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Presents advice on making profitable business decisions, describing how to use statistical methods to measure certain aspects of a business that are difficult to quantify, including such things as customer satisfaction, organizational flexibility, and technology risk.
Auteur
DOUGLAS W. HUBBARD is the inventor of Applied Information Economics (AIE), a measurement methodology that has earned him critical praise from The Gartner Group, Giga Information Group, and Forrester Research. He is an internationally recognized expert in the field of decision analysis and challenging measurements and is a popular speaker at numerous conferences. He has written articles for Information Week, CIO Enterprise, and DBMS Magazine. He is the author of The Failure of Risk Management: Why It's Broken and How to Fix It and Pulse: The New Science of Harnessing Internet Buzz to Track Threats and Opportunities.
Texte du rabat
Praise for the second edition of How to Measure Anything: Finding the Value of "Intangibles" in Business
"How to Measure Anything was already my favorite book (just ahead of Hubbard's second book, The Failure of Risk Management) and one I actively promote to my students and colleagues. But the Second Edition, improving on the already exquisite first edition, is an achievement of its own. As a physicist and economist, I applied these techniques in several fields for several years. For the first time, somebody wrote together all these concerns on one canvas that is at the same time accessible to a broad audience and applicable by specialists. This book is a must for students and experts in the field of analysis (in general) and decision-making."
--Dr. JOHAN BRAET, University of Antwerp, Faculty of Applied Economics, Risk Management and Innovation
"Doug Hubbard's book is a marvelous tutorial on how to define sound metrics to justify and manage complex programs. It is a must-read for anyone concerned about mitigating the risks involved with capital planning, investment decisions, and program management."
--JIM FLYZIK, former Government CIO, White House Technology Advisor and CIO magazine Hall of Fame Inductee
Praise for the first edition--The bestselling Business Math book two years in a row!
"I love this book. Douglas Hubbard helps us create a path to know the answer to almost any question, in business, in science, or in life . . . How to Measure Anything provides just the tools most of us need to measure anything better, to gain that insight, to make progress, and to succeed."
--PETER TIPPETT, PhD, MD, Chief Technology Officer, CyberTrust, and inventor of the first antivirus software
"Interestingly written and full of case studies and rich examples, Hubbard's book is a valuable resource for those who routinely make decisions involving uncertainty. This book is readable and quite entertaining, and even those who consider themselves averse to statistics may find it highly approachable."
--Strategic Finance
"This book is remarkable in its range of measurement applications and its clarity of style. A must-read for every professional who has ever exclaimed, 'Sure, that concept is important, but can we measure it?'"
--Dr. JACK STENNER, cofounder and CEO of MetaMetrics, Inc.
"Hubbard has made a career of finding ways to measure things that other folks thought were immeasurable. Quality? The value of telecommuting? The benefits of greater IT security? Public image? He says it can be done--and without breaking the bank . . . If you'd like to fare better in the project-approval wars, take a look at this book."
--ComputerWorld
Résumé
Shows managers how to inform themselves in order to make less risky, profitable business decisions. This book shows you how to measure those things in your own business, government agency or other organization that, until now, you may have considered "immeasurable," including customer satisfaction, organizational flexibility, and technology risk.
Contenu
Preface to the Third Edition xiii
Acknowledgments xix
About the Author xxi
Part I The Measurement Solution Exists 1
Chapter 1 The Challenge of Intangibles 3
The Alleged Intangibles 4
Yes, I Mean Anything 5
The Proposal: It's about Decisions 7
A "Power Tools" Approach to Measurement 10
A Guide to the Rest of the Book 11
Chapter 2 An Intuitive Measurement Habit: Eratosthenes, Enrico, and Emily 15
How an Ancient Greek Measured the Size of Earth 16
Estimating: Be Like Fermi 17
Experiments: Not Just for Adults 20
Notes on What to Learn from Eratosthenes, Enrico, and Emily 25
Notes 27
Chapter 3 The Illusion of Intangibles: Why Immeasurables Aren't 29
The Concept of Measurement 30
The Object of Measurement 37
The Methods of Measurement 40
Economic Objections to Measurement 48
The Broader Objection to the Usefulness of "Statistics" 52
Ethical Objections to Measurement 55
Reversing Old Assumptions 58
Notes 65
Part II Before You Measure 69
Chapter 4 Clarifying the Measurement Problem 71
Toward a Universal Approach to Measurement 73
The Unexpected Challenge of Defining a Decision 74
If You Understand It, You Can Model It 80
Getting the Language Right: What "Uncertainty" and "Risk" Really Mean 83
An Example of a Clarified Decision 84
Notes 90
Chapter 5 Calibrated Estimates: How Much Do You Know Now? 93
Calibration Exercise 95
Calibration Trick: Bet Money (or Even Just Pretend To) 101
Further Improvements on Calibration 104
Conceptual Obstacles to Calibration 106
The Effects of Calibration Training 111
Notes 118
Chapter 6 Quantifying Risk through Modeling 123
How Not to Quantify Risk 123
Real Risk Analysis: The Monte Carlo 125
An Example of the Monte Carlo Method and Risk 127
Tools and Other Resources for Monte Carlo Simulations 136
The Risk Paradox and the Need for Better Risk Analysis 140
Notes 143
Chapter 7 Quantifying the Value of Information 145
The Chance of Being Wrong and the Cost of Being Wrong: Expected Opportunity Loss 146
The Value of Information for Ranges 149
Beyond Yes/No: Decisions on a Continuum 156
The Imperfect World: The Value of Partial Uncertainty Reduction 159
The Epiphany Equation: How the Value of Information Changes Everything 166
Summarizing Uncertainty, Risk, and Information Value: The Pre-Measurements 171
Notes 172
Part III Measurement Methods 173
Chapter 8 The Transition: From What to Measure to How to Measure 175
Tools of Observation: Introduction to the Instrument of Measurement 177
Decomposition 180
Secondary Research: Assuming You Weren't the First to Measure It 184
The Basic Methods of Observation: If One Doesn't Work, Try the Next 186
Measure Just Enough 188
Consider the Error 189
Choose and Design the Instrument 194
Notes 196
Chapter 9 Sampling Reality: How Observing Some Things Tells Us about All Things 197
Building an Intuition for Random Sampling: The Jelly Bean Example 199
A Little about Little Samples: A Beer Brewer's Approach 200
Are Small Samples Really "Statistically Significant"? 204
When Outliers Matter Most 208
The Easiest Sample Statistics Ever 210
A Biased Sample of Sampling Methods 214
Experiment 226
Seeing Relationships in the Data: An Introduction to Regression Modeling 235
Notes 243
Chapter 10 Bayes: Adding to What You Know Now 247
The Basics and Bayes 248
Using Your Natural Bayesian Instinct 257
Heterogeneous Benchmarking: A "Brand Damage" Application 263
Bayesian Inversion for Ranges: An Overview 267
The Lessons of Bayes 276
Notes 282
Part IV Beyond the Basics 285
Chapter 11 Preference and Attitudes: The Softer Side of Measurement 287
Observing Opinions, Values, and the Pu…