Six Sigma Green Belt Training varies from 3 days to 3 weeks? Why such a disparity?

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Bill Pflanz

#11
Re: Six Sigma Green Belt Training varies from 3 days to 3 weeks? Why such a disparity

I had a client ask me if I can develop a "green belt" course without any projects or certifications. Just want to train their people in the tools and statistics, and not caring about the color of the belt.
My experience with a client was that they originally wanted the training for certifications but I was able to convince them that using the quality tools on company problems would be more valuable. By the time the course was over, they talked very little about being certified and the focus was mainly on the company benefit from the projects. I did create a Six Sigma test so that the company could certify the attendees after they completed their project. After I finished the course, the only questions I had (sometimes a couple of months later) were about their projects. They recently contacted me to do another training class so they must have thought it was useful. Steve would probably agree that those that truly understand the tools and statistics will see that the value of the training was not in hanging a piece of paper on the wall.

Bill Pflanz
 
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Statistical Steven

Statistician
Staff member
Super Moderator
#12
Mr

My experience with a client was that they originally wanted the training for certifications but I was able to convince them that using the quality tools on company problems would be more valuable. By the time the course was over, they talked very little about being certified and the focus was mainly on the company benefit from the projects. I did create a Six Sigma test so that the company could certify the attendees after they completed their project. After I finished the course, the only questions I had (sometimes a couple of months later) were about their projects. They recently contacted me to do another training class so they must have thought it was useful. Steve would probably agree that those that truly understand the tools and statistics will see that the value of the training was not in hanging a piece of paper on the wall.

Bill Pflanz

I agree with you Bill....but it is hard to sell that to the masses.
 
A

artichoke

#13
Re: Six Sigma Green Belt Training varies from 3 days to 3 weeks? Why such a disparity

I don't understand it either, unless the trainees have demonstrated at least a basic understanding of probability theory and normal-curve statistics. Perhaps then you could reduce the training to three weeks.
There is absolutely no need for green belt training in "probability theory and normal-curve statistics".
Most employees will never encounter a normal distribution and if they did, they would never able able to collect enough data to verify it. You might as well teach Burr distribution theory. For practical purposes, a Burr distribution is indistinguishable from a normal distribution but gives a 15,000% difference at 6 sigma. A Burr distribution may also be adjusted to fit a far wider set of skewed data than a normal one.



Most importantly, there is no need to understand either normal or Burr distributions if people properly understand control charts. There is a great misunderstanding that Shewhart charts are probability charts. They are not.
 

Jim Wynne

Staff member
Admin
#14
Re: Six Sigma Green Belt Training varies from 3 days to 3 weeks? Why such a disparity

There is absolutely no need for green belt training in "probability theory and normal-curve statistics".
Most employees will never encounter a normal distribution and if they did, they would never able able to collect enough data to verify it.
You've made a number of interesting observations on this subject lately, most of which seem to take the form of unsupported assertions. In addition to the statements quoted above, you say in this post Cp vs. Cpk - What is the difference - A visual animation,
Control limits are not probability limits. They do not give a probability of events falling outside limits.
and then
"Capability" means the capability of a process to meet specifications. This can only occur if a process is in statistical control.
I have a few questions:
  1. If knowledge of probability theory isn't important, why are we doing statistics? To put it another way, if we can use statistics to make predictions, why bother with statistical analysis at all?
  2. Do you actually believe that a process can meet specifications only if the process is in statistical control?
  3. Do you dispute the use of normal curve statistics in giving people a basic theoretical basis for doing statistical analyses?
You seem to be claiming to have overthrown some ideas that have been used successfully by many people for many years. I'm always open to learning, so perhaps you can help me to understand what you're saying.
 
M

Madfox

#15
Re: Six Sigma Green Belt Training varies from 3 days to 3 weeks? Why such a disparity

Because it's unregulated market!
(As opposed to ISO, where an accredited Lead Auditor course is 40 hours.)

I was taken back when asked what "level" of Shingo Lean training I had.

The Madfox
 
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A

artichoke

#16
Re: Six Sigma Green Belt Training varies from 3 days to 3 weeks? Why such a disparity

I have a few questions:
  1. If knowledge of probability theory isn't important, why are we doing statistics? To put it another way, if we can use statistics to make predictions, why bother with statistical analysis at all?
  2. Do you actually believe that a process can meet specifications only if the process is in statistical control?
  3. Do you dispute the use of normal curve statistics in giving people a basic theoretical basis for doing statistical analyses?
You seem to be claiming to have overthrown some ideas that have been used successfully by many people for many years. I'm always open to learning, so perhaps you can help me to understand what you're saying.
Jim,
Thank you for the good questions.
1. Deming discusses statistics in Ch3 "Diseases and Obstacles" in "Out of the Crisis". On p132 he says "Analysis of variance, t-test, confidence intervals and other statistical techniques taught in the books, however interesting, are inappropriate because they provide no basis for prediction and because they bury the information contained in the order of production." Imagine a run chart where the time sequence of the data was discarded ... that is in effect what enumerative studies are doing.
Shewhart said that if we had a process that was exactly stable and if we knew the details of its underlying distribution, we could work in terms of probability limits. However, in practice, neither of these conditions is ever met. The power of the control chart lies in the fact that it does not depend on the distribution of the data, which we can never know. Most importantly, the control chart is a predictive tool, whereas probability (enumerative) approaches are not.
Wheeler in his books "Understanding SPC", "Advanced Topics in SPC" discusses the above in detail. He does use probability to compare different types of control chart, although he does not do this in their application.
One of six sigma's fundamental flaws is that it has lost sight of the above, focussed on probability and forgotten the basics of control charts.

2. Yes. Processes are not limited in how far out of control they may become. Bill Smith's suggestion that the mean of out of control processes may vary "as much as 1.5 sigma" is quite incorrect. There is no limit to how far things can go wrong. Bill Smith suggested widening spec limits (as well as reducing variation) to avoid defective product. This is not enough. Processes must be in control. Only an in control process is predictable. This is the basis of what Deming refers to as an analytic study. The control chart is the tool of choice for this. There is no such thing as a "confidence level" for future behaviour.

3. Yes. Studying normal distributions is of no value for beginners. For experts, it should be studied as another form of theoretical distribution. It is of some historical interest as discussed in a very readable fashion in "Normality and the Process Behaviour Chart" by Wheeler, however it is of no relevance to process management. It should also be mentioned that while normal distributions are an interesting outcome of Laplace's central limit theorem, and Shewhart was are of this, he did not use it in his formulation of control charts.
 
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Tim Folkerts

Super Moderator
#17
Re: Six Sigma Green Belt Training varies from 3 days to 3 weeks? Why such a disparity

Some balance and common sense are needed whenever dealing with numbers. Perhaps Artichoke is going a bit strong toward one side, but many people also go a bit strong to the other.

I do think statistics are valuable and predictive within limits. Always these predictions are based on the assumption that things will continue as they have been in the past. Often these predictions are based on the assumption of a particular mathematical model - like a normal distribution. Either or both of these assumptions could be wrong in any given situation.

A big danger occurs when people forget that these assumptions were made. Then they blindly say things like "99.7% of data will fall within +/- 3 sigma" -- assuming that the data is exactly normal.
* even if the data is normal, there will be considerable random variation in exactly how many are outside +/- 3 sigma
* for different distributions, the theoretical % outside +/- 3 sigma can range from exactly 0% to 11%.

Here I definitely agree with
One of six sigma's fundamental flaws is that it has lost sight of the above, focussed on probability and forgotten the basics of control charts.
Another danger is that ANY summary of the data - mean, st dev, and yes, control charts - necessarily throws out information. This limits their predictive abilities. For example, consider an Xbar-R chart with a subgroup of 4. Each of the following sets of data will appear exactly the same on the chart: (1,1,-1,-1), (1,0,0,-1), (1.5,-0.5,-0.5,-0.5). Depending on the actual specs, these could have quite different affects on functionality - perhaps the USL is at 1.25.


Well, that's all I have time for right now. Perhaps later I can come back and add more.


Tim F
 

Statistical Steven

Statistician
Staff member
Super Moderator
#18
I think we are missing a fundamental piece to the black belt and green belt training. Management looks to these "belted" prodigy as the "expert" on ALL data analysis, not just quality improvement efforts and process control. Without a fundamental understanding of statisitics, these belted folks will spew out a set of t-tests instead of using ANOVA.

I am not a fan of SS, but I do all my training with the assumption that I need to teach you tools for your tool box and hope you will know how to apply them, and more importantly, know when you are in over your head and need to call a statistician. Experience has taught me that usually people who are belted are too proud to call in help for the fear that management will see SS as a failure.
 

Wes Bucey

Quite Involved in Discussions
#19
Re: Six Sigma Green Belt Training varies from 3 days to 3 weeks? Why such a disparity

I am not a fan of SS, but I do all my training with the assumption that I need to teach you tools for your tool box and hope you will know how to apply them, and more importantly, know when you are in over your head and need to call a statistician. Experience has taught me that usually people who are belted are too proud to call in help for the fear that management will see SS as a failure.
Amen! As much as I think I know about quality tools, I absolutely, positively know when I need to call in someone who knows more when I run into something that has me scratching my head.

Too often, "one-trick wonders" live in constant fear that "Today is the day the bosses find out how little I really know."

The only cure for that fear is to keep learning and freely admit to anyone and everyone that you are always willing to learn a new or better way.

From my own point of view, rarely does a week go by without me learning something new and useful here in the Cove. Most importantly, I learn new sources of information.

One of the fields of knowledge we discuss continually and pertinently here is the "human equation" - techniques for interacting with bosses, coworkers, subordinates, suppliers, and customers. Many brilliant professionals in our field have had their careers torpedoed by being blind to the human equation.
 

Jim Wynne

Staff member
Admin
#20
Re: Six Sigma Green Belt Training varies from 3 days to 3 weeks? Why such a disparity

1. Deming discusses statistics in Ch3 "Diseases and Obstacles" in "Out of the Crisis". On p132 he says "Analysis of variance, t-test, confidence intervals and other statistical techniques taught in the books, however interesting, are inappropriate because they provide no basis for prediction and because they bury the information contained in the order of production." Imagine a run chart where the time sequence of the data was discarded ... that is in effect what enumerative studies are doing.
I think you might be creating a false dichotomy, that being the idea that "enumerative" tests and control charting are mutually exclusive. I wholeheartedly agree that chronology is indispensable in control charting, but that doesn't mean that you can't do control charting and use other types of statistical analysis when appropriate.
Shewhart said that if we had a process that was exactly stable and if we knew the details of its underlying distribution, we could work in terms of probability limits. However, in practice, neither of these conditions is ever met. The power of the control chart lies in the fact that it does not depend on the distribution of the data, which we can never know. Most importantly, the control chart is a predictive tool, whereas probability (enumerative) approaches are not.
I think that our only difference here is one of semantics. You can't be "predictive" without knowing something about "probability." You're defining "probability" more narrowly than I was, which is fine, so long as we understand one another.
One of six sigma's fundamental flaws is that it has lost sight of the above, focussed on probability and forgotten the basics of control charts.
I don't disagree with this.
Yes. Processes are not limited in how far out of control they may become. Bill Smith's suggestion that the mean of out of control processes may vary "as much as 1.5 sigma" is quite incorrect. There is no limit to how far things can go wrong. Bill Smith suggested widening spec limits (as well as reducing variation) to avoid defective product. This is not enough. Processes must be in control. Only an in control process is predictable.
I'm wondering now if you misunderstood the question. It was,
Do you actually believe that a process can meet specifications only if the process is in statistical control?
Note that I did not ask if a process that is not in statistical control can consistently produce product that meets specifications. My point was that you seem to be confusing specification limits and control limits, but since that is a very basic error, I doubt that that was what you meant to do. Processes that are not in statistical control can produce product within specification limits. You say that they cannot.

There is no such thing as a "confidence level" for future behaviour.
My assumption is that you're referring to an analytically-derived, quantitative confidence level, although I'm not sure about the scare quotes. I think I agree, but we have to make sure that everyone who's likely to read this will understand what we're talking about. We can't lose sight of the fact that process design is a critical element of process control, and that it's possible to state that the probability of maladjustment of some process variable A resulting in nonconforming product is 1 without fear of contradiction.

Studying normal distributions is of no value for beginners. For experts, it should be studied as another form of theoretical distribution. It is of some historical interest as discussed in a very readable fashion in "Normality and the Process Behaviour Chart" by Wheeler, however it is of no relevance to process management. It should also be mentioned that while normal distributions are an interesting outcome of Laplace's central limit theorem, and Shewhart was are of this, he did not use it in his formulation of control charts.
Here I will disagree unequivocally. The theoretical nature of the normal distribution is largely irrelevant to the question. If we want neophytes to gain any sort of useful knowledge of statistical analysis at all, they must be conversant with normal curve theory. You are certainly correct in pointing out that Shewhart recognized that manufacturing processes don't perform the same way that processes in nature perform, but unless one understands that, there is no basis for moving forward. In other words, in order to understand why there is a difference between natural processes and man-made processes, a fundamental understanding of normal-curve statistics is necessary. My original point (regarding requisite knowledge for green belts) was that if they have a basic understanding of normal-curve theory and probablility theory, they have some basis for proceeding up the dubious belt chain. I did not mean to suggest that basic knowledge should be considered comprehensive knowledge.
 
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