Want to Learn Kaizen? Forget About It

Kaizen starts in the brain, so understanding the working of the brain is essential to doing kaizen better. A June 4, 2007 New Scientist article titled Forgetfulness is a tool of the brain suggests that if we want to learn kaizen, we also have to forget.
According to a new study, the brain only chooses to remember memories it thinks are most relevant, and actively suppresses those that are similar but less used, helping to lessen the cognitive load and prevent confusion.
Stanford University researchers Brice Kuhl and colleagues used functional magnetic resonance imaging (fMRI) to measure the brain activity of a group of healthy adults while they performed a simple memory test. The experimenters found:
“Whenever you’re engaging in remembering, the brain adapts. It’s constantly re-weighting memories,” says Kuhl. “In this simple test, we see it reverse memory to weaken competing memories. This is something that probably happens a lot in the real world.”

This is like a 5S of the mind. Sort and straighten. What new memories do I keep, and what do I throw out? The brain is constantly prioritizing and making room for new things. Our brain is a pretty fantastic instrument. The fact that our brains are constantly doing 5S is a good argument for us to do the same in our physical space.
The overall idea of forgetting something to learning something new is very much in the spirit of kaizen. To improve, we need to let go of old ways so that we can change them and make better ways.
On a related note, on June 4, 2007 the MIT News published an articled titled Brain uses both neural ‘teacher’ and ‘tinkerer’ in learning which has interesting parallels to standard work, variation, kaizen and learning through experimentation.
The investigative team of Emilio Bizzi, Uri Rokni, and Sebastian Seung at the Howard Hughes Medical Institute investigator found:

While most people need peace and quiet to cram for a test, the brain itself may need noise to learn, a recent MIT study suggests. In experiments with monkeys, the researchers found that neural activities in the brain gradually change, even when nothing new is being learned. Challenging the monkeys to adjust their task triggered systematic changes in their neural activities on top of this background “noise.”
The brain needs “noise” to learn. Variation and error correction is an essential part of the neourscience of learning, in this new theory

“What surprised us most was that the neural representation of movement seems to change even when behavior doesn’t seem to change at all,” said Sebastian Seung, professor of physics and computational neuroscience and a Howard Hughes Medical Institute investigator. “This was a surprising degree of instability in the brain’s representation of the world.”
Uri Rokni explained:

“Our theory holds that the learning brain has the equivalent of a ‘teacher’ and a ‘tinkerer’–a learning signal and noise in the learning process, respectively.
There is a sensei (teacher) in your brain, guiding your experiments (tinkerer).

“In producing a specific piece of text, the tinkerer just randomly changes the words, while the teacher continually corrects the text to make it have the right meaning. The teacher only cares about the meaning and not the precise wording. When the teacher and tinkerer work together, the text keeps changing but the meaning remains the same. For example, the tinkerer may change the sentence ‘John is married’ to ‘John is single,’ and the teacher may correct it to ‘John is not single.’
The tinkerer in the brain tries new things, while the sensei in the brain guides the experiment according to certain rules and principles, in the example above so that the novel sentence retains the same meaning or value.

“In the same way, learning in the brain has two components–error-correction and noise–so that even though the neural representation keeps changing, the behavior remains fixed. We think the tinkerer, that is the noise, is not merely a nuisance to the teacher but is actually helping the teacher explore new possibilities it wouldn’t have considered otherwise.”
The parallel in the Lean world may be that the set behavior is Standard Work, the noise is the naturally occurring variation in any system, and the actions to explore these new options is kaizen.

According to Rokni, the concepts of redundant networks and “noisy learning” have important implications for neurobiology. “I don’t think this concept of redundancy–that the brain can say the same thing in different ways–has really been fully appreciated until now,” he said.
This may also have parallels to this redundancy in Toyota’s design approach. The so-called set-based concurrent engineering where multiple design options are explored until the very end, increasing the “noise” in the overall design work flow, but ending up with a better overall result and more learning. This is in contrast to narrowing down the design options early and struggling to make it work.
If this this new model of learning and the brain is right, it confirms Toyota’s claim that their management system is powered by their greatest asset: people and their brains.

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