The Failure of Risk Management: Why It's Broken and How to Fix It,   ISBN:9780470387955

Customer Rating: 

By way of back ground I am an actuary (FCAS, ASA, MAAA) and a Chartered Enterprise Risk Analyst (CERA). I live in the world of risk quantification and really enjoyed and agree with Hubbard's comments on the subject. I also think he does a great job of expressing quantitative concepts in a manner that is accessible to non-quants.

One key theme that I related to was how more subjective or qualitative methods can get you into trouble. I often see this when performing modeling studies around risk for my clients. It's not uncommon for companies to take a look at the first time forecasts I perform and state "there is no way it can get that bad." They are saying this because they have already come up with a subjective estimate without really digging into the numbers. Even as time passes and the numbers do get "that bad" many are still so anchored to their original subjective assessment of the risk in question that they will continue to argue against the quantified trends.

One comment I often hear from clients is "You can't model that." My rebuttal has always been, "If you are making a decision, I assert you are modeling it. In you head you are putting together scenarios and thinks up consequences." Why not take it out of your head and try and put more rigor into your estimate? Hubbard uses the phrase "better is good" and I fully agree.

Other great points he makes include:
- Organizations are currently not consistently quantifying risk - real life examples I have seen can be as basic as different divisions using totally different interest or commodity assumptions in the decisions they make
- Qualitative risk ranking can get you into trouble
- There is a definite opportunity to take actuarial type standards to modeling insurance risk and apply them to other operational, financial and strategic risks that organizations face
- His four risk modeling fallacies (chapter 8)
- To understand risk, you need to understand the distribution of potential outcomes.

To my "You can't model that" comment above, I have picked up another of his books, "How to Measure Anything" and am really enjoying it as well.

Customer Rating: 

Doug Hubbard follows up his smash success on measurement with a penetrating look at why some of the most popular methods of risk assessment not only don't work, but are worse than no analysis at all. He argues convincingly, based on after-the-fact surveys of how various companies' decisions worked out, that "balanced scorecard" approaches typically make management feel much more confident while making the actual outcome no better, and often worse. The Analytical Hierarchy Process (AHP) fares almost as badly. Most telling is his finding, again backed by a cogent array of survey and interview data, that the purveyors of supposedly empirical methods rarely empirically study how well their methods work! He concludes by offering several improved methods to assess risk, understand what data would be most valuable to collect, correctly estimate and report one's uncertainty about predictions, and thus place risk management on a much more solid analytical footing.

He builds up to his conclusions with a competent and readable review of relevant applied probability, statistics, and simulation modeling, then a summary of what has generally been done in real decision-making in recent years. None of these sections is totally comprehensive or completely rigorous, but they don't need to be. He strikes a nice balance between readability and careful explanation of what the typical decision-making reader, somewhat knowledgeable but not highly technical, needs to know. The quantitatively naive manager will find it enlightening, if sometimes daunting; the quantitatively expert reader will find cause to quibble here and there, but no major mistakes or crucial omissions.

Warning: many of the established pooh-bahs associated with risk assessment as it's done now won't like this book. As he predicted, actuaries will continue to prefer methods firmly, even if dangerously, rooted in past experience; operations research analysts and their ilk ("war quants," he calls them) will continue to prefer increased modeling elegance over better metrics on which to base the models; economists will continue to rely on far too many unsubstantiated assumptions; and, worst of all, management consulting snake oil salesmen will continue to construct elaborate, impressive-sounding "methodologies" with lots of buzzwords and procedures and little verifiable empirical content. All of the above will try to reassert the excellence of their approaches and deprecate or marginalize Hubbard's criticisms. Believe them at your peril: Hubbard got it pretty much right. His findings and recommendations are most surely not the final, definitive answer, but they're a large promising step in the right direction. Highly recommended for anyone interested in doing risk management competently.

Customer Rating: 

Hubbard shines a skeptical light on what passes for "risk management" in so many organizations. He systematically tears down the claims that common risk management techniques are "proven" and provides extensive research behind the flaws in each method. He explains the avoidable errors in mathematical models, simulations and even expert opinion. By the time he is done the reader is convinced that all of the most popular methods in risk management are akin to astrology.

But then he explains how to fix these problems and without reinventing the wheel. He focuses on pieces of the current methods that actually show solid evidence in controlled tests of improving decisions and forecasts. He shows how experts can be trained to overcome a systemic bias of "overconfidence" and how to test models against outcomes. His solutions involve some simple corrections that can be used immediately and he also outlines a much more ambitious plan to build a cross-departmental, cross-company, cross-industry, cross-governmental model that would have "Lego" style components. This is a path we should all plan on following soon.

Customer Rating: 

I have been involved in business consulting, investment management, business valuation and corporate governance for most of the past 25 years, and I can say without hesitation that Doug Hubbard's book on The Failure of Risk Management is an outstanding and elucidating work. I have never been a risk manager per se, but I have frequently been deeply involved in risk assessment and risk management activities, so I do have firsthand experience in this topic.

This book is an eye opener from the outset. In Part One of his book ("An Introduction to the Crisis") Hubbard begins with fundamental, obvious questions about risk management that everyone (not just risk managers!) should be asking. For example: How do you know that your risk management program is effective? Would anyone in your organization know if your risk management program didn't work? (...and how would they know - and define - that it wasn't working?). These are very simple, obvious questions, yet I have never heard them asked by management teams or even members of boards where I have served as director. Alas, there is a huge "placebo effect" in so much of what passes for risk management nowadays - perhaps that is why it is so popular.

For example, consider the following: If risk management programs really do work, then it seems logical to assume that companies in a given industry with a (self proclaimed) "highly effective" risk management program would show greater shareholder returns, less earnings volatility, and better safety and regulatory compliance records than other companies in their peer group who lack such a program. Yet there appears to be no valid evidence that current risk management practices, taken as a whole, serve to improve overall corporate performance. The evidence just isn't there.

In Part Two ("Why It's Broken"), Hubbard provides a thorough and convincing overview of the many shortcomings of modern risk management practices. As a self proclaimed "Quant," he strongly endorse quantitative analytics as the most effective approach to both measuring risk as well as the implementation of risk management programs. His approach is compelling and convincing; after all, if we can't measure accurately, how can we rely on our system of "assessing" (i.e., measuring)? It sounds pretty obvious, doesn't it? Without metrics, what tools do we have, other than generalizations, hunches, intuition, and "gut feel"? Sure, certain qualitative techniques are helpful, but qualitative risk analytics is really effective (in my view) only for the most obvious risks, and therefore no better than having no risk management program at all. Indeed, Hubbard makes a compelling argument that ineffective risk management can be worse - possibly much worse - than having no risk management program at all.

Part Two also includes concepts that Hubbard brilliantly applies to risk management practices. This includes certain characteristics of human nature, such as a proven tendency to be overconfident in our estimates (of risk, but also of other estimates), that must be acknowledged and addressed in order for risk management programs to work effectively. He also provides a practical method of adjusting or "calibrating" for such overconfidence. Similarly, there is a fascinating discussion on risk correlations and how risk events seldom materialize in isolation from one another. Consider (my own example) certain risk correlations in mortgage banking. Banks that invested in mortgage backed securities no doubt undertook some sort of risk analysis of these investments. They also had risk management systems in place for their mortgage lending business. But how many lenders tied these two risk programs together, and properly concluded that a collapse of one market would also result in the collapse of the other? Thus, it's not just a case of accurately assessing and management individual risks, but also in considering the extent to which there might be a "domino" or "cascading" effect among different risk factors.

In reading Part Two (especially Chapters 6 and 9), it occurred to me that this book should be read by anyone and everyone involved in investing or lending money.

As one might expect, Part Three of Hubbard's book ("How to Fix It") embraces a scientific and quantitative approach to improving risk management. Once you get to this point in the book, you will find it very difficult to disagree. Another important concept introduced by Hubbard is that of language and communication with respect to risk. As a potentially murky and subjective topic (if not downright Byzantine at times) risk management systems require clear and concise language and terminology to be effective. Thus, if two different managers in the same factory concur that the likelihood of a risk event materializing is "very likely," we should not assume that they both agree on the use of the term "very likely." One may feel that this means the odds are one in three, while the other feels the odds are one in ten.

Hubbard is clearly on target when he proposes that risk managers apply scientific methods to risk management. His suggestions on how to do this are fairly simple and practical. Without such methodologies, risk managers are sailing through dense fog with an unreliable compass. You might even feel that you are making great headway, but if you can't measure where you are going, you will never know if you are really making any progress.

Finally, one of the greatest benefits to me in reading this book has less to do with the specifics of risk management and a lot more to do with the way people think. Consider, for example, why your sales team frequently falls short of their sales projections, or why so many portfolio managers buy stocks near their highs and sell near their lows. Or why risk management programs are so popular, and yet seldom work. Hubbard provides a brilliant and penetrating look into the human mind in the context of business decision making as a whole - not just with respect to risk. For me, this was an excellent "upside surprise" to this book. I finished reading this book several months ago, and I still think about it all the time. It has made a lasting and beneficial impression that I will never forget.

Customer Rating: 

This book is a must for every professional, undergraduate, graduate or post-graduate student dealing with risk management. Douglas Hubbard manages to combine proper mathematics with the basics of measurement and still keeping things within reach of an audience that does not necessarily has to have too much mathematical skills. Speaking of experience, I started as a PhD in Physics using Monte Carlo for simulating Magnetic forces in semiconductor interfaces. Then I transposed these methods more than 20 years ago to medical equipment, did some work in safety, environment, food hygiene and finally ended up in innovation and entrepreneurship. All of these tracks have an intensive relation with risk. I saw many of the errors (and even more) in risk management as (nearly literally) described in this book. So the level of relevance is there.

The treatment in three parts is well done, the structure is both professional and inviting to read more. The skill Douglas Hubbard apparently has in combining almost prosaic phrases with good scientific content, makes this book to be a reference book and a novel at the same time. An example for many of us (including me) that do not have this skill. I applied already formerly likewise approaches but with the reading of the book, I succeeded in leaving some very heavy (and expensive) calculation programs for the marvelous and illicit Excel sheets Douglas is posting on his website, at least for some applications. As a tutor I take the book of Douglas and leave the "heavy programs" for later on. This "step up" is amazing for students as they get gradually into the complexity of the matter.

I read some of the negative critics and think some of the people did not read the book properly. Of course when you are used to make large qualitative studies, I can imagine this book is at least a bit "annoying". But as I will always remember the quote of one of the Top Risk assessors and managers of Philips Medical Systems in Holland, "measurement is knowledge and when someone pretends to have a better risk assessment and/or risk management, let him prove to effectively be better". I love the way Douglas Hubbard takes these principles in to real life practice. I applied the risk approach as described in the book already many times and it does work amazingly well.

I strongly recommend this book to professional, tutors and students (getting) involved in risk (as well the risk assessment as the risk management). It can be applied to several domains of risk such as but not limited to: clinical trial, environmental risk, general business risk, safety of products risk, risk of medical equipment, food-safety risk, innovation & entrepreneurial risk (business plan or business case risk). That's were I already applied it with success.

Prof. Dr. Johan Braet, Antwerp University, Faculty of Applied Economics, Department of Environment and Technology, Innovation Management & Entrepreneurship, Risk Assessment (LCA) & Risk Management