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.
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