Applying the Pareto Principle to Distribution Assignment in Cost Risk and Uncertainty Analysis
Risk Track
RSK13_Presentation_ApplyingParetoPrincipletoDistAssignmentinCostRiskandUncertAnalysis_Glenn
RSK13_Paper_ApplyingParetoPrincipletoDistAssignmentinCostRiskandUncertAnalysis_Glenn
Abstract:
Significant effort and statistical knowledge is required in order to complete an accurate uncertainty analysis of a cost estimate. First, a representative sampling of data points must be collected in order to model appropriate distributions for each random variable in the estimate. Additionally, correlation between the random variables in the estimate must be properly assessed and applied. Finally, to generate the cumulative distribution of total costs (i.e., S-Curve) either the joint cumulative distribution function must be computed or an approximation technique such as Monte-Carlo simulation must be used.
However, collecting the data required to accurately model the distribution of each random variable and correlation between the random variables is difficult and time consuming. To help cost estimators develop uncertainty analyses with limited available resources, a variety of default distributions for random variables and default correlation application techniques between random variables have been proposed by authors and are incorporated in the leading cost estimating software applications. However, an overreliance on default distributions and correlation is likely to provide inaccurate results since it is not a sampling from the actual population of interest.
This is where the Pareto Principle can be applied. The Pareto Principle, named after the Italian economist Vilfredo Pareto, states that 80% of effects come from 20% of the causes. Applied to cost risk analysis, this would lead to focusing efforts to assign accurate cost risk distributions to the major cost drivers, while not assigning cost risk to the many WBS elements that do not drive cost. The purpose of this paper is to examine the potential effects of working to develop cost risk distributions for major cost drivers, and compare this to the overall effect of assigning cost risk distributions to all elements with default distributions. Assumptions are varied for the proportion of random variables which receive modeled distributions and the proportion of random variables which receive default distributions. Also, assumptions are varied for how closely both the modeled distributions and default distributions match the actual population mean, variance and skewness. Finally, observations are provided to help the cost community manage their limited resources to generate improved uncertainty analyses in cost estimates.
Author(s):
James R. Glenn
Missile Defense Agency
James Glenn is a Business Analyst Leader for Computer Sciences Corporation supporting Missile Defense Agency’s Cost Estimating and Analysis Directorate. Mr. Glenn has over seven years of operational research experience, specializing in cost estimating and data analysis for both industrial and governmental clients. Mr. Glenn has a B.S. degree in Industrial Engineering from Clemson University and an M.S. degree in Industrial and Systems Engineering from Virginia Tech.
Christian Smart
Missile Defense Agency
Dr. Christian Smart is currently employed as the director for cost estimating and analysis at the Missile Defense Agency (MDA). In this capacity, he is responsible for overseeing all cost estimating activities developed and produced by the agency, and directs the work of a 100-person team. Prior to joining MDA, Dr. Smart worked as a senior parametric cost analyst and program manager with Science Applications International Corporation. An experienced estimator and analyst, he was responsible for risk analysis and cost integration for NASAs Ares launch vehicles. Dr. Smart spent several years overseeing improvements and updates to the NASA/Air Force Cost Model and has developed numerous cost models and techniques that are used by Goddard Space Flight Center, Marshall Space Flight Center, and NASA HQ. In 2010, he received an Exceptional Public Service Medal from NASA for his contributions to the Ares I Joint Cost Schedule Confidence Level Analysis and his support for the Human Space Flight Review Panel led by Norm Augustine. He has given numerous presentations on cost modeling and risk analysis both in the U.S. and abroad. He was awarded best of conference paper at the 2008 Annual Joint ISPA-SCEA conference in Noordwijk for The Fractal Geometry of Cost Risk, best of conference paper at the 2009 Annual Joint ISPA-SCEA conference in St. Louis for The Portfolio Effect and the Free Lunch, best of conference paper at the 2010 Annual Joint ISPA-SCEA conference in San Diego for Here, There Be Dragons: Considering the Right Tail in Risk Management, and best of conference paper at the 2011 Annual Joint ISPA-SCEA conference in Albuquerque for Covered with Oil: Incorporating Realism in Cost Risk Analysis. Dr. Smart was named the 2009 Parametrician of the Year by ISPA. He is a SCEA certified cost estimator/analyst (CCEA), a member of the Society for Cost Estimating and Analysis (SCEA) and the International Society of Parametric Analysts (ISPA). Dr. Smart is a past president of the Greater Alabama Chapter of SCEA, is the managing editor for The Journal of Cost Analysis and Parametrics, and serves as the Region III VP on the SCEA national board of directors. Dr. Smart earned bachelors degrees in Economics and Mathematics from Jacksonville State University, and a Ph.D. in Applied Mathematics from the University of Alabama in Huntsville.
Hetal Patel
Missile Defense Agency
Hetal Patel is an Operation Research Analyst for the Missile Defense Agency’s Cost Estimating and Analysis Directorate. Mrs. Patel servers as the cost lead for the Global Deployment Program Office and has over seven years of operational research experience, specializing in cost estimating and data analysis for both industry and government. Mrs. Patel has a B.S. degree in Management Information Systems and a Master of Business Administration from Auburn University. She is also a SCEA certified cost estimator/analyst.
Lawrence Johnson
Missile Defense Agency
Lawrence Johnson is an Operations Research Analyst for the Missile Defense Agencys Cost Estimating and Analysis Directorate. Mr Johnson serves on the cost team for the Global Deployment Program Office and has over 15 years of cost estimating experience in government and industry. Mr Johnson has a B.A. degree in Accounting from Athens State University and is a Certified Public Accountant.