Introduction

In this episode, David and Andrew talk about Common Cause Variation vs Special Cause Variation, and the problem of confusing the two. Using the example of transgender students, David describes how a system's capability should be expanded rather than using that special cause situation as a weapon to destroy the entire system. 

TRANSCRIPT

Stotz: 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 am continuing my discussion with David P. Langford, who has devoted his life to applying Dr. Deming's philosophy to education, and he offers us his practical advice for implementation. Today's topic is weaponizing special causes. David take it away.

Langford: It sounds very dangerous, and it is. So I wanted to get into a little bit about special and common causes about what Deming talked about. So once again, we'll go back to Deming's system of profound knowledge. And as part of that he talked a lot about understanding variation in systems and without getting too statistical about things, he basically got people to identify two different types of variation. So there's common cause variation, which typically makes up anywhere from oh 94% to 98, 99% of what goes on in any system or any process. And then there's special cause variation, which is generally less than 2% or less than 1% of what goes on. So that sounds pretty innocuous until you actually start thinking about how that works out in society and systems and classrooms, especially in education in schools and Deming said over and over and over that there are basically two problems with special and common cause. So people treat special cause as if it's common, okay. Which is, and he called these deadly diseases, or they treat common cause variation as if it's special.

Langford: So sometimes it's difficult to sort of understand what is, what does that mean? So let's take an example like in a, in a school common cause variation would be say the, the performance of a whole school or a state or a nation or whatever it might be. You can chart that out over a long period of time and start to see a certain level of predictability of performance on anything you wanna look at, whether you're talking about behavior or you're talking about test scores or grades or kids showing up for school every day. Doesn't really matter what system you wanna look at. When you start looking at it from a systems perspective, you wanna look at as much data as you can.So at least six or seven data points, but preferably 12 and some, a lot of statisticians will say up to 20 data points.

Langford: So if you're just looking at, say test scores over a long period of time, well, you'd wanna actually look at average test scores over a 20 year period. So that, that could take a really long time to see data systems like that emerge, especially in education where we have what I call slow data that emerges. You’re familiar with like manufacturing environments and business, where you have a lot of fast data. So you may be making something and you're collecting a hundred thousand data points in a single day or a month or a week where in education, it, it really doesn't really work like that.

Stotz: I have an example that may be helpful for those people that aren't familiar with the topic. And that is in my coffee factory, we fill bags of coffee with, let's say a hundred grams of coffee. If we fill it with 101, well, we're giving away. If we fill it with 99, we're not delivering what we say. And what first lesson that we learned is that nobody's perfect. No, there is no way to consistently hit 100 is always gonna be some variation. Now that variation may be 100.0 1, 4 7, but ultimately variation around that is bad. And what you find is that maybe when the system is not that strong, you could be putting in 95 grams on sometimes and you could be putting in 105 on sometimes and something in between those. But those are all kind of common causes.

Stotz: There's just there's variation about that average, let's say. And then the only way to improve that would to be say, ‘oh, well, we need to have a more precise piece of equipment.’ It’s not that the workers weren't working hard enough or something, but we just didn't have, so we replace a piece of equipment that's measuring and all of a sudden we weigh more consistently the old clunky one didn't work that well, and now we're getting more and more narrow. And then one day the electricity goes off or we have a, a problem with the electricity and all of a sudden it's throwing the whole system off. Well, that would be some special cause as opposed to this common variation around the 100 that we're aiming for, would I be describing it? Right or how would you add to that?

Langford: Yeah, that, that that's exactly right. And so if we charted out filling your coffee bean bags over a long period of time, we'd probably find out that you'r, you probably have a really good system, right? So let's put it in terms of like grams or something. So you might find out that your variation is anywhere from 98 grams to 101 or a hundred, two grams. Right. And this also ties in with the last podcast we did about loss function. Because if you say, well, we're selling hundred gram bags, well, the further we move away from optimization or the optimum of a hundred grams, like what you were saying, if we're filling it too much, we're losing money. And if you're filling it too little, well, there might be a customer out there that feels cheated and might not ever buy your coffee ever again, because they, they weighed it and said, oh, this is only 99 grams.

Langford: Right? So there, and if you, the further that you would go away from that optimum 100 grams, and let's say that all of a sudden, you sent out a coffee bag that only had 90 grams in it. Now somebody could get really upset, right? Because that's a long way from the optimum of a, of a hundred grams or the opposite, right? If, if you're all of a sudden, randomly filling bags at 111 grams, well, now you take that 11 grams times the price of coffee beans. And like you said, you're losing a lot of money a lot of time.

Stotz: So it's one, one thing I would add to it is that now imagine that we’re measuring it very well, and we're getting a little variation. We're getting 101 sometimes. And 99, occasionally we get 102, occasionally we get 98, but it's in a relatively tight range. Now imagine that I start rewarding the employees when it goes, you know to a certain level and I start to identify if you hit this, that you're gonna get a bonus, I'm gonna dock your pay. Well, I would just be messing around with what are really just common causes of variation that have nothing to do with the employees. They have to do what that system can do.

Langford: That's what Deming called tampering. You're tampering with the system and you're, and you're making false assumptions, cuz you’re assuming that, oh, by holding somebody up as employee of the month that'll make everybody else work harder. So your assumption is that everybody else is not working harder. And the only way to get 'em to work harder is for me to manipulate 'em in some way. And Deming said that you you're now tampering with the system. You're making things worse, not better because pretty soon you have employees that say, well I'm not gonna do a really good job this month because you're offering that bonus you know, for most improved employee. Well, I can't be most improved if I'm always great, right? So one month I'm gonna look bad so I can look really good the next month.

Langford: So I can win that trip to Aruba, right? And now your coffee, the grams per sack are going down. And so everything's going haywire and everything else. And then, then you wanna blame the people in the system and not understanding that as management, you did this. You caused this to happen. And it's exactly the same way in a school classroom for education. If you start tampering with learning systems in the classroom. So most of the variation or performance of a system is built into the system. And that's what Deming talked about. Statistically like in 98, 98% of the result is coming from the system itself.

Stotz: Right. So don't like the results? Don’t blame the people, blame the system. So are, are there people problems and systems that are special causes? Absolutely. And what do you do when that happens?

Langford: So like in your example, with your coffee company once in a while, maybe you just, you hire someone that hates coffee, really shouldn't be there, they're there for the wrong reasons. They don't really love what's going on, you know? So what do you do? Well, instead of like changing the whole system based on that special cause person, right? Now, everybody has to do something different because we have this one person who's got defective behavior, so to speak, you just, you deal with the one person. Maybe they're just in the wrong job. I mean, they, they should be answering the phone in the company, not actually dealing with products or, or vice versa. Maybe they just can't deal with people. So maybe they should be in a position. So you're gonna make an adjustment. You're gonna shift that one person. And ultimately, maybe they're just in the wrong profession and maybe you need to help them find another job.

Stotz: And I just, I just wanna go back because it's such a common thing that people talk about about what Deming says about the output of the system is coming from a certain amount and the output the impact that a worker has for instance. And one of the sources of that is looking at the standard deviations. From the average, if you look at one standard deviation plus and minus you come up with 68% are within that range. If you go two standard deviations, now you're at 95%. And I believe it was that two standard deviation where he's saying, look, if something's happening within these two standard deviation, it's just common cause variation. No. He was actually talking about three standard deviations.

Stotz: Yeah. So three standard deviations would be what? 99.7%

Langford: Yeah. St yeah. Statistically it's like 99.9999998%. Right. Of something. And you know, why three standard deviations away from the, the mean, or the average? Well, because when you get to that point, if something is falling in that less than 1%, you could be pretty sure that's, that's, that's a special cause. Right? This doesn't normally happen in our, in our system. Well, the same thing in a classroom, if, if a teacher's teaching a lesson and every year when they, he or she teaches this lesson, everybody in the class scores, like, let's say 95 to a hundred. Right, right. And every year I get better and better. And my variations shrinks. And pretty soon I've got, now I'm getting an average about 98 percentile of people when they go through this lesson, right? Well, that's telling you that most of the variation is good within that system. So when people are randomly thrown into that classroom, that teacher is so good they can get that same result with almost anybody thrown it into that classroom.

Stotz: And then now.

Langford: What happens, that system is like that it becomes predictable. Now I can predict that next year. I'm probably gonna get an average somewhere between 95 and a hundred percent, if I keep doing what I've been doing.

Stotz: And what happens to that teacher when they see, oh, wait a minute, we've got this one kid who's getting a 62.

Langford: Then obviously, because you understand systems performance and you understand a little bit about special and common cause data, obviously this is a special cause there's okay. So it could be a learning difficulty. It, it could be home situation. It could be something psychological, it could be, could be a lot of things. Right. And so what do you do with a special cause? Well, typically like in the education system, we basically tried to get rid of 'em for years and we get, we would get rid of them in many different ways. Like, I'll, I'll just give them a failing grade and that that'll get rid of 'em eventually. I’ll send 'em out in the hallway, isolate them. I'll, we'll send them to special education classes. We don't we don't wanna have a mainstream in the class because it's a special cause.

Langford: And it's gonna take special effort to do, to work with that special cause and work through that. So veteran teachers that are really super good at dealing with students with special causes are amazing. Just amazing how no matter what the difficulty is or what the special cause that child starts to feel like they're part of the system, part of what's going on. Now, they may never get the same data as 98% of the rest of the students that come through that system, but they can also get better and better and better with, within that same system. And you that’s the exciting thing about education is to think about how special causes can be transformed.

Stotz: You remind me when I was in living in West Hartford, Connecticut, when I was just a little kid, I was all kinds of trouble in the classroom. And I was just, I just was all kinds of trouble. And they sent me to some special class to get some special help. And I ended up reentering the normal class and coming back kind of into a normal behavior, cuz they helped me kind of work on some of the things that were issues for me. And I ended up becoming a good student. But imagine...

Langford: You had, you had shock shock therapy or something.

Stotz: Yeah. They, they got me, they just a minor lobotomy this, but so now let's think about this cuz the, the title of today is weaponizing special causes. We've had a great discussion now about what are common, what are special? And I'm just imagining, like, let's just say that a teacher's doing really well, but they have this one student doing poorly and we know it's identified as a special cause. And then all of a sudden they decide, wow, I've gotta redo my whole way that I'm educating because of this particular unique situation. Would that be wise?

Langford: Well, it be insanity is what it would be. And we don't have to go very far, especially in the United States right now to see this happening. So there are transgendered children that that's, that's a fact, everybody knows this is happening, etcetera. But because I have one transgender child in my classroom or my school does not mean I changed the entire system based on a special cause. And now I'm disrupting 99.8% of all, all the students and parents and everybody else that comes through the system because I'm making this system twist to accommodate only a special cause. So and Deming said, this is one of the deadly diseases. So I'm gonna, I'm gonna change the whole bathroom structure into building. I'm gonna change the whole, how PE is run. I'm gonna, we're gonna change. We're gonna change everything because we have two children out of 1400 that may be transgender.

Langford: So I don't want to, I don't wanna offend anybody by this or anything else, but I just wanna point out that you can spend literally millions of not billions of dollars. go weaponizing special causes. And this is, this is just one example and PE uh districts are now building schools., where's, they're changing the bathrooms and getting rid of gender and all kinds of things based on only a few special causes. Whereas what should be happening is what do special causes needing these special, special help? So if they need a special bathroom, that's, that's fine. And there's a transition or gender bathroom for those two students out of 1400. Yeah. But just suddenly you start making rules, regulations policy I've seen district policy. That's just crazy based on maybe one instant instance every 10 years or so. And you're, you're changing an entire system based on that. is it that maybe gonna help that one individual? Yeah. But it's the same example as, as you gave, right? instead of changing the whole school because you were having difficulty in a classroom, what did we do? Well, we got you some help, right? Yeah. And basically you need discipline and people don't, people don't understand what discipline means. The first definition of discipline and the dictionary is training.

Langford: So you needed some training, right? This is what you do and this is what you can't do and in a classroom and everything else. And when you got that kind of training and it was better for you because you felt like you were belonging and you didn't have to be disruptive anymore. And it was better for everybody else because they could accept you. Right. They didn't, they weren't all of a sudden afraid that you were gonna fly out the handle or go crazy.

Stotz: Yeah. It's, it's interesting about the transgender stuff because in Thailand Thai people are just really accommodating to transgender. It's not a big deal. I mean, and in fact, the transgender people here are people who really speak up for kind of their rights. They're more outspoken. Whereas other people kind of go along more than let's say we're used to in the west. so they're there, it's just been fascinating to watch. And I think that the point is, and it's a little bit like handicap as an example we did decide to put in ramps to, to locations. And that was an adaptation to the system to accommodate the needs of that small group, but we didn't reshape a huge amount of things and other people in...

Langford: That. Well, what you're trying to do is well we see it now in medicating children with drugs and all kinds of stuff to help them learn better. And and in some cases, some schools and places you're, you're talking about 20, 25% of the population is now being medicated. Well, that's the, that's the opposite of what Deming talked about is treating special causes as if they're common that this is a common thing. So we're gonna do this with everybody. But these special causes are very, very rare, whether it's some kind of a mental thing or transgender thing or whatever it might be, you're talking about less than 1% of the population generally. And when you start to transfer a special cause to a whole population, that's what I'm talking about, about weapon weaponizing a special cause. And then ultimately you can do that with anything, but what you're really trying to do, and you comment about the, the handicap access, etcetera. What you're really trying to do is expand the capability of a system so that there are fewer and fewer and fewer special causes, not going the opposite direction, where the system becomes less and less and less and less capable. And so pretty soon everybody starts looking like a special cause.

Langford: And and that becomes hugely expensive and not very productive when you're treating everybody like their special cause.

Stotz: So let me try to summarize a little bit about what we've talked about. First of all, we talked about the importance of understanding variation. And we talked about the idea that 94 to 99% of variation is actually common cause, and only maybe one or 2% is special cause, and you, you mentioned about treating special causes as common was what Dr. Deming calls deadly diseases. You also talked about tampering, which is when you're chasing around common cause variation and either rewarding it or punishing it or highlighting it as success when in fact you really are having false assumptions. And the best way to think about that is that you walk into McDonald's and it's got a picture of the employee of the month and it's just a rotation. And then you talked about identifying the special cause, let's say it's a poor performing student.

Stotz: And then thinking about how do we how do we deal with this special cause? And it doesn't make sense necessarily to change the whole system because of what we're seeing with the special cause. And finally, I'm gonna add in my last little bit I wrote down when you were speaking is let variation run! Allow variation. It is the beauty of nature. It is the beauty of human. It is the beauty of system. Stop trying to attack every variation through medicine or through all these different things. Let variation free. Let variation run. Anything you'd add to that.

Langford: No, it's no, that's, that's good. It's a good summary. Yeah. It's in some ways it's very, very simple to think about. But in other ways, it's, it's very complex and in many ways, very contrary to the common society and businesses and schools and the way they’re run today.

Stotz: It's simple. But not always easy.

Langford: Yeah. And I think that's why Deming calls it profound knowledge. You have to have profound knowledge and profound means deep. You have to have a deep knowledge of something if you're gonna manage properly.

Stotz: Fantastic. Well, David, on behalf of everyone at Deming Institute, I want to thank you again for the discussion for listeners. Remember to go to deming.org to continue your journey. David, what's the best way that people can contact you if they wanna learn more?

Langford: You could go to our website, which is LangfordLearning.com, and there you can find out resources and support material etcetera.

Stotz: Fantastic. Well, this is your host, Andrew Stotz, and I'll leave you with one of my favorite quotes from Dr. Deming. People are entitled to joy in work.