How to Measure Anything: Finding the Value of Intangibles in Business

"How to Measure Anything: Finding the Value of Intangibles in Business" is a valuable resource for anyone looking to improve their decision-making and problem-solving skills. The book provides a framework for thinking about and measuring intangible assets, such as knowledge, expertise, and customer satisfaction.One of the key takeaways from the book is the importance of accurately measuring intangible assets in order to make informed business decisions. The author, Douglas W. Hubbard, presents a range of techniques for doing so, including the use of surrogate measures, decision trees, and the application of probability theory.One of the strengths of the book is its practicality. The author provides numerous examples and case studies to illustrate the concepts he introduces, making it easy to understand and apply the ideas to real-world situations.Overall, "How to Measure Anything" is a well-written and thought-provoking book that is sure to be of interest to anyone looking to improve their ability to measure and value intangible assets.

After reading the book, I organized a seminar for four managers involved in decision support at the company. After each chapter participants were tasked to apply what we learned to our business. Already by the 5th chapter we found important key performance indicators that we could measure much faster with minimal loss of accuracy, and, more importantly, reduce uncertainty of "gut" decisions.

I was introduced to Mr. Hubbard's writing through a recommendation from a friend on another book of his,  The Failure of Risk Management: Why It's Broken and How to Fix It . After seeing his critical breakdown of a problem that many in business face, I was eager to see how he tackles another major issue with the measurement of intangibles. The attempt to put a number on something not easily quantified has been an interest of mine, particularly on the end of business valuation. I was intrigued by the likes of Warren Buffet who seemingly through infinite wisdom find the magic number a company was worth and make investment decisions from it. After reading this book from Hubbard, things can be seen in a whole new light. The opening of How to Measure Anything focuses on trying to both dispel of statistical myths that surround the topic, as well as try to specify the language and concepts that we need to approach measurement of things not clearly quantified. A major idea is focusing on uncertainty and how we can reduce it in order to make better decisions. Combining this with relatively sophisticated statistical tools such as Monte Carlo modelling, Hubbard outlines an approach that even those who avoided stats class in college can follow. The middle and back end of the book contain enough meat for the quantitatively inclined to dig into, but also is approachable enough for those with less experience. As Hubbard mentions it is about learning when and how to use the tool, not necessarily how to tool works; you don't need to build a car from the ground up in order to drive to work.

Yes, this is a difficult one to sit down and read straight through. And yes, it might be common sense for some. However I would think that those folks especially would appreciate the way that the book breaks down data-based decision making for people who aren't really sure where to start. I really enjoyed this book and recommend it to anyone I can, but I would recommend using it more as a textbook or reference. Read the first part, but visit his website and perform the exercises as you learn. Then review the rest of the book as needed, ans refer back to it when you have a tricky problem that you aren't sure how to start on. Even if this seems like common sense there is something new for everyone to learn.

The book is good and has many good ideas and examples. But it is language is a little difficult for non-English speakers as it uses many non-technical terms. It also takes too much to discuss its ideas making it very time consuming to finish reading each single page.

"Calibration" for 90% likelihood of a solid approximation came off as a bit of a placebo / weird selling point. Language like this makes the book sounds less empirical. The other star off was for redundancy - I wish more of the book was anecdotes in optional boxes that already exist in the format of the book.I believe what the book is suggesting - that anything can be measured - and in most of the methodologies suggested, but this could be accomplished with a link to online case studies and 50% less book.

How to measure anything is a great book and I’m happy that I’ve read it. I was surprised though that the main points that it gave me reached far beyond just measuring things:If we are providing a service “which values cannot easily be measured” - maybe we should think again about what we are trying to achieve. Some kind of observable consequence must be present if they matter at all? Right?Measuring things just because they are easy to measure is pretty useless. What are the decisions you want to support? Will this measurement help this?One thought experiment to find what is important to measure is “if we didn’t do this - how would you notice the difference?”

An important aspect of making decisions is how we assign values to choices. Hubbard does a good job of showing the process of valuation and collecting the data.An interesting aspect of his work discusses estimation. Since we may not always have access to real data we should be able to estimate. Some people are very good estimators -- they practice. Hubbard has some example exercises showing how you can practice. This set of exercises alone is worth the price.The book is also an easy read.I do use it as a reference.

Great Resource

É um curso prático e interessante de estatística aplicada, para relembrar e incrementar o que a gente sabia de estatística. Requer leitura atenta.

Una gran lectura que te ayuda a transformar tus palabras o ideas generales a puntos muy concretos que te pueden llevar a tener una medición correcta de objetivos.Es un libro que te enseña que en realidad nada es subjetivo, solo tienes que aire fer a hacer las preguntas correctas.

Very insightful and thought provoking read. Enough maths to be sound but not so much as to obfuscate the message. Thanks for your time in authoring this Doug.

This book goes into detail about how to better approach decisions. If I had read the book 20 years ago, I would have been able to evaluate decisions better. I like that this book exposed me to different methodologies.