The Failure of Risk Management: Why It's Broken and How to Fix It, 2nd Edition

This book should be required reading for any risk manager.It has an excellent history of the roots of risk management from the point of view of the various types of risk managers (actuaries, war quants, economists, and management consultants). You learn that category you fall into and the strength and weaknesses of you category.What I like most is the practical solutions that any risk manager can use to improve the quality of their risk management skills. Doug even gives you access to working examples.Once you read this book, you will be a better risk manager, or at least understand how your analysis may be doing more harm than good.

Es un enfoque diferente a la Gestión de Riesgos tradicional. Lectura amena y sencilla, y el autor trata de ser muy claro al explicar nuevos conceptos, los cuales son aplicables en la vida real sin necesidad de adaptaciones complejas con respecto a las metodologías tradicionales.

Doug Hubbard understands far better than most business leaders that, despite our high confidence, our intuitions about risk and probability are awful. Hubbard has for decades challenged the mindless practices of corporate risk teams and the frameworks, standards bodies and consultancies that inform them.Hubbard show exactly why the ordinal scoring of risks, heat maps, RPN, and of soft analyses peddled by the likes of the PMI and ISO 31000 are worse than useless, using examples from industry. He provides accessible explanations and practical examples of analyses done in academic and government/military circles, all of which support his claim that risk management is and has been broken in the corporate realm, and that low cost solutions are available, yet are ignored. His pragmatic and down-to-earth approach does a fabulous job of presenting intuitive Bayesianism while steering clear of academic jargon and mathematical digressions. This is as practical a guide as you will ever find.

The book is well structured and is full of wonderful researched information on both the downsides of conventional risk management techniques and better quantitative alternatives. It is a must have table book for anyone working in risk. To give the lessons in this book justice, I created a book club in my team and every week we discuss few chapters and share the lessons that we can take away and apply in our work. Every chapter has valuable insights that we can implement and help our company make better risk-based decisions.

This is essential reading for anyone in decision science. Gives an excellent overview of how the Knightsian terminology infiltrated organisations and a concise critique of the fallacy of ordinal scales that is spot on and relevant. Amusing at times, especially the line 'Who am I to question thinkers like Taleb?!' (after spending one chapter highlighting flaws in his 'Fat Tonyism' methodology) there is no shortage of substance - the accompanying one for one spreadsheet is a useful aide for those overawed by Monte Carlo and the calibration questions are also very useful representations of Hubbard's (and Tetlock's) point about overconfidence in SME's.At times it feels like an advert for Hubbard Research Training Sessions, but this is no bad thing - I've signed up as a result so mission accomplished!Overall, a great read from one of the leading voices in quantitative risk analysis.

A great book for those already familiar with quantitative methods of risk analysis as well as for any risk manager or decision specialist considering a quantitative approach. The chapter on calibration of expert opinions is very interesting.

Worth reading by anyone who can't afford to make suboptimal decisions.

As a risk consultant and trainer, I was greatly interested by this book. Yes, quantitative risk analysis is important, but should we throw to the bin all the concepts and tools of qualitative risk management? I dont think so. Public of risk management workshops and training course are very diverse, with different education background, different field of activities. The use of sampling methods like Monte Carlo opens tremendous possibilities of scenario analysis, but often at a heavy cost (external consulting services). Anyway, it is good to discover all the biases that are inherent to the current practice of qualitative risk analysis, and the author go deeply in the different aspects of these biases. So this book is very useful for risk practitioners in order to be aware of all the traps they may encounter. Also useful for operational manager or decision makers to evaluate what they may get when they implement risk management processes in their project or company, and maybe lead them to implement quantitative risk analysis. Grat book. I recommand.

Not 100% finished yet but the book is definitely a must read for every risk professional!