Many people make two mistakes regarding Quality Assurance. The first mistake is viewing quality assurance as an event that occurs post-production. It isn’t—Quality Assurance is ongoing during the production of a product or service, and preferably is done by the operator.

The second mistake is to rely solely on numbers—data, benchmarks, or some other metric to tell us whether we produce products and services that are fit with the needs of our customer. That is the definition of Quality, in case you missed our earlier posts.

Don’t get me wrong. I am a fan of using data, it’s just that data alone is useless. Data must be layered with intuition to become effective, particularly when our task is to ensure Quality during production.

Numbers can only tell us that this product or service either meets the quality specifications or fails to meet the quality specifications. They can’t tell us why the failure occurred, or even why we were successful! We tend to think of numbers as the cold, hard truth—I serve on a nonprofit board of directors with a colleague who tells me that numbers never lie. That simply isn’t true—numbers can lie, and not just because a human used them to deceive. Perhaps it isn’t quite a lie; numbers don’t always tell us the whole truth, which for me is the same as telling a lie. This is the difference between philosophical and scientific objectivity.

Philosophical objectivity is concerned with the truth, while scientific objectivity is concerned with knowledge with the judgments and biases of the people who developed the knowledge removed.

Forgive me that digression.

Because quantification with numbers cannot tell us why things happen, we must balance the information provided by the numbers with intuition. The numbers direct our attention to specific areas and our intuition, the way we turn our experience into quick action, is used to make decisions.

Quantification and intuition, when combined, perform several useful functions related to Quality Assurance.

First, they help us make sense of the situation—what are the underlying causes of the success or failure, what forces are at work in this context, what motivations are driving the behaviors associated with success or failure?

Second, they can help us resolve conflicts created by conflicting ideas about the success or failure. A high rate of success does not mean you have a well-designed and executed process—perhaps the reporting is gamed, or the operator performs an undocumented work-around for a faulty process because she is concerned about the quality of her work.

Third, they work together to reduce perverse incentives—the things that drive bad behavior to produce “good results”.

Fourth, they help us make decisions about which things should be measured. One challenging question my intuition forces me to ask is “Where did that number come from?” Often I discover the source of the number is dubious—and I’ve had many paradigms shattered by that discovery, forcing me to continually revise papers in the pursuit of truth.

Fifth, the numbers used in conjunction with intuition help us build better mental models of how things really work to produce goods and services that are fit for the customer’s Job To Be Done.

This is the role intuition plays in Quality Assurance.

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