An essential guide to the calibrated risk analysis approach.
The Failure of Risk Management takes a close look at misused and misapplied basic analysis methods and shows how some of the most popular "risk management" methods are no better than astrology! Using examples from the 2008 credit crisis, natural disasters, outsourcing to China, engineering disasters, and more, Hubbard reveals critical flaws in risk management methods and shows how all of these problems can be fixed. The solutions involve combinations of scientifically proven and frequently used methods from nuclear power, exploratory oil, and other areas of business and government. Finally, Hubbard explains how new forms of collaboration across all industries and government can improve risk management in every field.
©2009 Douglas W. Hubbard (P)2012 Audible, Inc.
"Doug Hubbard, a recognized expert among experts in the field of risk management, covers the entire spectrum of risk management in this invaluable guide. There are specific value-added take aways in each chapter that are sure to enrich all readers including IT, business management, students, and academics alike" (Peter Julian, former chief-information officer of the New York Metro Transit Authority. President of Alliance Group consulting)
"In his trademark style, Doug asks the tough questions on risk management. A must-read not only for analysts, but also for the executive who is making critical business decisions." (Jim Franklin, VP Enterprise Performance Management and General Manager, Crystal Ball Global Business Unit, Oracle Corporation)
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Hubbard gives good examples why simple risk modeling techniques such as red, yellow, green rankings and others are too simple. He makes the argument that those that say that at least they are something and better than nothing can be blatantly wrong since they give a false since of control. The last part of the book he makes the case for Monte Carlo analysis. The power of Monte Carlo and other techniques like it is the ability to look for multiple variables impacting a risk and looking for causality and other things that can amplify the effects of one variable on another.
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