Risk Analysis of Complex and Uncertain Systems (International Series in Operations Research & Management Science)

Description

In Risk Analysis of Complex and Uncertain Systems acknowledged risk authority Tony Cox shows all risk practitioners how Quantitative Risk Assessment (QRA) can be used to improve risk management decisions and policies. It develops and illustrates QRA methods for complex and uncertain biological, engineering, and social systems systems that have behaviors that are just too complex to be modeled accurately in detail with high confidence and shows how they can be applied to applications including assessing and managing risks from chemical carcinogens, antibiotic resistance, mad cow disease, terrorist attacks, and accidental or deliberate failures in telecommunications network infrastructure. Written for a broad range of practitioners, including decision risk analysts, operations researchers and management scientists, quantitative policy analysts, economists, health and safety risk assessors, engineers, and modelers, the book emphasizes methods and strategies for modeling causal relations in complex and uncertain systems to the point at which effective risk management decisions can be made. Individual sections of the book introduce QRA, show how to avoid bad risk analysis, illustrate the principles for doing better analysis, and then show specific applications and extensions.
Review:
This is an excellent, approachable read for any risk manager; understanding its examples requires only elementary probability, statistics and calculus, though the foundations are much deeper. The author uses direct language, and does not hesitate to declare a fashionable risk analysis technique "worse than useless." The author shows how not to do risk analysis, using simple but devastating examples to illustrate the weaknesses of prioritized investments, subject matter expert opinion, risk matrices and qualitative risk assessments, and the independence assumption. Then, case studies present constructive examples of good practice. Refreshingly, this text clearly distinguishes between threats from Mother Nature, and those posed by an intelligent adversary. There is unevenness, because this is an edited ensemble of papers originally published in a variety of technical journals; however, this is also a strength, because the appeal and scholarship underlying biological, engineering, and social science examples is broad. This is not a how-to guide, and won't help fill in a blank page risk analysis; however, this is an excellent source for the skeptical consumer of contemporary risk management advice and products, and hopefully will have some influence with policy makers who are the source of simplistic and dangerous guidance.
Gerald G. Brown
Distinguished Professor of Operations Research
Naval Postgraduate School
National Academy of Engineering
INFORMS Fellow

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