We had some difficult times with my manager to set up my goals for this year. If you spent more than half a year in any “serious” corporation, probably you have already heard about what goals should look like. They should be all
- Specific,
- Measurable,
- Achievable,
- Relevant,
- Time-bound.
Our biggest concerns are usually about finding goals that are specific and measurable enough. Around that time, I ran into a book recommendation on a similar topic: “How to Measure Anything: Finding the Value of Intangibles in Business”.
I found the book interesting and high quality, but if you are looking for an answer to set up good and measurable goals, this is not your book. On the other hand, if you have to make decisions for projects where you don’t have enough information available, this book will provide you even with the mathematical details of how to get there.
I didn’t spend much time on the mathematical explanations, but I still think this value has many interesting stories and important messages. Let me share a couple here.
The three reasons for measurements
If you want to learn about measurement, if you want to invest time and effort into learning to do it better, we should rather understand why we could or even should care about measurements.
The author shares 3 valid reasons:
- Key decisions are based on information. Information comes from data and data comes from measurement. The better decisions you want to make or support, the better you have to measure.
- You can make money out of measuring well. As good data, after all, good measurement has a key role in decision-making, it has its own market value.
- Maybe you just find it entertaining or satisfying for your curiosity.
Why immeasurables aren’t…
According to the author’s experience, people find things immeasurable mostly due to three reasons:
1) They don’t understand what measurement means. Often we think about measurement as quantifying something or computing the exact value of something. But that’s not what measurement really is. By measurement, we mean observations that quantitatively reduce uncertainty.
Depending on the type of the problem, a mere reduction of the uncertainty can be a realistic and very valuable goal, but sometimes people ignore this as something not valuable. It has to be defined what end-goal one expects from a measurement.
2) The object of measurement is not clearly defined. Business managers need to realize that some things seem intangible only because they just haven’t defined what they are talking about. When vague terms are used such as “strategic alignment”, “flexibility” or “customer satisfaction”, you have to ask what exactly is meant by those.
By clearly defining that by customer satisfaction we mean the number of returning customers, we are already in a much better chance to make our measurements.
3) People often consider things immeasurable simply because they have no idea how to measure those things. In most cases, they don’t have to reinvent the wheel, most probably they wouldn’t be the first people in history to measure those. They should rather ask around and research a bit.
The biggest lie you often hear…
The biggest hypocrisy that you can hear from anyone is that life is priceless. Why is it a lie? Just examine your own decisions. How much do you invest in leading a healthier life? What are your behaviours that go strongly against being alive as long as possible?
It would be too easy to think about political decisions, policies, public advertisements when we think about why this statement is hypocrisy, but that would be clearly just fingerpointing.
Have you done your fair sport today and limited the intake of unhealthy food? According to the results of measurement, we don’t have to go further to understand the lie behind “life is priceless”…
Weird reasons behind decisions
Sometimes certain decisions seem simply absurd. While absurd will stay absurd, it’s often the result of cognitive biases. Let me share two interesting examples:
Thinking about one number affects all the coming estimations, even on completely unrelated issues. This is something called anchoring. It turned out that even just giving your social security number can affect your subsequent answer to a quantitative question.
If you want to ask a group of people about something you want to measure, it’s better if you ask them separately. If you ask them in front of each other, there is a fair chance that the first answer will have an effect on all the rest. That’s the bandwagon effect.
Trade-offs everywhere
And here is the last thing I’d like to share. A question from the book.
“Is a programmer who gets 99% of assignments done on time and 95% error-free better than one who gets only 92% done on time but with a 99% error-free rate?”
The author doesn’t give you an answer, nor will I. The idea behind this question is to show that sometimes decision-makers have to deal with multiple conflicting preferences.
Often the problem is not about measurements, but documenting subjective trade-offs. For example, plotting all the data to utility curves help to find the good trade-offs.
Conclusion
Even if you are not someone specified to measure things, this book is engaging and will give you many interesting ideas to ponder. I think it’s good to read it cover to cover, but I’d suggest going a bit faster through some parts which are more mathematically detailed. Unless, you are interested in, or need that math.
Otherwise, you’ll find most of this book entertaining. You’ll learn about interesting measurement problems, methods and outcomes starting from ancient Greece to our days.
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