Fellow Statistical Problem Solvers;
I wrote the following after reading the article posted on Linkedin called "Planning the Abandonment of Six Sigma" by Dr. Gregory Watson. Dr. Watson posits that the many current models used in problem solving each have unique reasons why they are not universal models and that such a universal continuous improvement model is needed, particularly to meet the needs of "Quality 4.0".
Okay. I have never been a "buzz word" person and Quality 4.0, like its parent, Industry 4.0 are to me just fancy ways of framing concepts without solving anything. All Quality (or Industry) 4.0 says is that things are changing including information collection and evaluation and that we need to learn how to deal with and use those changes to thrive.
Here is a quote from Juran.com "The core concept of Quality 4.0 is about aligning the practice of quality management with the emerging capabilities of Industry 4.0; to help drive organizations toward operational excellence."
Lots of pretty words that (to me) boil down to; "Hey! Things are changing. Let's use that and keep making things better!" Which is what you and I have been doing all along.
But back to Dr. Watson's article. First, to his credit, he does a great job outlining many of the top improvement models and bringing out their weaknesses. Also the new IAQ model does make some of the currently unspoken steps, more clear.
I won't dwell on his assertions that DMAIC does not engage in a 'strategy formulation process' nor complete the improvement process controls. I strongly disagree. DMAIC's failures are management failures not process failures - as could be said for any method.
To me, the issue that any call for a new and improved continuous improvement model includes the assumption, especially in many managers minds, that a continuous improvement engineer should not need their brain. If we can be given a list of steps, and we follow those steps, an answer will pop out. Sorry, but any improvement effort requires a trained investigator to think, adjust, and use whatever tools are needed to reach the solution. This may even mean moving outside a specific model into uncharted territory.
As a (primarily) DMAIC practitioner, I have learned that the DMAIC is a flexible process that can be pared down or expanded up. And it always must include problem identification strategies going into a project and also consider implementing sustainable changes at the end. But this is also true for the other models.
I guess that having a one size fits all model is a great goal. Don't misunderstand. We should all continue to explore "improvements to the improvement process." But remember that often we have different models because they are each tuned to a specific need. Why would I ever consider using a financially based model to solve a shop floor quality issue? But its damn good for finances.
The new "IAQ" model proposes a seven step process (Characterize, Investigate, Explore, Solve, Evaluate, Implement, Monitor).
Think about those seven words and think about what you do every day as you find and solve problems. Sound familiar to you? To me the IAQ is just re-branding current concepts by changing the names. Its DMAIC. Its PDCA. Its the '8 Step Problem Solving Process" and all the others.
All improvement models, whether DMAIC, PDCA, 8-Step, Shainin, or others are subsets of an unspoken "master" model. This master model could potentially be described as "Find" problems, "Solve" problems" and "Fix" problems. In this case the PDCA model approaches our perceived "Master" model the closest and to be honest, that is what the IAQ model really does and does well. It provides that master concept. But I reject it replacing all other models, but I would embrace it being used, especially as a learning tool.
Bottom line is, that as an investigators of problems, we have a calling to learn as many tools as possible and to apply the appropriate tool for the particular job at hand. It may be a simple PDCA one time, a full DMAIC another, and a Shainin based process the next. Or (and most important) it may be an amalgam of two or more models. Maybe I get part way into my PDCA work and realize that a DMAIC SIPOC would be a great way to frame my issue. However, as I am "Defining" my problem, I pull in some Shainin "FACTUAL" (c) tools to help narrow down my problem definition at which point I find I need to transition into a Design for Six Sigma process.
Continuous Problem solving needs to be fluid, flexible, and adjust to the situation. That's all. It takes work. It takes training. It takes lots of study on ones own time. It also takes mentoring and coaching. What it does not take is a universal method with checklists that anyone can do.