Improved Methodology for Developing Cost Uncertainty Models for Naval Vessels
Abstract
The purpose of this paper is to analyze the probabilistic cost model currently in use by Naval Sea Systems Command Cost Engineering and Industrial Analysis Division (NAVSEA 05C) to predict cost uncertainty in naval vessel construction and to develop a better method of predicting the ultimate cost risk. The data used to develop the improved approach is collected from an analysis of the CG(X) class ship by NAVSEA 05C. NAVSEA 05C cost risk factors are reviewed and analyzed to determine if different factors are better cost predictors. The cost model factors investigated in this paper include data elicitation methods, probability distribution function (PDF) choice, correlation effects, and Money Allocated is Money Spent (MAIMS) principle effects. The most significant impact is seen with MAIMS and data elicitation effects. PDF choice and correlation effects have lesser impact upon the cost model. Data quality is directly affected by data elicitation methods and influences the choice of probability distribution used to give the best predictor of cost risk. MAIMS and correlation effects are shown to make a significant impact to the overall cost model. Program managers and analysts can readily implement the enhanced models using commercial Excel (trademark) add-ins, such as Crystal Ball (trademark) or @Risk and integrate them into their current cost risk analysis and management practices to better mitigate risk and control project cost. The presentation includes 23 briefing charts.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 22, 2009
- Accession Number
- ADA527700
Entities
People
- Cinda Brown
Organizations
- Naval Postgraduate School