How to Measure Anything: Finding the Value of Intangibles in BusinessNow updated with new measurement methods and new examples, How to Measure Anything shows managers how to inform themselves in order 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, government agency or other organization that, until now, you may have considered "immeasurable," including customer satisfaction, organizational flexibility, technology risk, and technology ROI.
Written by recognized expert Douglas Hubbard—creator of Applied Information Economics—How to Measure Anything, Third 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. |
Contents
CHAPTER1 The Challenge of Intangibles | 3 |
Eratosthenes | 15 |
3 | 55 |
4 | 71 |
5 | 93 |
CHAPTER6 Quantifying Risk through Modeling | 123 |
7 | 145 |
From What to Measure | 175 |
15 | 293 |
Quantifying Risk Tolerance | 296 |
16 | 328 |
New Measurement Instruments for Management | 339 |
29 | 354 |
Applied | 357 |
Forecasting Fuel for the Marine Corps | 367 |
Measuring the Value of ACORD Standards | 373 |
Other editions - View all
How to Measure Anything: Finding the Value of Intangibles in Business Douglas W. Hubbard Limited preview - 2014 |
Common terms and phrases
actually additional analysis answer apply approach asked assess average Bayesian benefits better bound calculation calibrated called chance Chapter claim compute consider correlation cost customers decision defined detail determine discussed distribution economic effect entire error estimate example Exhibit experts fact further give given human identify important improvement increase initial investment least less look loss lower managers mean measurement mentioned methods million objective observations outcomes particular performance person population possible prediction prefer prior probability problem quantity questions random range reason reduce risk sample scale scores shows significance simple specific standard statistics step subjective survey things threshold tion tool true uncertainty units usually variables weighted