • Aircrafts
  • Contracts
  • Databases
  • Department Of Defense
  • Fighter Aircraft
  • Information Science
  • Military Acquisition
  • Procurement
  • Statistical Analysis
  • Systems Engineering
  • Tactical Aircraft
  • Test And Evaluation
  • Unmanned Spacecraft

Readers

  • Computational Modeling and Simulation
  • Defense Acquisition Program Management
  • Economics