Theory Tests Reality, Reality Tests Theory

“Experience by itself teaches nothing… Without theory, experience has no meaning. Without theory, one has no questions to ask. Hence, without theory, there is no learning.”

–W. Edwards Deming, The New Economics for Industry, Government, Education – 2nd Edition

The field of psychology, it seems, shares an issue with the field of operations management.

Wilson and Golonka, psychologists who blog on Notes From Two Scientific Psychologists lament about the lack of a unifying theory in their field in Theory, and Why Its Time Psychology Got One.

This is fairly heavy reading since it is likely from outside your field, but the core message is here (paragraph breaks added for readability):

Theory in Science
As I try to teach my students, the role of theory in science is to provide structure to your data. A good theory rules explanations in and out, and if it rules out the wrong explanation that will become clear over time as you pursue your theory guided research.

Good science means a) restricting your explanatory mechanisms to include things your theory allows, and b) keeping an eye on how well that’s working out for you, while c) allowing yourself to rest on your well supported theory to resist breaking the rules as long as you can.

As Deming points out in the quote at the top of this post, having a theory – a solid statement of what you believe is true is a prerequisite for learning to take place. Without that theory, events and information simply get filed away as “interesting.”

With a theory, each is compared against the prevailing thought and forces us to reflect on our understanding.

Sure, we run into confirmation bias (where we unconsciously exclude things that contradict our beliefs) and other logical flaws, but honestly – if scientific thinking were easy, we wouldn’t have to discuss it.

This is pertinent to us at a couple of levels.

At the macro-level we have the proliferation of “solutions” out there for management. We all talk about “flavors of the month” and “alphabet soup” as we see companies cycle through the various structures for “world class performance.”

Wilson and Golonka’s message, and our problem, is that in attempting to embrace everything, we embrace nothing.

Of course part of the problem is that book authors and management consultants are not, by and large, researchers who are interested in unifying the theory. Quite the contrary. They are interested in differentiation. This causes problems for people who see these various “solutions” as competing somehow. (In reality, they are mostly re-packaging of subsets of the same overall stuff.)

OK, we can’t do much about that in the larger sense, but within your company, you can.

I have yet to encounter a situation that is outside of my baseline theory of “what TPS is.”

As I said in a talk I gave last week, the only faith-based position I am asking you to embrace is that if your results seem incompatible with TPS, look at your understanding and deployment before rejecting it as unworkable.

While we wait for the MBA programs and influential institutions in our field to catch up, we can continue to identify in forums like this one which authors and researchers we think are largely congruent with one another and some kind of common baseline.

The other area where this message is applicable is in our daily approach to process design and problem solving.

Almost all of the “tools of lean” (and many techniques not especially associated with TPS) are really designed to develop and test a working theory of how the process should be working.

Takt time is a great example, though far from the only one.

I set up a process to operate at a certain speed. I say, in effect, “if the process has no unexpected problems, this is how long it should take.”

That is a theory.

I test the theory each and every time I run the process.

When (not if) something unexpected happens – when the team member can’t meet the standard work for some reason, then we have data that is not congruent with our baseline theory.

Now we can get into understanding why – what happened that we didn’t count on. Likely (in this example) something uncontrolled tripped him up. In experimental terms, we didn’t have the baseline conditions.

In our process terms, we now have a problem to solve – how do we keep that issue from coming up again, so that our team member can do the work in the time expected?

As we cycle through this thinking again and again, each iteration either cleans up some issue in the operation (which is continuous improvement), or we realize that we should have included this factor in the original plan (we modify the working theory).

Either way, our knowledge of the process is improved.

In reality, these two cases – micro and macro – point to the same thing. We need the macro (the theory of management) to reflect that we need to incorporate this thinking into the way we manage everything.