The Taguchi Loss Function: Deming in Education with David P. Langford (Part 9)

What is the Taguchi Loss Function and how does it apply to education? In this episode, Andrew and David talk about statistician Genichi Taguchi's idea that the further you move from a measurable quality target, the more quality is lost, even if the item still "meets specifications." David shows how you can apply this to education.

(For more about the Tachugi Loss Function, visit Wikipedia or Christopher Chapman's Digestible Deming blog post.)

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'm 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, Taguchi loss function. David, take it away.

Langford: Thank you, Andrew. And I liked how your eyes got really big when you said Taguchi loss function. Oh my gosh, it sounds frightening, doesn't it?

Stotz: It does. It's a little bit overwhelming, it's exciting. I'm interested to learn.

Langford: And in education, it's probably less known than it is in business. Usually when I'm working with a group of business leaders and I mention that I can get pretty strong - two-thirds of the audience probably knows something about the Taguchi loss function. I was at a conference with a whole roomful of school superintendents and I asked them, Anybody know what the Taguchi loss function was? And not a single hand went up. So less well known, but just as applicable. So in one of the earlier podcasts, we were talking about the concept of optimization of the system. And I just wanna refresh our memories and the memory of our listeners that it's really based on Deming's System of Profound Knowledge as well. So the four parts that Deming had was, Appreciation for a System, Understanding Variation, and especially statistical variation, Psychology and Knowledge of Theory. And I always add neuroscience to that mix as part of profound knowledge, because it's really critical to understand, especially in education, how the brain actually processes information.

Langford: So when we're talking about the optimization of a system, we're actually talking about all of those factors being optimized, especially in a classroom or a school. So you can't just sort of optimize one thing, for instance. So over the last 30 years, I've known principals that are just really, really good managers, excellent at running the building. They never do anything out of the ordinary, everything is always perfect. The trash cans are always where they're supposed to be. They're just really good managers. They're the kind of people that if you're gonna take a school trip and they have to organize something complex, that's the kind of people you want. But if you're gonna do something really super innovative, change the system in some way, do something that's never been done before, that's not the kind of person that you want.

Stotz: Right, it's interesting that you just mentioned that optimizing so many different factors, that's part of the reason why people don't do it because it is complex. David, I just pulled up Wikipedia and I thought maybe it would be interesting if we see what Wikipedia says about what is the Taguchi loss function. Would you like me to read a little bit of that?

Langford: Yeah, so, go ahead.

Stotz: According to Wikipedia, the Taguchi loss function is graphical depiction of loss developed by the Japanese business statistician, Genuichi Taguchi to describe a phenomenon affecting the value of products produced by a company. Praised by Dr. W Edwards Deming. It made clear the concept, of the quality does not suddenly plummet when, for instance, a machinist exceeds a rigid blueprint tolerance. Instead, loss in value progressively increases as variation increases from the intended condition. This was considered a breakthrough in describing quality and help fuel the continuous improvement movement.

Langford: So now that we've lost about 80% of our audience...

Stotz: Oops, sorry about that.

Langford: No, that's... It's actually correct, and Taguchi was actually a contemporary of Deming, and Deming always referred to Taguchi as having one of the best, the greatest breakthroughs in systems. I really wanna focus on in education and applying this kind of thinking to education and what would that mean? So I think we looked at a Taguchi loss function diagram and if you could pull that up on the screen?

Stotz: Yeah, let me pull that up for the video viewers and I'll walk you through and we'll walk you through for the audio listeners.

Langford: And then we'll put a link in the show notes for that.

Stotz: Yep.

Langford: If you wanna contact it later. So basically you have to start to think about... And then, in the diagram right in the very middle of the diagram, is the target or what Deming would talk about as a system that's perfectly optimized. And in that, there's not losses on either side. And basically, without getting in into too much statistics or math or anything like that, the further you move away from that optimum state, the greater the loss. So, I wanna talk...

Stotz: And maybe for the listeners, I'll just describe it. We're looking at a parabola. So we have... On the Y axis, we have the level of loss. In other words, if it goes down on the Y axis, the loss is going down. And on the X axis we have the value of the characteristics, meaning we wanna hit some target and the parabola is going up if you go too far away. So loss is rising if you go too far to the right or loss is rising if you go too far to the left. So, in fact, that's kind of interesting. Both if you're off target either way, it's still gonna bring you loss.

Langford: So let me give you a very practical education example. My good friend, Dr. Doug Stilwell in Iowa, when he was a school superintendent, his problem was that, parents were complaining when... The time that they would get called when there was a snow day or a school cancellation during the winter. And so these complaints just had gone on year after year, after year for 20 years. And so finally, when I taught him about the Taguchi loss function, he did a little study with parents to find out the optimum time to be called. And so sent out surveys and said, "What would be the optimum time?" And if I recall, it ended up the perfect time was like 6:20 in the morning. So the further, the earlier you did it as you move towards say 6 o'clock or even earlier, if you went all the way to 5:30, then the losses became huge. There's these tons and tons of people did not like that. And on the other side, if 6:20 was the optimum, the closer and closer that you move towards 7 o'clock, there's already people going to work and making other plans and not being informed, etcetera.

Langford: And so the losses are mounting on that side as well. And so he ended up implementing a system that in explaining parents always even new parents coming into the system that, "You will receive a notification by 6:20 every morning whether or not there's gonna be a school closure." And guess what? Complaints virtually disappeared completely. So I think it's a really good example about you can optimize... Even sometimes people say, "Oh well, that's not a big deal, and I'll just put up with the complaints." But why would you wanna do that? Why would you wanna have parents calling board members and calling the school and complaining about this and that. And it goes back to really making people happy within the system, but you're not just making them happy just for happy's sake, you're making them happy because you're doing a really good job of managing with the input of the people in the system because they're the most knowledgeable about the systems.

Langford: So, so many managers will make a decision like that, it could be based on what's best for the front office. It could be that the decision is what's best for me as a manager. I don't like to get up before 6 o'clock in the morning and check the weather and have that to be the first thing I do during the day. And so I'm gonna do it at this time, but have no systems knowledge. They haven't taken the time to actually solve the problem or understand even what the problem is. And that is where I think Taguchi loss function really comes in. Same kind of an example I wanna share would be like in a classroom, if you're talking about the speed at which you're moving through material that you're teaching kids as they're learning about stuff, well, you go too fast, the losses are gonna be students who can't keep up, don't understand, get frustrated and get mad, etcetera. That's on one side.

Langford: And on the other side, you go too slow, you have all the students that really do grasp things quickly and wanna move forward. So understanding that optimum zone, and often times in neuroscience, scientists will sometimes call it the learning zone. That there's a zone or speed that you can go in, but there's another way to optimize learning within the classroom too. And that is, as a teacher to stop managing the pace yourself and let each student learn to manage their own pace. And so now each student is starting to optimize learning based on their pace. Well, the reason we don't do that is if I've got 30 kids in the class and I got 30 kids at different paces, that's a lot more work for me as the teacher, right. Rather than me setting the pace and forcing everybody to work within that. So I would have to learn to manage the system much differently if I'm gonna optimize learning for every child within