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The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty Hardcover – June 9, 2009
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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
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
A Groundbreaking must-read for anyone who makes business decisions in the face of uncertainty
As the recent collapse on Wall Street shows, we are often ill-equipped to deal effectively with uncertainty and risk. Yet every day we base our personal and business plans on these kinds of uncertainties, whether they be next month’s sales, next year’s costs, or tomorrow’s stock price.
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. Instead of the usual anachronistic statistical jargon, Savage presents complex concepts in plain English, connecting the seat of the reader’s intellect to the seat of their 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.
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1. There is a whole part of statistics called Non-Parametric statistics which overcome the short-coming of average, and variance. So his statements that statisticians are not aware of some of the short-coming of average, and have no tools to deal with it is wrong.
1. He define a Random Variable (RV) as an uncertain Variable. Well, RV is mapping of representation of events and outcomes to numbers. For instance, a toss of a coin can have two outcome Head or Tail, so mathematically one can represent Head as , and tail by numbers x.
2. He also miss-informs the readers about the concept of dependency with his example of the two ladders that are connected. If ladder 1 has a probability of falling equal to 0.1, and ladder 2 has a probability of falling equal to 0.1, does it mean that the probability of them falling when connected is 0.01, of course not. By adding a connector we have changed the essence of the problem. This can be compared with throwing two dices. While the probability of having a 3 on each dice is 1/6, the probability that the sum (which is the result of throwing both dices at the same time) will be equal to 6 is not 1/36 but it is equal to the sum of the probabilities of throwing a 1 and 5, 2 and 4, 3 and 3, 5 and 1, 4 and 2 or 5/36 (not 1/36 as the author may want us to believe).
He changes the essence of the problem but mislead the readers that he is still using the same initial assumptions.
3. Lastly his description of the Black Swan is wrong. If a wheel has numbers between 0 and 1, and one is turning the wheel in hope that it will stop at a number larger than 0.2 that the wheel goes flying and breaks has no effect on the probability that it will stop at a certain number. The two events are independent, and we have a new problem that is created.
Now if the wheel has one number 0.000001 in it wheel, one may assume that the wheel will stop at this number is extremely slim, and will not even bother taking it into consideration, and it will be discredited. Hence, this number when it occurs it will be the same as the black swan.
4. He states that quant could not predict the outcome of the market meltdown, and that there exists no tool to predict such events. Well, there exists a distribution called (GEV) that does only that, while it is not publicized it does a good job.
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.
I lost all respect for Mr. Savage once he wandered off the intellecutal road into the weeds of his liberal nirvana. I guess I should not have been surprised though because one look at his picture on the inside flap of the book gave a shining clue that this man was going to be far to the left of the political distribution.