How to Measure Anything, Finding the Value of “Intangibles in Business” Third Edition

I am traveling this week in India for the 13th CSI/IFPUG International Software Measurement & Analysis Conference: “Creating Value from Measurement”. Read more about it here. In the meantime, enjoy some classic content, and I’ll be back with new blog entries next week.

Final Notes of HTMA

Last week we completed the re-read of How to Measure Anything, Finding the Value of “Intangibles in Business” Third Edition.  Boiling the whole book into a single punchline yields the statement: “Anything that is important and is observable is measurable with some work.” If you need a caveat, you could consider adding that while anything is measurable, often we know enough that if we take the time estimate the value of the measure before we jump directly into measuring that we know enough and spend the effort on other variables. The ability to test the economic value of a measure (cost versus benefit) is perhaps the most important reminder I got during this re-read.

I spend a lot of my professional life helping people and organizations measure “things”. Sometimes measures and measurement plans either don’t spend the time to identify the decisions they are collecting data to make OR worse, only play lip service to the need that step. When organizations or a measurement analyst makes this mistake it is nearly impossible to determine the value an organization will derive from the measurement effort. Hubbard’s rational for his framework for Applied Information Economics calls out the fallacy of jumping directly to measuring something before you crisply define WHAT YOU ARE GOING TO DO WITH THE DATA. Hubbard reminds us that every measurement activity must be with my favorite question “why.” If you get nothing else from the book that is well worth the price.

For me there are couple of other major ideas that re-read brought home for me:

  1. I need to refresh my memory of Bayesian Statistics. It is easy to fall into the trap of using statistics that make assumptions of no prior knowledge or that everything lives below a normal curve, but that is myopic.  Do I need a good workbook, any suggestions?
  2. I need to do a few articles on Monte Carlo analysis for the blog.  I mentioned Monte Carlo in polite conversation the other day, only to receive a deer in the headlights look from my conversation partner. It is time to help educate more people and to refresh my knowledge at the same time. In the interim feel free to reach out to my friend Mauricio Aguiar and ask for his presentation on the topic.

A few days ago I was listening to a GAO Experts call for a discussion focused on developing alternative analyzes. During the call, a very senior participant suggested that there was no need to spend time quantifying qualitative data used in making billion dollar investments even when that data was important to the decision process. I found it difficult to believe that if the qualitative data was an important component in making the decision, that the effort to measure the qualitative aspects did not have value.  If I knew the participant I would send him a copy of How to Measure Anything, Finding the Value of “Intangibles in Business” Third Edition.  Maybe that is a bit passive-aggressive or represents a small arrogance on my part, but perhaps it would be balanced by a bit of enlightenment for him.


Past installments of the Re-read Saturday of  How To Measure Anything, Third Edition

Chapter 1: The Challenge of Intangibles

Chapter 2: An Intuitive Measurement Habit: Eratosthenes, Enrico, and Emily

Chapter 3: The Illusions of Intangibles: Why Immeasurables Aren’t

Chapter 4: Clarifying the Measurement Problem

Chapter 5: Calibrated Estimates: How Much Do You Know Now?

Chapter 6: Quantifying Risk Through Modeling

Chapter 7: Quantifying The Value of Information

Chapter 8 The Transition: From What to Measure to How to Measure

Chapter 9: Sampling Reality: How Observing Some Things Tells Us about All Things

Chapter 10: Bayes: Adding To What You Know Now

Chapter 11: Preferences and Attitudes: The Softer Side of Measurement

Chapter 12: The Ultimate Measurement Instrument: Human Judges

Chapter 13: New Measurement Instruments for Management

Chapter 14: A Universal Measurement Method: Applied Information Economics