Lean, Six Sigma, Kaizen–what do they have in common?

Today is a short post, an experiment to see if I can post from my mobile phone because my AT&T Uverse high-speed Internet service just collapsed into a black hole of unknown origin, and no technician is available today, so I can’t access the Internet with my desktop computer. Here goes…

In our Six Sigma Green Belt class, these three terms are used and the pre-class discussion is usually how they are related. The high-level view is that Six Sigma is for reducing variability, lean is for reducing waste, and that kaizen is for creating incremental but steady process improvement.

Instead of asking how they are different, let’s turn the discussion on its head: how are they the same, or more precisely what do they have in common?

1. They all involve processes. The process may involve materials, data, or humans (health care), so they have many application areas.

2. They all involve teamwork for implementation. I am probably prejudiced in this regard by having worked for so many years in Japan, but it is precisely the cultural genius of the Japanese for group dynamics that have led them to make so many strides in implementing kaizen and other quality improvement techniques.

3. They all involve quality principles which ultimately derive from the same sources: Deming, Juran, etc. Despite the Japanese cultural spin put on many concepts of kaizen and what is referred to as The Toyota Way, any discussion of the relative superiority of these methods to the “made in the USA” brand of Six Sigma is pointless, in my humble opinion.

Both these “brands” of quality improvement derive ultimately from the same source and the same principles, although they are shaped in their appearance by the culture that has elaborated upon them.

4. They all derive from bottom-up rather than top-down styles of management. Every worker needs to buy in to the process, but doing so empowers each worker to make a change through knowledge and creativity.

5. They all require statistical techniques for proof of their effectiveness. And that is why quality professionals must learn the language of statistics fluently.

So despite their differences, these areas require an overlapping body of knowledge and a similar problem-solving attitude.


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