The Failure of Risk Management: Why It's Broken and How to Fix It

The 2008 credit crisis, terrorism, Katrina, computer hackers, and air travel disasters all have something in common-the methods used to assess and manage these risks are fundamentally flawed. If risks cannot be properly evaluated, risk management itself becomes the biggest risk. The Failure of Risk Management shows you how to identify and fix these hidden problems in risk management.
Ineffective risk management methods, often touted as "best practices," are passed from company to company like a bad virus with a long incubation period: there are no early indicators of ill effects until it's too late and catastrophe strikes. Exploring why risk management fails—the failure to measure and validate methods as a whole or in part; the use of components known not to work; and not using components that are known to work—The Failure of Risk Management shows you how to measure the performance of risk management in a meaningful way, identify where risk management is broken, and fix it.
Respected expert and bestselling author Douglas Hubbard-creator of the critically praised Applied Information Economics (AIE)—uses real-world examples to reveal the serious problems in our current approaches to risk analysis. Hubbard skillfully illustrates how to use a calibrated risk analyses approach, and the many benefits that go along with it, along with checklists and practice examples to get you started.
One of the first resources to apply risk management across all industries, The Failure of Risk Management provides you with the tools you need to hit the ground running with radically better risk management solutions.
Here, you'll discover:
The diversity of approaches to assess and mitigate risks
Why many influential methods-both qualitative and quantitative don't work
Why we shouldn't always trust assessments based on "experience" alone
The fallacies that stop you from adopting better risk management methods
How those who develop models of risks justify (in error) excluding the biggest risks
Adding empirical science to risk management