An Assumptions-Based Framework for TRL-Based Cost and Schedule Models
Journal of Cost Analysis and Parametrics
The Technology Readiness Level scale has been used to assess progress and provide a framework for developing technology. Many Technology Readiness Level-based cost and schedule models have been developed to monitor technology maturation, mitigate program risk, characterize transition times, or model schedule and cost risk for individual technologies as well technology systems and portfolios. We present a four-level classiﬁcation of models based on the often-implicit assumptions they make. For each level, we clarify the assumptions made, review evidence that supports the assumptions, and propose alternative or improved models. Our results include a justiﬁcation of the recommendations of the US General Accounting Ofﬁce on Technology Readiness Level, two new methodologies for robust estimation of median transition times and for forecasting transition times using historical data, and a set of recommendations for Technology Readiness Level-based regression models.
Bernard El-Khoury is a consultant with the Boston Consulting Group in Dubai, United Arab Emirates. He has a master’s degree in Technology and Policy from the Massachusetts Institute of Technology, a master’s degree in Industrial Engineering from Ecole Centrale Paris, and a bachelor’s degree in engineering from Ecole Centrale Paris. His research interests are technology cost and schedule forecasting, and power systems modeling.
C. Robert Kenley is an Associate Professor of Engineering Practice in Purdue’s School of Industrial Engineering in West Lafayette, Indiana. He has doctoral and master’s degrees in Engineering-Economic System from Stanford University, a master’s degree in statistics from Purdue University, and an bachelor’s degree in management from the Massachusetts Institute of Technology. He has over thirty years’ experience in industry, academia, and government as a practitioner, consultant, and researcher in systems engineering. He has published papers on systems requirements, technology readiness assessment and forecasting, Bayes nets, applied meteorology, and the impacts of nuclear power plants on employment.