Summary for quick reference. Relevant in the context of decision-making and uncertainty.
When you prioritize easily measured data points over more elusive information when making decisions, you might fall victim to the McNamara fallacy.
The first step is to measure whatever can be easily measured. This is OK as far as it goes. The second step is to disregard that which can’t be easily measured or to give it an arbitrary quantitative value. This is artificial and misleading. The third step is to presume that what can’t be measured easily really isn’t important. This is blindness. The fourth step is to say that what can’t be easily measured really doesn’t exist. This is suicide.
— Daniel Yankelovich, “Corporate Priorities: A continuing study of the new demands on business” (1972).1