How To Measure Anything Second Edition: Finding The Value Of Intangibles In Business 9780470539392 下载 pdf 百度网盘 epub 免费 2025 电子版 mobi 在线

Now updated with new research and even more intuitive

explanations, a demystifying explanation of how managers can inform

themselves to make less risky, more profitable business decisions

This insightful and eloquent book will show you how to measure

those things in your own business that, until now, you may have

considered "immeasurable," including customer satisfaction,

organizational flexibility, technology risk, and technology ROI.

Adds even more intuitive explanations of powerful measurement

methods and shows how they can be applied to areas such as risk

management and customer satisfaction Continues to boldly assert

that any perception of "immeasurability" is based on certain

popular misconceptions about measurement and measurement methods

Shows the common reasoning for calling something immeasurable, and

sets out to correct those ideas Offers practical methods for

measuring a variety of "intangibles" Adds recent research,

especially in regards to methods that seem like measurement, but

are in fact a kind of "placebo effect" for management - and

explains how to tell effective methods from management mythology

Written by recognized expert Douglas Hubbard-creator of Applied

Information Economics-"How to Measure Anything, Second Edition"

illustrates how the author has used his approach across various

industries and how any problem, no matter how difficult, ill

defined, or uncertain can lend itself to measurement using proven

methods.

Preface xi Acknowledgments xv SECTION I MEASUREMENT: THE

SOLUTION EXISTS 1 CHAPTER 1 Intangibles and the Challenge 3 Yes, I

Mean Anything 5 The Proposal 6 CHAPTER 2 An Intuitive Measurement

Habit: Eratosthenes, Enrico, and Emily 9 How an Ancient Greek

Measured the Size of Earth 10 Estimating: Be Like Fermi 11

Experiments: Not Just for Adults 13 Notes on What to Learn from

Eratosthenes, Enrico, and Emily 18 CHAPTER 3 The Illusion of

Intangibles: Why Immeasurables Aren't 21 The Concept of Measurement

22 The Object of Measurement 26 The Methods of Measurement 28

Economic Objections to Measurement 35 The Broader Objection to the

Usefulness of "Statistics" 37 Ethical Objections to Measurement 39

Toward a Universal Approach to Measurement 41 SECTION II BEFORE YOU

MEASURE 45 CHAPTER 4 Clarifying the Measurement Problem 47 Getting

the Language Right: What "Uncertainty" and "Risk" Really Mean 49

Examples of Clarification: Lessons for Business from, of All

Places, Government 51 CHAPTER 5 Calibrated Estimates: How Much Do

You Know Now ? 57 Calibration Exercise 59 Further Improvements on

Calibration 64 Conceptual Obstacles to Calibration 65 The Effects

of Calibration 71 CHAPTER 6 Measuring Risk through Modeling 79 How

Not to Measure Risk 79 Real Risk Analysis: The Monte Carlo 81 An

Example of the Monte Carlo Method and Risk 82 Tools and Other

Resources for Monte Carlo Simulations 91 The Risk Paradox and the

Need for Better Risk Analysis 93 CHAPTER 7 Measuring the Value of

Information 99 The Chance of Being Wrong and the Cost of Being

Wrong: Expected Opportunity Loss 100 The Value of Information for

Ranges 103 The Imperfect World: The Value of Partial Uncertainty

Reduction 107 The Epiphany Equation: How the Value of Information

Changes Everything 110 Summarizing Uncertainty, Risk, and

Information Value: The First Measurements 114 SECTION III

MEASUREMENT METHODS 117 CHAPTER 8 The Transition: From What to

Measure to How to Measure 119 Tools of Observation: Introduction to

the Instrument of Measurement 120 Decomposition 124 Secondary

Research: Assuming You Weren't the First to Measure It 127 The

Basic Methods of Observation: If One Doesn't Work, Try the Next 128

Measure Just Enough 131 Consider the Error 132 Choose and Design

the Instrument 136 CHAPTER 9 Sampling Reality: How Observing Some

Things Tells Us about All Things 139 Building an Intuition for

Random Sampling: The Jelly Bean Example 141 A Little about Little

Samples: A Beer Brewer's Approach 142 Statistical Significance: A

Matter of Degree 145 When Outliers Matter Most 148 The Easiest

Sample Statistics Ever 150 A Biased Sample of Sampling Methods 153

Measure to the Threshold 162 Experiment 165 Seeing Relationships in

the Data: An Introduction to Regression Modeling 169 One Thing We

Haven't Discussed-and Why 174 CHAPTER 10 Bayes: Adding to What You

Know Now 177 Simple Bayesian Statistics 178 Using Your Natural

Bayesian Instinct 181 Heterogeneous Benchmarking: A "Brand Damage"

Application 187 Bayesian Inversion for Ranges: An Overview 190

Bayesian Inversion for Ranges: The Details 193 The Lessons of Bayes

196 SECTION IV BEYOND THE BASICS 201 CHAPTER 11 Preference and

Attitudes: The Softer Side of Measurement 203 Observing Opinions,

Values, and the Pursuit of Happiness 203 A Willingness to Pay:

Measuring Value via Trade-offs 207 Putting It All on the Line:

Quantifying Risk Tolerance 211 Quantifying Subjective Trade-offs:

Dealing with Multiple Conflicting Preferences 214 Keeping the Big

Picture in Mind: Profit Maximization versus Purely Subjective

Trade-offs 218 CHAPTER 12 The Ultimate Measurement Instrument:

Human Judges 221 Homo absurdus : The Weird Reasons behind Our

Decisions 222 Getting Organized: A Performance Evaluation Example

227 Surprisingly Simple Linear Models 228 How to Standardize Any

Evaluation: Rasch Models 230 Removing Human Inconsistency: The Lens

Model 234 Panacea or Placebo?: Questionable Methods of Measurement

238 Comparing the Methods 246 CHAPTER 13 New Measurement

Instruments for Management 251 The Twenty-First-Century Tracker:

Keeping Tabs with Technology 251 Measuring the World: The Internet

as an Instrument 254 Prediction Markets: A Dynamic Aggregation of

Opinions 257 CHAPTER 14 A Universal Measurement Method: Applied

Information Economics 265 Bringing the Pieces Together 266 Case:

The Value of the System that Monitors Your Drinking Water 270 Case:

Forecasting Fuel for the Marine Corps 275 Ideas for Getting

Started: A Few Final Examples 281 Summarizing the Philosophy 287

APPENDIX Calibration Tests (and Their Answers) 289 Index 299

DOUGLAS W. HUBBARD is the inventor of Applied Information

Economics (AIE), a measurement methodology that has been used in IT

portfolios, entertainment media, military logistics, R&D

portfolios, and many more areas where big decisions are based on

factors that seem difficult or impossible to measure. He is an

internationally recognized expert in metrics, decision analysis,

and risk management, and is a popular speaker at numerous

conferences. He has written articles for InformationWeek, CIO

Enterprise, Architecture Boston, Analytics and OR/MS Today and is

also the author of The Failure of Risk Management: Why It's Broken

and How to Fix It.

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量化的概念是“减少不确定性”，而且没有必要完全消除不确定性，这是本书的核心观点。

量化是在数量上减少不确定性的观测结果。这个定义和大众对量化的实际理解有巨大的差别。一个真正的量化过程不需要无艰精确。而且，如果没有报告误差，也没有采用抽样和实验等实证方法，就认为数字是完全精确的，根本不是真正的量化。

1948年，他发表了题为《通信的数学理论》（A Mathematical Theoryof Communication）

的论文，奠定了信息论的基础，而且我敢说，也奠定了量化的基础。现代人不会全都喜欢这篇文章，但他的贡献怎么强调都不为过，因为信息论从此成了所有现代信号处理理论的基础，而且也成了电子通信系统的工程基础。

香农将信号中不确定性的减少量作为信息的数学定义，在信息论中，他用信号代替了“熵”（shāg）。对香农来说，信息的接收者可以描述为具有一定程度不确定性的人。也就是说，接收者早就知道一些事，新的信息只是减少了接收者的一些而不是所有的不确定性。接收者以前的知识或不确定性，可以用来计算诸如在一个信号中传递的信息量的上限消除噪音所需要的最少信号量、数据可能达到的最大压缩程度等。

澄清链就是把某物想象为无形之物再到有形之物的一系列短的链接过程。

首先，如果X是我们关心的某种事物，那么根据定义，X必须可通过某种方法来感知。如果质量、风险、安全、公众形象等事物完全不可感知，那我们该用何种直接或间接的方法关注它们呢？我们关心某些未知数据，是因为我们觉得它和希望或不希望的结果有某种关联；

其次，如果这个事物可以感知，那必然能估计到某些数值。

如果你可以观测一个事物，就多少能得出一些东西。

最后，这一步或许是最容易的了：如果可以通过观测得到某些量，那它就一定是可量化的。

确定真正要量化什么，是几乎所有科学研究的起点。商业领域的管理者需要认识到，某些事物看起来完全无形无影，只是因为你还没给所谈论的事物下定义。搞清楚你的意思到底是什么，就已经完成了量化工作的一半。

进行很小的随机抽样量化

你可以从潜在顾客、员工等很小的样本里获得一些东西，尤其是存在较多不确定性的情况下。

不可能获得所有数据时，可对总体的一个样本进行量化

确定海洋里一种鱼的数量、雨林里一种植物的数量、新产品中不合格的数量，或者对你的信息系统进行未授权的访问但又没有被检测到的次数，都有更聪明和更简单的量化方法。

当存在很多其他变量甚至未知变量时，该如何量化

在宏观经济、竞争对手的失误或者新的定价策略等因素下，我们可以确定一种新的程序是不是销量提高的真正原因。

量化小概率事件的风险

火箭发射失败、另一场“911”、另一水新奥尔良的防洪堤溃坝、另一次重大的金融危机发生的概率，都可以通过观测和推理等有价值的方式来预防。

量化客体的偏好和价值取向

通过评估多少人真正付款，我们可以量化艺术、自由时间或减少生活中的风险所带来的价值。

书籍介绍

Now updated with new research and even more intuitive explanations, a demystifying explanation of how managers can inform themselves to make less risky, more profitable business decisions This insightful and eloquent book will show you how to measure those things in your own business that, until now, you may have considered "immeasurable," including customer satisfaction, organizational flexibility, technology risk, and technology ROI. Adds even more intuitive explanations of powerful measurement methods and shows how they can be applied to areas such as risk management and customer satisfaction Continues to boldly assert that any perception of "immeasurability" is based on certain popular misconceptions about measurement and measurement methods Shows the common reasoning for calling something immeasurable, and sets out to correct those ideas Offers practical methods for measuring a variety of "intangibles" Adds recent research, especially in regards to methods that seem like measurement, but are in fact a kind of "placebo effect" for management - and explains how to tell effective methods from management mythology Written by recognized expert Douglas Hubbard-creator of Applied Information Economics-"How to Measure Anything, Second Edition" illustrates how the author has used his approach across various industries and how any problem, no matter how difficult, ill defined, or uncertain can lend itself to measurement using proven methods.