Scientific Improvement Beyond The Experiment

“How do we deploy this improvement to other areas in the company?” is a very common question out there. A fair number of formal improvement structures include a final step of “standardize” and imply the improvement is laterally copied or deployed into other, similar, situations.

Yet this seems to fly in the face of the idea that the work groups are in the best position to improve their own processes.

I believe this becomes much less of a paradox if we understand a core concept of improvement: We are using the scientific method.

How I Think Science Works

In science, there is no central authority deciding which ideas are good and worth including into some kind of standard documentation. Rather, we have the concept of peer review and scientific consensus.

Someone makes what she believes is a discovery. She publishes not only the discovery itself, but also the theoretical base and the experimental method and evidence.

Other scientists attempt to replicate the results. Those attempts to replicate are often expanded or extended in order to understand more.

As pieces of the puzzle come together, others might have what seems to be an isolated piece of knowledge. But as other pieces come into place around them, perhaps they can see where their contributions and their expertise might fit in to add yet another piece or fill in a gap.

If the results cannot be replicated at all, the discovery is called into serious question.

Thus, science is a self-organized collaborative effort rather than a centrally managed process. All of this works because there is a free and open exchange among scientists.

It doesn’t work if everyone is working in isolation… even if they have the same information, because they cannot key in on the insights of others.

What we have is a continuous chatter of scientists who are “thinking out loud” others are hearing them, and ideas are kicked back and forth until there is a measure of stability.

This stability lasts until someone discovers something that doesn’t fit the model, and the cycle starts again.

How I Think Most Companies Try To Work

On the other hand, what a lot of people in the continuous improvement world seem to try to do is this:

Somebody has a good idea and “proves it out.”

That idea is published in the form of “Hey… this is better. Do it like this from now on.” image

We continue to see “standardization” as something that is static and audited into place. (That trick never works.)

What About yokoten. Doesn’t that mean “lateral deployment” or “standardize?”

According to my Japanese speaking friends (thanks Jon and Zane), well, yes, sort of.  When these Japanese jargon terms take on a meaning in our English-speaking vernacular, I like to go back to the source and really understand the intent.

In daily usage, yokoten has pretty much the same meaning [as it does in kaizen] just a bit more mundane scope…along the lines of sharing a lesson learned.

Yokogawa ni tenkai suru (literally: to transmit/develop/convey sideways) is the longer expression of which Yokoten is the abbreviation.

Yoko means “side; sideways; lateral. Ten is just the first half of “tenkai” to develop or transmit. Yokotenkai..

If you take a good look at the Toyota internal context, it is much more than just telling someone to follow the new standard. It is much more like science.

How the Scientific Approach Would Work

A work team has a great idea. They try it out experimentally. Now, rather than trying to enforce standardization, the organization publishes what has been learned: How the threshold of knowledge about the process, about a tricky quality problem, whatever, has been extended.

We used to know ‘x’, now we know x+y.

They also publish how that knowledge was gained. Here are the experiments we ran, the conditions, and what we learned at each step.

Another team can now take that baseline of knowledge and use it to (1) validate via experimentation if their conditions are similar. Rather than blindly applying a procedure, they are repeating the experiment to validate the original data and increase their own understanding.

And (2) to apply that knowledge as a higher platform from which to extend their own.

But Sometimes there is just a good idea.

I am not advocating running experiments to validate that “the wheel” is a workable concept. We know that.

Likewise, if an improvement is something like a clever mistake proofing device or jig (or something along those lines), of course you make more of them and distribute them.

On the other hand, there might be a process that the new mistake-proofing fixture won’t work for. But… if they applied the method used to create it, they might come up with something that works for them, or something that works better.

“That works but…” is a launching point to eliminate the next obstacle, and pass the information around again.

oh… and this is how rocket science is done.

Edit to add:

I believe Brian’s comment, and my response, are a valid extension of this post, so be sure to read the comments to get “the rest of the story.” (and add your own!)

3 thoughts on “Scientific Improvement Beyond The Experiment

  1. Great blog Mark. I’ve seen different organizations make different types of attempts at “best practice sharing”, which in the context of your blog would be their attempts to create the open forum to transfer ideas and let others attempt to replicate. The different methods I’ve seen have had luke warm success at best.

    You could make a case that a kaizen event report out is another method in trying to share information. Those typically do a decent job of showing the different activities the team was engaged in and the new results those activities produced. But again, I haven’t seen this really drive the type of sharing that leads other groups to try and replicate.

    Where I have seen the most success in spreading improvements into other areas has been when there is movement of personnel. The people that were a part of the improvement now take what they learned from that and apply it to their new work area.

    My organization is currently embarking on an effort to require site lean leaders to submit 4 blocker examples of the improvements they have made and upload them to a central database that could be viewed by anyone. The intent is to have a trove of improvement examples that people could browse and learn from. I’m nervous that the only thing this will drive is paperwork.

    I’m curious on you and your readers thoughts on how to create systems of knowledge sharing that will allow improvement to spread.

    1. Brian –
      Realistically it is a tough one.
      I have even heard from Toyota people that it is tough for them unless an idea is truly revolutionary like the Toyota raku-raku seat (https://www.youtube.com/watch?v=wtWqcbuXFC4) which, I am told, was a shop floor idea. But it clearly had SO much impact that it was quickly spread and adopted across the company, and has made its way into other companies.

      The story told in Jeff Liker’s book “The Toyota Way to Lean Leadership” is a case where one area benchmarks another area with similar issues that has solved a problem. But rather than copying the solution, the benchmarking area takes the idea as a foundation and builds something better from it. That, in turn, is transferred back to the originating area and is improved again. This cycle continues as each area builds upon the other. BUt… (and this is critical) even THAT only happens because the area manager is being challenged and pushed by his manager / coach.

      You can see that this is far more than a reference database. Rather, this is “go and see” to truly understand not only the solution, but the problem behind it. (“Solutions” exist only in a symbiotic relationship with “problems.” If there is no “problem” then a “solution” is just an idea which may, or may not, be useful.)

      In science, that would (in my mind) be equivalent to visiting the discovering researcher, and having him teach you what he knows, then going back to your own lab and building on it. This, in fact, was the foundation of the discoveries in the early 20th century that led to our understanding of quantum mechanics. Individual researchers would apply to become students of prominent figures, learn from them, then push the edges of the discoveries to another level. Again… learning at the gemba.

      The question for your 4-blocker is this:
      It isn’t about the work in creating them. The question is “Who do you expect to look at them?”
      “What process do you expect the reader / researcher to follow to absorb what was learned?”

      Many academic works start with a “literature search” – a survey of the current literature to establish a baseline, before documenting the case to extend it. This, in turn, is driven by a coach (the thesis adviser) who is working with the person doing the research.

      Who is the coach in your case?
      And does that coach *expect* the improver to, at some point, survey the state of understanding in the company as part of their “grasp the current condition” step?

      That might make sense – in your understanding of the “current condition” I might also want to hear you understanding of the current condition of experience within the company on other related issues.

      But without that driving force (a coach), it is unlikely anyone is going to search your database except in the level that some of us get lost following hyperlinks in Wikipedia. It’s interesting, but hard to make relevant. And relevance is your challenge here.

      What is the mechanism you are putting into place to drive the process of using this information? That is the question.

  2. Hi Mark

    Toyota for a fact does roll most solutions to the rest of their plants outright, but they do share what was done and allow those other plants to use it directly as is, or what happens far more often is that the idea gets improved on so it works better for the next plant trying something similar. The honest reality is no two of their plants are identical, nor are any two of their lines.

    They constantly look to use what they currently know, and apply and improve it each time it gets attempted else where. And there are times when something worked in one plant and failed in another, the reality is that all factors are never equal.

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