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October 13, 2018
I wrote this book to correct a costly myth that permeates many organizations today: that certain things can’t be measured. This widely held belief is a significant drain on the economy, public welfare, the environment, and even national security.
In some cases, when someone called something “immeasurable,” I would remember a specific example where it was actually measured.
Not only was every alleged immeasurable turning out not to be so, the most intractable “intangibles” were often being measured by surprisingly simple methods.
Whereas scientific management originally focused on optimizing labor processes, we now need to optimize measurements for management decisions. Formal methods for measuring those things management usually ignores have barely reached the level of alchemy. We need to move from alchemy to the equivalent of chemistry and physics.
Section One makes the case that everything is measurable and offers some examples that should inspire readers to attempt measurements even when it seems impossible.
Section Two begins to get into more specific substance about how to measure things—specifically uncertainty, risk, and the value of information.
Section Three deals with how to reduce uncertainty by various methods of observation, including random sampling and controlled experiments.
Section Four is an eclectic collection of interesting measurement solutions and case examples. It discusses methods for measuring such things as preferences, values, flexibility, and quality.
Write down one or more measurement challenges you have in home life or work, then read this book with the specific objective of finding a way to measure them.
When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely in your thoughts advanced to the state of science. —Lord Kelvin, British physicist and member of the House of Lords, 1824-1907
No matter how “fuzzy” the measurement is, it’s still a measurement if it tells you more than you knew before.
In some cases, the committees were categorically rejecting any investment where the benefits were primarily “soft” ones.
some of the most important strategic proposals were being overlooked in favor of minor cost-savings ideas simply because everyone knew how to measure some things and didn’t know how to measure others.
Equally disturbing, many major investments were approved with no basis for measuring whether they ever worked at all.
Some of the methods are so much simpler than what is taught in the typical introductory statistics courses that we might be able to overcome many phobias about the use of quantitative measurement methods.
The focus here is on measurements that are relevant—even critical—to major organizational decisions and yet don’t seem to lend themselves to an obvious and practical measurement solution.
three propositions
Management cares about measurements because measurements inform uncertain decisions. 2. For any decision or set of decisions, there are a large combination of things to measure and ways to measure them—but perfect certainty is rarely a realistic option. 3. Therefore, management needs a method to analyze options for reducing uncertainty about decisions.
Measurement is about supporting decisions, and there are even several decisions to make within measurements themselves.
three broad issues: why nothing is really immeasurable, how to set up and define any measurement problem, and how to use powerful and practical measurement methods to resolve the problem.
We have to answer the question “What is the real problem/decision/dilemma?”
“What about that problem really needs to be measured and by how much (to what degree of accuracy/precision)?”
measurements that are useful are often much simpler than people first suspect.
measurement “heroes”—individuals who saw measurement solutions intuitively and often solved difficult problems with surprisingly simple methods.
In ancient Greece, a man estimated the circumference of Earth by looking at the different lengths of shadows in different cities at noon and by applying some simple geometry. • A Nobel Prize-winning physicist taught his students how to estimate by estimating the number of piano tuners in Chicago. • A nine-year-old girl set up an experiment that debunked the growing medical practice of “therapeutic touch” and, two years later, became the youngest person ever to be published in the Journal of the American Medical Association (JAMA).
Eratosthenes (ca. 276-194 B.C.) made the first recorded measurement of the circumference of Earth.
typical results put his answer within 3% of the actual value.1
Eratosthenes made what might seem an impossible measurement by making a clever calculation on some simple observations.
He wrung more information out of the few facts he could confirm instead of assuming the hard way was the only way.
The value of quick estimates
asking his students to estimate the number of piano tuners in Chicago.
This approach to solving a Fermi question is known as a Fermi decomposition
It is really more of an assessment of what you already know about a problem in such a way that it can get you in the ballpark.
Instead of being overwhelmed by the apparent uncertainty in such a problem, start to ask what things about it you do know.
even touchy-feely-sounding things like “employee empowerment,” “creativity,” or “strategic alignment” must have observable consequences if they matter at all.
Massimo Curatella liked this
If quality and innovation really did get better, shouldn’t someone at least be able to tell that there is any difference?
Executives often say, “We can’t even begin to guess at something like that.” They dwell ad infinitum on the overwhelming uncertainties. Instead of making any attempt at measurement, they prefer to be stunned into inactivity by the apparent difficulty in dealing with these uncertainties. Fermi might say, “Yes, there are a lot of things you don’t know, but what do you know?”
The concept of measurement as “uncertainty reduction” and not necessarily the elimination of uncertainty is a central theme of this book.
1. Concept of measurement. The definition of measurement itself is widely misunderstood. If one understands what “measurement” actually means, a lot more things become measurable. 2. Object of measurement. The thing being measured is not well defined. Sloppy and ambiguous language gets in the way of measurement. 3. Methods of measurement. Many procedures of empirical observation are not well known. If people were familiar with some of these basic methods, it would become apparent that many things thought to be immeasurable are not only measurable but may already have been measured.
In addition to these reasons why something can’t be measured, there are also three common reasons why something “shouldn’t” be measured. The reasons often given for why something “shouldn’t” be measured are: 1. The economic objection to measurement (i.e., any measurement would be too expensive) 2. The general objection to the usefulness and meaningfulness of statistics (i.e., “You can prove anything with statistics.”) 3. The ethical objection (i.e., we shouldn’t measure it because it would be immoral to measure it)
As far as the propositions of mathematics refer to reality, they are not certain; and as far as they are certain, they do not refer to reality. —Albert Einstein
Although this may seem a paradox, all exact science is based on the idea of approximation. If a man tells you he knows a thing exactly, then you can be safe in inferring that you are speaking to an inexact man. —Bertrand Russell (1873-1970), British mathematician and philosopher
Measurement: A quantitatively expressed reduction of uncertainty based on one or more observations.
A measurement doesn’t have to be about a quantity in the way that we normally think of it.
In 1946, the psychologist Stanley Smith Stevens wrote an article called “On the Theory of Scales and Measurement.”2 In it he describes different scales of measurement, including “nominal” and “ordinal.” Nominal measurements are simply “set membership” statements, such as whether a fetus is male or female, or whether you have a particular medical condition. In nominal scales, there is no implicit order or sense of relative size. A thing is simply in one of the possible sets. Ordinal scales, however, allow us to say one value is “more” than another, but not by how much. Examples of this are the
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In measurement theory, a measurement is a type of “mapping” between the thing being measured and numbers.
If someone asks how to measure “strategic alignment” or “flexibility” or “customer satisfaction,” I simply ask: “What do you mean, exactly?”
Massimo Curatella liked this
Once managers figure out what they mean and why it matters, the issue in question starts to look a lot more measurable.
The clarification chain is just a short series of connections that should bring us from thinking of something as an intangible to thinking of it as a tangible.
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Second, if this thing is detectable, then it must be detectable in some amount.
