Comparing Deming, Lean, and Six Sigma: Interview with Mustafa Shraim

Andrew Stotz talks with Dr. Mustafa Shraim of Ohio University about Deming's approach to variation, comparing it to Lean and Six Sigma.

"When you do Six Sigma, you're basically outsourcing your quality to an external source, providing the training, the titles, and all of that. You can cut it off any time. But when you do the [Deming] theory of knowledge and the Plan-Do-Study-Act, you have to commit. The commitment is really the big deal here...the component that is missing [from Six Sigma] is a commitment to quality."

SHOW NOTES4:30 Variation 12:40 The problem with Six Sigma 20:40 Statical Process Control Charts 25:44 Deming chain reaction 30:03 Suboptimizing departments 43:01 Management by visible figures 40:05 Why Deming, why now? Driving out fear 50:52 Continuous improvement and Plan-Do-Study-Act

TRANSCRIPTDownload the complete transcript here.

0:00:04.1 Andrew: My name is Andrew Stotz, and I'll be your host as we continue our journey into the teachings of Dr. W. Edwards Deming. Today I'm here with featured guest, Mustafa Shraim. Mustafa, are you ready to share your Deming journey?

0:00:19.8 Mustafa: Absolutely, let's go for it. Thank you.

0:00:21.5 Andrew: I'm excited. Well, let me introduce you to the audience. Mustafa Shraim is an Assistant Professor at Ohio University teaching quality management and leadership. Professor Shraim has over 20 years of experience as a quality engineer, corporate quality manager, and consultant. His PhD is in Industrial Engineering. He publishes widely, and he has a passion for Dr. Deming's system of profound knowledge. Mustafa, why don't we start off by you telling us the story about how you first came to learn of the teachings of Dr. Deming and what hooked you in?

0:00:57.5 Mustafa: Yeah. Thank you, Andrew. Thank you for inviting me back. So...

0:01:01.9 Andrew: Yeah.

[chuckle]

0:01:06.1 Mustafa: The whole thing started when I was doing my master's and that was the late '80s, at Ohio University, and I was concentrating on the area of quality. So, I was doing research, and my research touched up on what Dr. Deming was doing. I was doing it in design of experiments and quality tools and things like that. But of course, you come across Dr. Deming's work when you talk about quality control, in general, and statistical quality. So, that was the first encounter of learning about what Dr. Deming did in Japan and how he used statistical process control and things of that nature to teach how you can improve your processes, your products, and later on, the management. But at the beginning, I did not really get into his management philosophy so I was more on the technical end of Dr. Deming's teaching which was mainly quality control and SPC, and just improving quality in general.

0:02:24.1 Mustafa: So, as I went... So I went, and I started my first job as a quality engineer, and quickly after that, maybe after one year, I moved to another company, and I became a statistical quality engineer, and I was doing... I was a part of a training program there. I was doing training on SPC as a part of a training for employees at that company. It was a union shop, it was automotive, and so we utilized statistical process control and what Dr. Deming was teaching. So, that was the beginning of it, but later on in the '90s, I started learning more about Dr. Deming after I read "Out of the Crisis" and then "The New Economics" about his management method. In fact, his management methods just captured me. I knew I got hooked on the quality part first, but the management method just brought it together for me. And since then, I've been reading and practicing, trying to at least, what Dr. Deming has taught.

0:03:41.9 Andrew: And would you say... One of the things that I started realizing was that the statistical... What I thought was the end was the statistical tools. And what I started to learn is that, actually, the statistical tools start to have limitations if you're not doing the management of the whole operation in a good way. And I think that that's something that really resonated with me when I started putting the pieces together. How do you see the role... And in a little bit I'm gonna ask you about some more specific tools, but just generally, we have statistical tools, but we also have management. Many people may think that you can just apply statistical tools and solve all the problems, but I'm curious how you see that interaction between the tools and the management style.

0:04:30.2 Mustafa: Well, as you know and many, probably, of your listeners already know that Dr. Deming had understanding variation, or some variation, as a part of his system of profound knowledge. So, understanding variation, under it, is really learning how to distinguish between the types of variation that you would have in any situation, managerial or process situation. So, that interaction there is really big. That really captured me because what Dr. Deming says is like, more than 80% of the application for statistical process control is actually, should be in management, and not necessarily just on the line, controlling quality of the product. So that was... It captured me, and because of explaining how many managers, many supervisors, don't understand the difference between common cause and special cause variations, and they start managing people with common cause variation going up and down, and they reprimand if it goes down, and they praise if it goes up, and that actually just makes things even worse in the future. As you probably know, it's tampering with the process.

0:06:08.8 Andrew: The best way that I've ever come up to try to explain this is to say to people, "Imagine there's 10,000 people in a stadium. They all flip a coin, and you say, 'Hey, if you flip heads, go to one side of the stadium. You flip tails, you go to the other. Everybody sit down. Okay, now... '" Or basically say, "Flip the coin again, and if you flip heads again, so two times, stay standing. And if you flip tails two times, then stay standing, but if you hit the heads and tails, then sit down." And now, your audience is getting smaller and smaller. If you do this 10 times, you will have 10 people, generally, you're gonna have 10 people that have flipped heads consecutively 10 times, and people that flip tails consecutively 10 times.

0:06:54.1 Andrew: And if we said, if we started off the whole game by saying, "Tails is bad." Now you've got some people that have done bad 10 times in a row, and some people that have done good 10 times in a row. But we know, because of the design of that example, that it's purely random. So, the question... So, we can understand that, but when we think about random variation, what Dr. Deming started to do is show us how that fits into management and psychology and how we're missing that. I'm just curious if you can help us to understand how that variation fits into that management 'cause you started talking about rewarding and all that. So, just curious about how those things fit together.

0:07:38.7 Mustafa: Right. For example, within the control limits, and those are the limits that are on a control chart, and they are spaced three standard deviations up and three standard deviations down. All the variation within is mostly a common cause variation, and it's due to the system. It's a system variation. It's not attributed to any special cause whether it's operator or something else that changed. So, distinguishing between the two becomes very important because if you don't look at variation from the perspective of a control chart, what happens is that you are in the weeds, and you look at every point as either really high up or high down cause you don't have any perspective as to how to evaluate or filter this type of variation. On the other side, also you don't want to not react to something that is special. For example, if you don't have the control limits, and if you don't have a proper way of looking at the variation, then you might end up also passing a special cause as a common cause, or not reacting to it enough to fix it and to make it a part of your controllable system before moving on.

0:09:16.7 Mustafa: From both perspective, I think it's very important for managers, for leadership, to understand why we do this. It's not just something that you have to do on the production line. It is something that you have to do in management based on performance. Look at your data and see if it's a stable process in control or if it's not, then you need to start eliminating those special causes. Like Dr. Deming said that, "Nothing really is born perfect as far as the processes." I'm paraphrasing here. But when you start a new manufacturing process, it doesn't mean that it's going to be in control; you have to work at it. You have to eliminate one by one all these special causes that come up before you start seeing a stability. And then after stability, then you will be able to work on the system part of the process, which is a long-term continuous improvement projects.

0:10:29.9 Andrew: Yeah, it's interesting. I remember a story. When I was working at Pepsi, we had a bottling plant in Los Angeles that I worked at. And the management were putting pressure on the people that were running the bottling machine because the variation of the level of the liquid in the bottle was getting wider and wider. And so, as a supervisor on the factory floor, my job was to go and kick ass, basically, and tell the guy, "Hey, come on, what are you doing here? You're messing around." And he just said, "Look, Andrew," and I was a young guy who listened to what these guys said, and he said, "Look, look at that machine over there. They spent the mone