Shewhart/Deming Statistical Process Control vs Six Sigma

"The problem is that most courses teach what is wrong."
-- W. Edwards Deming - Quality Founder - (see Deming's Quotes)

There are a number of critics around Six Sigma at least around its marketing hype:

- Juran's interview
- Desperately Seeking Sigma

Juran said:

"I don't like the hype, and I don't think the hype is going to last. Something that is as successful as the improvement process gets label after label after label. Those labels come and go, but the basic concept stays. There will be some marketer that finds a new label, finds a way to make that a fad and off he'll go, doing the same thing we did before under a new label."

Apart from the hype critics, Six Sigma (associated with Motorola) does not focus on the background Philosophy of Statistical Process Control founded by Walter A. Shewhart - later popularized by his student W. Edwards Deming - at least in its understanding or practice by the community of users, vendors and consultants. This risks not to be changed with Lean Six Sigma.

Why? Though Common and special causes seem to be listed in the majority of Six Sigma glossaries, people seem to "learn without understanding" - to borrow the title of a chapter (excerpt here) from Richard Feynman's book. Mostly, many presume that their process under study follows the Normal Law Distribution. To illustrate the case, it is interesting to read the testimony of a quality practitionner and consultant in one of his article untitled "Non-Normal Distributions in the Real World" where he said:

"After nearly two decades of research involving thousands of real-world manufacturing and nonmanufacturing operations, I have an announcement to make: Normal distributions are not the norm.

You can easily prove this by collecting data from live processes and evaluating it with an open mind. In fact, the early quality pioneers (such as Walter A. Shewhart) were fully aware of the scarcity of normally distributed data. Today, the prevailing wisdom seems to say, “If it ain’t normal, something’s wrong.” That’s just not so."

In fact the flaw seems rooted in the core definition of Six Sigma as understood by some people like here:

Below is Bain’s explanation of Six Sigma:

“Sigma” is a measure of statistical variation. Six Sigma indicates near perfection and is a rigorous operating methodology aimed to ensure complete customer satisfaction by ingraining a culture of excellence, responsiveness and accountability within an organization. Specifically, it requires the delivery of defect-free products or services 99.9997 percent of the time. That means that out of a million products or service experiences, only 3 would fail to meet the customer’s expectations. (The average company runs at around Three Sigma, or 66,800 errors per million.)

Six Sigma cannot indicate with perfection if the process does not follow normal law and as every practitionner should check, normal law is, more often than not, an exception to the normal law in the real-world.

There is no need of Six Sigma to become a "Black Belt".