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  • The Failure of Risk Management

  • Why It's Broken and How to Fix It, 2nd Edition
  • By: Douglas W. Hubbard
  • Narrated by: Stephen Bel Davies
  • Length: 13 hrs and 29 mins
  • 4.4 out of 5 stars (14 ratings)

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The Failure of Risk Management

By: Douglas W. Hubbard
Narrated by: Stephen Bel Davies
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Summary

The Failure of Risk Management provides effective solutions to significant faults in current risk analysis methods. Conventional approaches to managing risk lack accurate quantitative analysis methods, yielding strategies that can actually make things worse. Many widely used methods have no systems to measure performance, resulting in inaccurate selection and ineffective application of risk management strategies. These fundamental flaws propagate unrealistic perceptions of risk in business, government, and the general public.

This book provides expert examination of essential areas of risk management, including risk assessment and evaluation methods, risk mitigation strategies, common errors in quantitative models, and more. Guidance on topics such as probability modelling and empirical inputs emphasizes the efficacy of appropriate risk methodology in practical applications.

Recognized as a leader in the field of risk management, author Douglas W. Hubbard combines science-based analysis with real-world examples to present a detailed investigation of risk management practices. This revised and updated second edition includes expanded coverage of innovative statistical methods and new cases of current risk management issues such as data breaches and natural disasters.

©2020 Douglas W. Hubbard (P)2020 Gildan Media
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What listeners say about The Failure of Risk Management

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Must Read for all risk managers.

If you are a risk manager or not, this book might just change your perspective on everything.

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  • Overall
    5 out of 5 stars
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    4 out of 5 stars

The final nail in the coffin for Qualitative Risk?

The author has extensive experience and shares many stories. The content is well-researched and thoroughly explained. Food for thought.

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    4 out of 5 stars
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    2 out of 5 stars
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Important attitude adjustment for risk managers

Overall this is a very important message, and everyone in risk management needs to hear it. This book doesn’t go into enough detail to actually solve the problem - it’s more of an appetiser for Hubbard’s other work. But it’s still worthwhile, and if you’re not the one actually doing the work, this may be all you need in order to understand that change is necessary.

The performance is unfortunate, though. The narrator is very good at delivering the prose, but obviously hasn’t been provided with any notes on how to read the technical content. For example, Bayes Theorem says P(A|B) = P(B|A).P(A) / P(B), which is painfully narrated as “P times A divided by B equals P times B divided by A, times P times A, divided by P times B.” If you can contain your screams through this sentence, you’ll be fine with the rest of the book.

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    4 out of 5 stars
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    4 out of 5 stars

Good anecdotes on risk topics, flawed narration

I liked the argument in favor of mathematically and statistically rigorous treatment of risk. It stresses to use Monte Carlos and distributions, capturing all the uncertainty and correlations. A few areas took the listener through practical steps, like how to calculate 90% confidence interval from a standard deviation, whereas most parts were more philosophical rather than practical. The case studies were interesting and varied, from oil, volcanology, IT and cybersecurity etc. The book taught me that risk management is a science, not an art or management quip. Overall the book isn't a great textbook or reference; rather it's a collection of anecdotes and good practice.

The narration was clear but flawed. Sadly the narrator was not of a mathematical or scientific background, evidenced by regular mispronounciation of certain words and equations throughout, for example "chi-squared" as "chee" and "Richard Feynman" as "fain man" and the natural logarithm ln() was pronounced "in", which confused me for a moment. Probabilities were misread every time, e.g. P(B|A) read as "P times B divided by A". Bayes Theorem was misread every time so far as to be completely unrecognisable. For a book about statistics, and full of probabilities, this was completely unacceptable.

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