Author Measures Up to the Immeasurable
When decisions get made before all of the best available information is gathered, the chance for errors increases. Bad decisions lead to resources getting wasted, good ideas getting pushed aside and, sometimes, very bad things happening.
On the other hand, when the right things are measured, smarter decisions get made.
Many people believe that there are some things that just cannot be measured, but author Douglas Hubbard says this is a myth. In How to Measure Anything, he writes that this myth "is a significant drain on the economy, public welfare, the environment and even national security." Classifying some things as "intangibles" can prevent them from being measured, Hubbard explains, and when we fail to calculate the numbers behind such things as the value of quality, employee morale and the economic impact of environmental conditions, we are leaving key information off the table when we make decisions.
To help people make better decisions, Hubbard published the first edition of How to Measure Anything in 2007. The book was so popular that it was consistently the single bestseller in Amazon’s "Math for Business" category for three years. Over those years, Hubbard wrote and published his next book, The Failure of Risk Management: Why It’s Broken and How to Fix It. Throughout all of his work, Hubbard declares that many of the most widely used risk management and risk measurement tools do not stand up to scientific scrutiny. In his new edition of How to Measure Anything, Hubbard expands on the book’s original text with the new evidence he has compiled since 2007.
Applied Information Economics
Hubbard is an internationally recognized expert in metrics, decision analysis and risk management. In 1994, he invented the Applied Information Economics (AIE) measurement methodology, which has been used around the world to measure some of the hardest things to measure, such as military logistics, entertainment media, information technology portfolios and research & development portfolios. In How to Measure Anything, Hubbard not only describes how the AIE has been used by the U.S. Marine Corps, the Environmental Protection Agency and many other organizations, but he also shows how anyone can learn to measure what once seemed immeasurable.
Hubbard starts his book by explaining that everything is measurable, even the intangibles that, at first glance, seem to be completely impossible to measure. Going beyond theory, he describes a number of case studies from a variety of industries. One of the most important lessons that he offers throughout his book is described in the details of these case studies: Valuable measurements can be made in ways that can be justified economically. In other words, organizations can put numbers on things such as "reduced strategic risk" and "premium brand positioning" without breaking the bank.
Reducing uncertainty through observation is the next topic Hubbard explores. Many valuable tips on random sampling and controlled experiments offer ways to get better results through more calculated observations. Hubbard points out that treating each observation as "updating and marginally reducing a previous state of uncertainty" helps to improve measurements.
Hubbard rounds out his book with a fascinating collection of real-life stories that provide deep insight into the measurement solutions that worked for a variety of organizations. He also shows readers how the Internet can be used to create accurate measurements of things such as preferences, values, flexibility and quality. A list of strategies for avoiding response bias offers some valuable tips for anyone using surveys to find the measurements they need.
How to Measure Anything presents dozens of tools and methods for measuring the things that organizations once believed were immeasurable, such as management effectiveness, the value of information and public image. Although measuring these important aspects of an organization has often been avoided, Hubbard shows how anyone can improve decisions by generating a few more numbers.