Rabu, 20 April 2011

[P819.Ebook] Download PDF The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, by Sam L. Savage

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The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, by Sam L. Savage

The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, by Sam L. Savage



The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, by Sam L. Savage

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The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, by Sam L. Savage

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 Savage�known 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: #99314 in Books
  • Published on: 2009-06-09
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.10" h x 1.50" w x 6.40" l, 1.39 pounds
  • Binding: Hardcover
  • 416 pages

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.

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

13 of 13 people found the following review helpful.
Useful explanations lost in hype
By David J. Aldous
Unusual style, intermediate between a serious attempt to explain a simple yet important statistical idea in plain words and graphics, and the frothy "management secrets" style that permeates the Business section of an airport bookstore, the latter reflected in breezy writing, a layout of short chapters containing short sections, and the admirably inexpensive price. The idea can be said in 5 words -- "don't put averages into spreadsheets" -- where averages refer to expectations about the future. A typical illustration is what Operations Research calls the Newsboy Problem, which supposes you buy the daily paper wholesale, sell retail, but are stuck with any unsold copies. If you sold exactly 100 copies every day then you would simply order 100 copies; if your sales vary but average 100 a day, then the best number to order is (typically) not exactly 100, because of asymmetry between profit on sold copies and opportunity cost of lost sales if you run out. In such simple settings the idea is rather obvious, but now imagine some business spreadsheet, with actual figures from last year which combine in some complicated way to get last year's actual profit. It's natural to try to estimate next year's profit by entering estimates of each line entry and having the spreadsheet recalculate; but in any complicated setting there are always asymmetries between upside and downside and one does not get the correct "average profit" so easily. And one is interested not only in averages but also in risks of large losses.

This is no mystery to statisticians, just one of 100 workaday concepts not particularly emphasized in a typical college statistics course -- though as the book implies, worthy of more emphasis in a business statistics course. Scattered through the book are the components of a potentially great 30-page chapter illuminating this idea via graphical ideas of representing distributions as histograms, and describing contexts where asymmetries are important. For instance: bonuses for meeting a target, inventory and supply-demand, options, a project takes as long as its longest component, and interesting analogs with portfolio theory.

It would have been valuable to extend these 30 pages to either (i) in depth case studies, or (ii) a wide-ranging book explaining 10 different statistics ideas in 10 chapters. But instead, this book becomes a mashup of historical and personal anecdotes, superficial descriptions of case studies, some of the "popular science" style topics in probability and statistics covered in many other books, and witticisms about traditional mathematical statistics as "Steam Era statistics". As the author implies, it would be useful if Excel and open source analogs had an option for entering distributions instead of numbers. Alas, this book turns into a plug for the author's Probability Management software, and case studies turn into one paragraph testimonials.

5 of 5 people found the following review helpful.
The Flawed Flaw of Averages
By Chris Jeanty
A thoughtful look into how business management and how to overcome the field's bias in its decision making process of discounting risk. Sam Savage constructs what amounts to a resource textbook for the masses . It is written intuitively, but rather clumsily. Savage, despite trying hard to frame himself as a common man, cannot hide the fact that he has been in academia for too long and unable to mask his inability to transcribe in `commonspeak.' Savage's inability to express complex ideas in a clear concise manner led to a patchwork of watered down examples broken into non-flowing parts that lacked much order or improved even slightly the explanation power resulted in me feeling lost throughout the text. The book is a textbook-lite which fails miserably. He should have just went all in and made a probability management textbook.

The book's strongest point is its use of the internet. Rather than footnoting or appendixing particular points or thoughts, he utilizes interactive online pages on his website. The books true value comes from the connecting readers with several powerful probability management programs that are also free, such as solver and Analytica. I have downloaded solver since and find its potential uses rather numerous, though to be honest I was exposed to solver in a limited context during graduate school. Additionally, the book recommends reading of several books that I intend in the future to read, such as Peter Bernstein's `Capital Ideas' and Roger Lowenstein's `When Genius Failed.'

The book spent a considerable length of time explaining the difficulties that arise when managers use one single number, usually an average, but sometime can be a median, within their budget forecasts and decision making process. This is problematic, Savage argues, as, in the example of the drunk who on average is walking within the center of the road but spends most of his time walking towards incoming traffic or away from outgoing traffic, this does not really provide an accurate view of the true uncertain trend . Instead managers should use simulations that account directly for uncertainty using statistical principles, minus the esoteric language and terms, and chart and graphs that clearly display the range of possibilities of outcomes given a decision. I agree with this assessment.

Savage does not fail to include an important caveat. That probability and its universe of uncertainty and risk analyzing techniques should not preclude genuine understanding of risk, rather than as a tool to post-hoc protection of liability if things go sour. The most recent economic crisis and resulting recession is a derivative of not modern portfolio theory failing but rather the people who ignored the very basis of modern theory of accounting for risk and not as merely representing some abstract and uninterruptable number. Other great bits of knowledge include "The computer should be used to chronicle your thoughts, rather than form them" and "the best models are those you no longer need because they have changed the way you think."

The week used reading this book was well spent, and I feel I've walked away with an added decision making skill-set that I did not have before, nor would have gotten until perhaps years of first hand trial and error. Though I don't feel I have really learned anything new, what I currently know has been reframed, which I believe was how Savage desired anyone who read his book to leave. In this regard , Savage's writing style was a success. Again, there is just feeling that there could have been much clearer and concise treatment of the topic of probability management than Savage's attempt in this textbook-lite.

0 of 0 people found the following review helpful.
Easier way to learn statistics
By Artephius (.
I have been using basic statistics for over 30 years in my work as an Engineer. I enjoyed the author's attempt at explaining statistics in terms most people can understand.

The whole book is based upon not using averages, but instead run a Monte Carlo simulation using probabilities.

I know of one famous case where using averages caused a famous person to look like a fool. If you study the long-term annual returns of the US stock market, you will find an average return of about 10% with 1 sigma of about 20%. These annual returns fit a normal distribution pretty well (unlike daily returns which fit a logarithmic distribution better).

Very few people have been able to invest and beat the general 10% average return of the US stock market. Peter Lynch, of the Fidelity Magellan fund, was one of these few people. I think he beat the S&P 500 stock index average for about 15 years straight, before retiring.

In an article in the September 1995 issue of Worth magazine, Lynch was quoted as saying that retirees can easily annually withdraw 7% from their portfolio.

Apparently Lynch was not aware that a year ealier, 1994, William Bengen used one of the first personal computers to run a simulation to determine the maximum percentage of a portfolio that a retiree could annually withdraw. He found that 4% was the maximum, not the 7% that Lynch suggested.

Why did Lynch, a very smart investor, get is so wrong? Using average returns does not account for the variability in annual stock market returns. If the retiree experiences a few bad years of stock market returns during the first few years of retirement, there is not enough time for the portfolio to recover. Retirees that use a 7% withdrawal rate have about a 50% change of outliving their retirement portfolio.

Another famous person that focused on average returns and apparently did no meaningful simulations was Dick Fuld, CEO of Lehman Brothers when it went bankrupt in the Fall of 2008. I saw Fuld testify at Congressional hearings where he lamented that he did know what went wrong, and he was sorry he had hurt so many employees and investors.

While he was testifying, I did some mental math. Fuld had Lehman leveraged at a 33 to 1 ratio. This means a 3% drop in real estate prices causes the mortgage scheme to collapse. I was aware that in the 1990s, California real estate prices had dropped by at least 10%, so a 3% drop was very possible.

After Fuld finished testifying, a Professor testified next. He repeated the 33:1 leverage, then stated what I had been thinking just a few minutes before. He said a 3% drop in real estate prices would sink Lehman. The Professor speculated that the $600 million in salary Fuld had been paid the couple years before the collapse may have clouded his judgment.

All-in-all, this book will be enlightening to those people who are not aware of the importance of understanding the dramatic impact that variability of inputs can have on outputs.

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