Mini Tutorial 3: Risk Informed Decision Making An Introduction

Dr. Smart is a Cost Engineer with NASA’s Jet Propulsion Laboratory. He has experience supporting both NASA and the Department of Defense in the theory and application of risk, cost, and schedule analytics for cutting-edge programs, including nuclear propulsion and hypersonic weapon systems. For several years he served as the Cost Director for the Missile Defense Agency. An internationally recognized expert on risk analysis, he is the author of Solving for Project Risk Management: Understanding the Critical Role of Uncertainty in Project Management (McGraw-Hill, 2020). Dr. Smart received the 2021 Frank Freiman lifetime achievement award from the International Cost Estimating and Analysis Association. In 2010, he received an Exceptional Public Service Medal from NASA for the application of risk analysis. Dr. Smart was the 2009 recipient of the Parametrician of the Year award from the International Society of Parametrics Analysts. Dr. Smart has BS degrees in Mathematics and Economics from Jacksonville State University, an MS in Mathematics from the University of Alabama in Huntsville (UAH), and a PhD in Applied Mathematics from UAH. Abstract: All projects are inherently uncertain. To make wise decisions, projects should incorporate an analysis of uncertainty in considering potential alternatives. One process that provides an approach to incorporating uncertainty in the decision-making process is known as risk-informed decision making (RIDM). RIDM can be applied whenever there is uncertainty involved and competing alternatives. This tutorial provides a comprehensive of everything needed to conduct RIDM analysis. Examples of technical failures, cost overruns, and schedule delays for historical project projects are provided, giving clear evidence of project uncertainty and provide strong motivation for conducting risk analysis. The terminology of risk is presented. Risk and uncertainty for a variety of sources – cost, schedule, technical, and safety – are discussed. The mathematical basis for risk analysis is discussed, along with a simple worked example. The tools and techniques necessary for the conduct of risk analysis are provided as well. Best practices and potential pitfalls are provided. The RIDM process is outlined and contrasted with a similar approach called risk-based decision making. An overview of risk management is provided and its relationship with RIDM is described. The tutorial concludes notional case studies of RIDM. Session Materials:https://dataworks.testscience.org/wp-content/uploads/formidable/23/Thrs_Mini_Smart-1.pptx