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The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, by Sam L. Savage
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A must-read for anyone who makes business decisions that have a major financial impact.
As the recent collapse on Wall Street shows, we are often ill-equipped to deal with uncertainty and risk. Yet every day we base our personal and business plans on uncertainties, whether they be next month’s sales, next year’s costs, or tomorrow’s stock price. In The Flaw of Averages, Sam Savageknown for his creative exposition of difficult subjects describes common avoidable mistakes in assessing risk in the face of uncertainty. Along the way, he shows why plans based on average assumptions are wrong, on average, in areas as diverse as healthcare, accounting, the War on Terror, and climate change. In his chapter on Sex and the Central Limit Theorem, he bravely grasps the literary third rail of gender differences.
Instead of statistical jargon, Savage presents complex concepts in plain English. In addition, a tightly integrated web site contains numerous animations and simulations to further connect the seat of the reader’s intellect to the seat of their pants.
The Flaw of Averages typically results when someone plugs a single number into a spreadsheet to represent an uncertain future quantity. Savage finishes the book with a discussion of the emerging field of Probability Management, which cures this problem though a new technology that can pack thousands of numbers into a single spreadsheet cell.
Praise for The Flaw of Averages
“Statistical uncertainties are pervasive in decisions we make every day in business, government, and our personal lives. Sam Savage’s lively and engaging book gives any interested reader the insight and the tools to deal effectively with those uncertainties. I highly recommend The Flaw of Averages.”
—William J. Perry, Former U.S. Secretary of Defense
“Enterprise analysis under uncertainty has long been an academic ideal. . . . In this profound and entertaining book, Professor Savage shows how to make all this practical, practicable, and comprehensible.”
—Harry Markowitz, Nobel Laureate in Economics
- Sales Rank: #126047 in eBooks
- Published on: 2012-03-13
- Released on: 2012-03-13
- Format: Kindle eBook
From the Inside Flap
Despite all its promise, the Information Age is also laden with a dizzying array of technological, economic, and political uncertainties. While the electronic spreadsheet brought the power of business modeling to tens of millions, in so doing, it also paved the way for an epidemic of what Sam Savage calls the Flaw of Averages. This set of systematic errors occurs in all types of business and scientific endeavors when smart people focus on single average values in the face of uncertainty and risk, and it is an accessory to the economic catastrophe that culminated in 2008. The Flaw of Averages also ensures that plans based on averages of such uncertainties as customer demand, completion time, and interest rate are below projection, behind schedule, and beyond budget. In his book, Savage draws on recent breakthroughs in technology, along with new data structures and management protocols, to offer an approach to curing the Flaw of Averages.
Savage begins by providing a basis for intuitively grasping and visualizing risk and uncertainty, using simple everyday props such as game-board spinners and dice. He refers to such statistical jargon as standard deviation and covariance as Red Words, and instead uses straightforward, everyday language throughout the book. He does not assume any statistical background on the part of the reader, but claims that for those with extensive training in the field, the first section of the book will repair the damage. He then describes how risk and uncertainty are handled in the field of finance, where the Flaw of Averages was first systematically conquered by Modern Portfolio Theory. Savage describes how the recenteconomic turmoil was caused in part by clinging blindly to this early work while not adhering to its fundamental principles. He then shows how these principles still form an excellent foundation for managing uncertainty and risk in other areas of industry and government, and provides examples in supply chain management, project portfolios, national defense, healthcare, climate change, and even sex.
In the book’s final section, Savage reveals current developments in the emerging field of Probability Management—a path towards increased transparency and a potential cure for the Flaw of Averages. Finally, the book includes a Red Word Glossary that defines statistical terms in plain English to assist readers in defending themselves against those wielding technical mumbo jumbo.
The goal of The Flaw of Averages is to help you make better judgments involving uncertainty and risk, both when you have the leisure to deliberate, and, more importantly, when you don’t. Its approach of a more transparent representation of uncertainty is helping people and some big companies to make better decisions today.
From the Back Cover
"Statistical uncertainties are pervasive in decisions we make every day in business, government, and our personal lives. Sam Savage's lively and engaging book gives any interested reader the insight and the tools to deal effectively with those uncertainties. I highly recommend The Flaw of Averages."
—William J. Perry, former U.S. Secretary of Defense
"Enterprise analysis under uncertainty has long been an academic ideal. . . . In this profound and entertaining book, Professor Savage shows how to make all this practical, practicable, and comprehensible . . . the Distribution String . . . represents a major breakthrough in the communication of risk and uncertainty."
—Harry Markowitz, Nobel Laureate in Economics
"This is a book written for laymen with enough interesting insights to engage even the most scholarly professional."
—Douglas Hubbard, author of How to Measure Anything
"Sam Savage is the Edward Tufte of risk."
—Matthew Raphaelson, Executive Vice President, Wells Fargo
A GROUNDBREAKING MUST-READ FOR ANYONE WHO MAKES BUSINESS DECISIONS IN THE FACE OF UNCERTAINTY
In The Flaw of Averages, Sam Savage—known for his creative exposition of difficult subjects—describes common avoidable mistakes in assessing risk in the face of uncertainty. He explains why plans based on average assumptions are wrong, on average, in areas as diverse as finance, healthcare, accounting, the war on terror, and climate change. Savage refers to anachronistic statistical jargon as Red Words, which he defines as things that may not be uttered in a singles bar. Instead, he presents complex concepts in plain English (Green Words), backed up by interactive simulations at www.FlawofAverages.com, which connect the seat of the intellect to the seat of the pants.
Savage also presents the emerging field of Probability Management aimed at curing the Flaw of Averages through more transparent communication of uncertainty and risk. Savage argues that this is a problem that must be solved if we are to improve the stability of our economy, and that we cannot repeat the recent mistakes of applying "steam era" statistics to "information age" risks.
About the Author
Sam L. Savage is a Consulting Professor of Management Science and Engineering at Stanford University, and a Fellow of the Judge Business School at the University of Cambridge.
Most helpful customer reviews
102 of 110 people found the following review helpful.
Plenty of selling, not enough teaching
By KTR73
So, let me start by saying that I think this book had a ton of potential. I couldn't put it down after reading the first several chapters. The author is witty, clearly very intelligent and has thought a lot about his subject matter. He clearly describes the problem(s) through the use of clever analogies. My favorite is his comparison of using averages to that of a drunk walking down the highway. On average, the drunk's path is along the center line - but on average, he is dead. But, the book in my opinion has some serious flaws.
The essence of the book is that you should not use an average number in your predictions / forecasts / etc. Rather, you should use a distribution (e.g., simulations) instead. More specifically, he recommends the use of "Probability Management" which is his brainchild - basically boiling down to sharing probability distributions that are "certified" by designated specialists in the organization. This ensures that your work takes interrelationships into account, whereas separate simulations might miss the boat.
The main problem with the book, in my opinion, is that he talks far too much about the problem and far too little about the solution. He spends chapter after chapter talking about where the problem exists (or previously did exist), but doesn't give much in the way of details for the alternative. Even when the alternative is discussed, it is rarely in enough detail to glean any real kind of information about the solution to the problem other than a cursory overview.
The book also includes a lot of superfluous chapters that don't seem to fit with the book. For example, chapter 35 is about World War II statisticians (one in particular) that used a clever trick to figure out how many German tanks were created based on those captured by the US Army. While the chapter was interesting, I'm not exactly sure why it was in the book - maybe leading up to the next chapter regarding the war on terror? In the end, it seemed to me that there was too much fluff.
I would have given the book a lower rating, but the author was too funny and interesting to go that far. Also, I think it depends on the type of person you are - I'm a doer, a self-taught programmer and I like solving problems and implementing solutions. A different personality may have enjoyed the book differently and not minded the things that I did.
55 of 62 people found the following review helpful.
About a simple flaw at the heart of so many bad decisions
By Douglas W. Hubbard
Sam Savage has written a book that reveals what is behind a simple flaw in so many management decisions. This book leads the manager who is used to accounting-style, point-estimate thinking to the world of thinking with probabilities. His writing style is light (sometimes even funny) but the content is meaty.
Savage criticizes what he calls "steam era" concepts of statistics which most stats courses seem stuck in and introduces decision making under uncertainty in a way that is much more welcoming than most books on this topic. I suspect that if more people had a professor like Sam Savage as their first mentor on statistics, there would be far fewer people with bad memories of that course.
His approach is all about avoiding intimidating terminology and getting hung up on esoteric concepts. In particular, he explains the concepts of Monte Carlo simulations in a way that might just get the reader excited about the power of the tool. He is not only an expert in MC simulations himself (he has developed many new innovations in the method) but is also an expert in how to explain it to a wide audience.
This is a book written for laymen with enough interesting insights to engage even the most scholarly professional.
44 of 49 people found the following review helpful.
The first statistics book for everyone
By Aaron C. Brown
As other reviewers have noted, this is an exceptional account of what you need to know about statistics, without any of the boring or intimidating stuff people like to layer on. No combinatorics, no measure theory, no calculus. It's clear and entertaining, with helpful links to simulations and animations on the web. The illustrations are amusing and useful, the overall production quality is significantly better than similar books. The writing is skillful and lively.
Experts (and I consider myself one) will learn some new things and, more important, learn effective ways to explain things they already know. Novices will learn what they need, and sharpen their thinking skills. People in between will unlearn a lot of nonsense, and replace it with good stuff, and get the confidence to ignore self-proclaimed experts with dense jargon and impenetrable formulas. Key concepts are reduced to easy-to-remember "mindles." There are examples from most areas of finance, including some quite advanced, and business; with a few from other fields. What more could you want?
Well, one more thing, but it's impossible. The author is the son of Jimmie Savage, and I consider his The Foundations of Statistics one of the great accomplishments of human thought. It was his intellectual precision and genius, and those of a few other people, that allows statistics to be made simple. Before that work, people were impossibly confused about the basics. It would have been nice to see that acknowledged instead of ridiculed.
However, I realize so many people are traumatized and intimidated by statistics that it takes a little iconoclasm to motivate them. But why did it have to be from Jimmy Savage's son? Why not someone whose parents were killed by an overmathematical analysis that overruled common sense?
The sections on finance, my specialty, are quite deep. His explanations of options, portfolio management and risk are excellent. It reads at the level of Kiplinger's Personal Finance magazine, but it makes the points of more intimidating authors such as Benoit Mandelbrot, Nassim Taleb and Kent Osband. His accounts of business management issues a bit more superficial, but still excellent.
I do have a few specific gripes, that will bother no one but nerds. He uses "Monte Carlo simulation" to mean simulation of a random event. This is a near-universal error. Monte Carlo means creating randomness that doesn't exist to get a deterministic result. It matters because anyone can simulate a random event, and it's an obvious idea. Monte Carlo can wonderful, unexpected answers to seemingly intractable questions, but it requires a lot of precise mathematics to do correctly.
Another gripe is he defines "Value-at-Risk" (VaR) as just a percentile. There is much more to VaR. For example, he estimates the distribution of return on movie investments by resampling from 28 past movies, which includes one blockbuster. Someone familar with VaR would realize that one observation is not enough to reliably estimate either the probability or potential size of blockbusters; and those factors are very important to the result. So she would resample among the other 27 movies, and call that the distribution inside the 95% VaR limit. To estimate what might happen outside the VaR limit, she would look at a much longer record of movies to get enough observations of blockbusters. This is necessarily a judgmental process (it's called "stress testing") because she's bringing in less comparable data. The end result is a range of profits where normal conditions apply and you can make reliable probability forecasts; you optimize in this range; and a much larger range where you have only qualitative guesses about probabilities; you create plans to maximize probability of survival in these ranges.
I cannot think of a person who will not benefit significantly from this book. It won't make people forget his father (thankfully) but it's one of the few books worthy to be on the same shelf.
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