What can Dr. Deming's famous Red Bead Experiment teach us about quality? What happens when you only focus on the bad, and ignore the good? In this episode Bill Bellows and Andrew Stotz discuss acceptability vs desirability in the context of the Red Beads and a few of the 14 Points for Management.

0:00:02.1 Andrew 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 discussions with Bill Bellows who has spent 31 years helping people apply Dr. Deming's ideas to become aware of how their thinking is holding them back from their biggest opportunities. This is episode 5 of the Misunderstanding Quality series and the title is "The Red Bead Experiment." Bill take it away.

0:00:30.4 Bill: Thank you, Andrew, and welcome back. Welcome back to our listeners. One thing I want to say is, one is I listen to every podcast two or three times, listening for, is there a need for clarification, reminding myself, thinking, oh, I should have said this. Or sometimes I say, oh, make sure you make this point, and I do or I don't. And. so one is, nothing comes up from the last one that I thought I missed or mispronounced, but what I do want to clarify is, I'm viewing the target audience as quality professionals in your respective organization or people that want to become a quality professional that are learning, that are trying to apply these ideas in their organization, are fascinated with it. Could be quality professionals who are consultants looking for new awareness of the Deming perspective. So, that's...

0:01:35.8 Bill: And so, some of what I have in mind is, and the examples is, things you can try at home. In fact one thing I encourage... What I encourage my students to do, undergraduate and graduate students, even the clients I consult with, companies I consult with, is develop the ability to explain these ideas, any of them, to people outside of work. So, that could be a spouse, a brother, a sister, a mother, father, son, daughter. And, why outside of work? 'Cause I view that as a safe audience. You say, hey, I just listened to this podcast. Somebody at work may not be as safe. And why are we having this conversation? So, I would say, it could be a college classmate, but one is, try explaining these things to people outside of work and then when whoever that is looks at you and says, I have no idea what you're talking about, or this makes sense, then as you develop that confidence then you're refining your explanations. And that puts you in a better position to apply, to explain it at work.

0:02:54.9 Bill: And why is that important? I'd say there's a lot you can do on your own. I mentioned that a month or so ago, my wife and I were in New England, and I met my doctoral dissertation advisor, who's 86 years old and lives in the middle of nowhere. And one of the things is the wisdom he gave us way back when it was so profound. One of the things he said, we were poor starving college students making seven bucks an hour, working 20 hours during the semester as Research Assistants or 40 hours during the summer. And what a life. Living in... This is poor starving college students. And he would say to us... We'd get together now and then, there'd be a keg on campus and we'd be... Which it wasn't all that often, but anyway, he'd say to us, "These are the best years of your life." [laughter] And we'd look at him like... Now again, I mean, we were... I wouldn't say we were poor starving college students, but I mean, we made ends meet. Now our classmates had gone, undergraduate, gone off to work and they were making real money, and we just stayed in the slum housing and doing... Just living cheap.

0:04:20.3 Bill: Then he says, "These are the best years of your life." We're looking at him like what are you saying? And what he said was, you're working on your research projects either undergrad, masters or PhDs. He said, "You will never have the time you have now to focus on one thing and not be distracted." Now a few of the classmates were married. Most were not married, but he just said this is... I mean, what a dream situation. You're in the laboratory every day. That's all of your focus. Your tuition is covered, blah, blah, blah. But it was just like, yeah, okay. So, when our daughter was in graduate school I shared that with her and she laughed at me. I said, "Allison, these are the best years of your life."

0:05:14.4 AS: If only we listened.

0:05:15.5 Bill: Right. So, that's... And well, I wanted to bring up... But the other thing I want to bring up aside from that story is, he'd say to us, when you go to work, he said trust me. He said "there will be more than enough time to get your job done. You'll have a lot of... You will have time to..." And he said, 'cause he used to brag about he'd be given a task and he can get it done in a fraction of the time that was allocated. And why I mention that is that every job has latitude. And so, to our listeners I would say, think about how to use the latitude you have to practice, to do a small scale Plan-Do-Study-Act thing. Now I really think that's what it's going to come down to is, either experiment at home or whatever, but just practice. And then as Andrew always reminds us at the end of each podcast, you can reach out to me on LinkedIn. And that's led to a number of people I'm meeting with once or twice a month.

0:06:31.8 Bill: And they are exactly who I hope to meet, is young quality professionals wanting to know more, to know more, to know more, and they're either in the States or they're living in Europe. All right. So, before we get into the Red Bead Experiment I wanna go back and talk more about acceptability, desirability which will be a focus of the Red Bead Experiment as well. But in the first series we did, there were 23 episodes before we got into the Misunderstanding Quality, and somewhere in there we discussed, you may recall the paradigms of variation. And the paradigms are labeled letters A, B, C, D and E. And we will look at them in this series. So, for those who don't know what I just said, don't worry we'll cover you. And for those who heard it before, okay, we're going to review it. And I mentioned that because paradigm A, the only one I want to talk about tonight, is paradigm A, is does it meet requirements? That's what acceptability is. Is it good? 'Cause we have this binary world in quality. Part of paradigm A is a binary world. It is good or it's bad. We talked about last time is, if it's bad can we salvage it? Which means we can rework it.

0:07:52.3 Bill: Now some of the rework means it could be we can rework it and use it. And in the aerospace industry what happens is, maybe we can't put it in a flight engine. When I was at Rocketdyne maybe it doesn't end up in a Space Shuttle Main Engine, but maybe it ends up in a test engine and a test stand, so it doesn't fly, but we're still going to use it, or it's scrapped. We have to throw it away. But paradigm A is acceptability. Another thing I want to mention is, I was commenting on LinkedIn the last couple of days over process capability metrics. And there's Cp which stands for capability of the process. And, then there's Cpk which is a little bit different. And I don't want to get into those equations tonight, maybe in a future episode. But what I want to say is, if you're looking at a metric such as yield, people say the yield is 100%. What does that mean? It means everything is good. What if the yield is 50%? That means we have to... 50% is good, 50% is bad.

0:09:06.2 Bill: So, yield is an acceptability metric. Why do I say that? Because the measure is percent good. What is a good versus bad? Also say that indices that involve the requirements. And we've talked in the past about a lower requirement and an upper requirement, the idea because we expect variation we give a min and a max. And so, if the equation for the metric you're using includes the tolerance limits, then that's a clue that that's an acceptability-based metric. Now, I don't care whatever else is in the equation, but if those two numbers are in the equation, then the inference is, what you're talking about is a measure, some type of measure of acceptability.

0:10:00.5 AS: Right.

0:10:02.6 Bill: But even if people talk about... If the metric includes the middle of the requirements, well, as soon as you say middle of the requirements, as soon as you say requirements we're back to acceptability. So, these are things to pay attention to is what we're talking about acceptability and desirability, 'cause what we talked about last time was I was trying to give everyday examples of both. And so, acceptability is when people talk about... In fact I listened to about an hour long podcast today on quality management. And one of the comments was, if you follow the steps correctly you get the right result. Well, that's acceptability. Right? If things are right as opposed to wrong. So, again, when you're in this world of good, bad, right versus wrong, that's acceptability.

0:10:58.7 Bill: Again, the reminder is this is not to say acceptability is bad, but it's not desirability. Which one is it? And then what we talked about in the last podcast number four was choose. Do we wanna to focus on acceptability or do we wanna focus on desirability? Where desirability is saying, of all the things that are acceptable, I want this one. I want that orange. I want that parking spot. I wanna date that person of all the ones that meet requirements in my search... You know, in the dating app. And so, that's acceptability. What got me excited by Deming's work in the early '90s was, I was spending a whole lot of time at Rocketdyne focusing on things that were broken. I'm trying to apply Dr. Taguchi's ideas to go, to take something that used to be good but then slipped into bad, and now we're focusing on the bad stuff to make it good. And now the good news is it kept me busy.

0:12:06.5 Bill: I was having a lot of fun. These are high visibility things and the solutions. We got the solutions working with some really wonderful people. But that led me to start asking questions. And I was once at an all-day meeting in Seattle at Boeing. Rocketdyne had been sold to Boeing Commercial Airplane Company. I got invited to a meeting up there. And it was a monthly all-day production meeting. I don't know 50, 60 people in the room. And they asked me to come up. So, I went up. And what time does the meeting start? You know 8 o'clock, 9 o'clock, whatever. And I said you know put me on a few hours into the meeting. Well, why then? Well, I want to listen to the first couple of hours of the meeting. Because in listening, now we're going back to what we talked about with Edgar Schein. And I've developed the ability... You know, I can hear are we focusing on acceptability, desirability, I can hear things you know with a Deming lens. People think of a lens as seeing, well, there's a Deming ear set as well.

0:13:10.7 Bill: And so, I listened for the first two hours and exactly what I expected. So, when I get up to speak at last I said before I got to the slides, I said, "How much time do you spend every day discussing parts that are good, that arrive on time?" And a couple of people in the front row made a circle with their fingers, zero. And I said, so why is that the case? And one of them says, if it's not broken don't fix it. And wherever I go that's what people say. I went to a big Boeing customer doing... Because they were a customer we sold them rocket engines of some size. And I was briefing that slide, had 110 people in the room for a lunchtime presentation. Before I could read the slide, the room erupted in laughter. And so, I share that because if we're spending all this time focusing on the bad but not the good, what is that? That's acceptability. That's what happens, is the economics of acceptability says, only focus on the bad to make it good. But we don't focus on the good because... And that's what we're gonna look at towards the end of tonight is, why don't we focus on the good? And so, next, I had a co-worker at Rocketdyne got a job in Chicago at a toy factory. They bottled soap bubbles. And as a kid's toy with a little wand inside and blowing bubbles and all that.

0:14:56.0 Bill: And she dramatically turned the place around, did some amazing, amazing work. She went from being the senior manufacturing engineer to the, I think plant manager. So, she called me up as she'd been promoted to plant manager. And the question was now that I'm plant manager what should I focus on? So, I said... I had known her for four or five years at that time. I had been mentoring her and the mentoring continued in that capacity. So, I said well, what do you think you should focus on? And the comment was, I think I should focus on all the things that are broken. Well, that's acceptability once again. And I said, so you're focusing on being 100% reactive. And she said, well, yeah. And I said, what you're doing then by focusing on acceptability, you're saying the things that are good I ship, the things that are bad I got to work on. But without understanding that there's actually variation in good... I mean, go back to the Boeing folks when the guy says to me if it's not broken don't fix it. My response to that was, if you use that thinking to drive your car when would you put gas in it? When it runs out. If you use that thinking relative to your plumbing system, your water system at home when would you call the plumber? When it breaks.

0:16:25.5 Bill: When would you go see the doctor? When... So, the downside of not working on things that are good and not paying attention to things that are good is that they may bite you. So, part of the value proposition of acknowledging from a desirability perspective that there's variation in good. If you pay attention to the variation in good there's two upsides. One is, you can prevent bad from happening if that's all you want to do. And two, the focus of a future episode is by focusing on things that are good and paying attention to desirability in the way that Yoshida, Professor Yoshida was talking about. That offers opportunities to do things that you can't do with an acceptability focus, which is improve how things work together as a system. And the idea being when you move from acceptability which is a part focus to desirability, which is a system focus, you can improve the system. Okay, more to follow on that. All right. So, I got some questions for you Andrew, are you ready?

0:17:37.4 AS: Uh-oh. Uh-oh.

0:17:39.8 Bill: So, Dr. Deming had how many points for management?

0:17:42.9 AS: Fourteen.

0:17:46.3 Bill: All right. Okay.

0:17:48.3 AS: I'm being set up here. I just feel it. You start with the easy ones.

0:17:52.8 Bill: All right. And...

0:17:54.3 AS: Listeners, viewers help me out.

0:17:56.9 Bill: All right. And which point, Andrew, was cease dependence on inspection to achieve quality? What number was that?

0:18:09.6 AS: I'm gonna say four or five, or six. I can't remember.

0:18:14.2 Bill: Three. Three.

0:18:14.6 AS: Really? Three. Okay. That was close.

0:18:16.1 Bill: I would not have known. That was number three.

0:18:19.1 AS: Yeah.

0:18:20.1 Bill: And it's followed by Dr. Deming saying, "Eliminate the need for inspection on a mass basis by building quality to the product." So, the first question is what point was it? And again, I had to look it up. I know it's one of the 14. Second question, Andrew, is, if Dr. Deming is saying cease dependence on inspection to achieve quality, would you think of that as an acceptability focus or a desirability focus?

0:18:55.1 AS: I don't know if I can answer that. I mean, I can only think about what he was saying, which was design quality in from the beginning and get everybody involved in quality, not just having an inspector at the end, but I'm not sure.

0:19:11.4 Bill: Yeah. No. And even as I asked the other question, I'm thinking... Well, this is great because if in the audience you think of quality from an acceptability perspective, right?

0:19:24.2 AS: Mm-hmm.

0:19:24.9 Bill: So, if you're working for Boeing, which is all about acceptability or most companies, and you hear step three, then you're thinking, cease dependence on the inspection to achieve..., you're thinking acceptability. If that's what you're used to, if you're used to quality being doesn't meet requirements...

0:19:42.9 AS: Okay.

0:19:43.2 Bill: Then what you're hearing is Deming talking about acceptability. But if you've been exposed to Yoshida's work and Dr. Taguchi's work and you're understanding that within requirements there's variation of things that are good, so it's kind of a trick question. The idea is it depends. Alright.

0:20:02.4 AS: Yep.

0:20:05.5 Bill: I got two other of 14 points to ask you about. Alright. Which of the 14 points is in the practice of awarding business on the basis of price tag alone? Instead, minimize total cost. So,  first which point is that?

0:20:26.9 AS: I think it was also... I would say then four.

0:20:32.1 Bill: Yes.

[laughter]

0:20:33.6 AS: Yeah.

0:20:34.1 Bill: Yeah.

[laughter]

0:20:34.5 AS: You'd think I know. I wrote a book about it.

[laughter]

0:20:39.3 Bill: Alright. So, that's point four and...

0:20:42.1 AS: Okay. So, I got... I don't wanna be rated and ranked, but I got one right at least. Okay. Let's keep going.

0:20:49.1 Bill: Okay. And, so, is that acceptability or desirability? Let's say this. Is awarding business on price tag acceptability or desirability?

0:21:02.1 AS: Probably acceptability.

0:21:04.6 Bill: Yeah. 'Cause then you're saying...

0:21:06.5 AS: Can you hit this number? It's okay.

0:21:11.2 Bill: Yeah. Or you contact your insurance company and you say, I'm looking for a heart surgeon, and you say, and I found one, blah, blah, blah, blah, blah. And they call you up and say, yes, that person is a heart surgeon, but we prefer you use this one. [chuckle] What's the chance they're thinking about a cheaper option? Right? Alright? So, you're looking at from desirability perspective...

0:21:38.5 AS: This guy's really cheap on kidneys.

0:21:40.7 Bill: Right? And so you're thinking you've done a bunch of references. You've asked your friends. And why are you asking? Because all the doctors out there that meet requirements, you're blindly saying, I'll take any one. That's acceptability. And you're saying, I want this one. That's desirability. But the insurance company says, no. We consider them all to be the same in our policy. That's acceptability. Alright. Okay. And here's the last point we're gonna look at tonight. Which of the 14 points is "improve constantly and forever the system of production and service to improve quality and productivity and thus constantly decrease cost"?

0:22:23.5 AS: Isn't that number one? Constancy of... That's...

0:22:28.0 Bill: That's constancy of purpose. That's number one.

0:22:28.8 AS: Okay. Constancy of purpose. So, improve... Don't know. No. No.

0:22:39.4 Bill: That's number 5.

0:22:40.5 AS: Okay. Five.

0:22:44.5 Bill: And I was looking at, so I know those are three and one, and I thought, oh, that's three, four, and five. Alright. So, what I wanna do there is, we're gonna look at that a little bit later. So, I don't wanna ask you about acceptability, desirability, but I just wanna lay that on on the table. Alright. So, now we're gonna look at what Dr. Deming referred to as his chain reaction. The Deming Chain Reaction. Alright. So, what do you remember about the Deming chain reaction? It wasn't a motorcycle chain or a bicycle chain, right? What did Dr. Deming call his chain reaction?

0:23:31.3 AS: I can't... I mean, I'm thinking of the flowchart.

0:23:34.9 Bill: Yeah. We'll get to that. We'll get to that. The chain reaction...

0:23:36.5 AS: But that I can't remember.

0:23:39.6 Bill: And this is likely Out of the Crisis. The Deming chain reaction is, "if you improve quality, you will reduce scrap and rework, thereby reduce costs." And then he goes on to, by reducing costs, you can increase sales and expand the market. That's the chain reaction.

0:24:01.9 AS: Yeah.

0:24:02.2 Bill: So, when I ask students, again, in my either graduate, undergraduate classes is, talk about the Deming Chain Reaction, then I say, is the Deming Chain Reaction... Within the Deming Chain Reaction, Deming says, if you improve quality, reduce scrap and rework, lower cost, is that explanation of quality, acceptability, or desirability?

0:24:31.9 AS: I don't know. I'm fearful to answer nowadays because I'm not getting these right.

0:24:37.4 Bill: No. You are. You're on a roll. [chuckle] Again, the Deming Chain Reaction, if we improve quality, we reduce scrap and rework, thereby lower the cost thereby sell more and expand the market.

0:24:52.2 AS: I would say that's desirability.

0:24:56.1 Bill: Okay. One more time. If we improve quality, we reduce scrap and rework.

0:25:03.2 AS: Yep.

0:25:04.3 Bill: So, the clue is scrap. Is scrap something we talk about with acceptability or desirability?

0:25:12.1 AS: That's acceptability.

0:25:14.1 Bill: And rework.

0:25:18.2 AS: Well, we're trying to make it acceptable.

0:25:20.1 Bill: Exactly. And the reason I point that out is, I'm not sure... And I think we talked last time about things we agree with Deming or disagree with Deming. I'm not a big fan of the Deming Chain Reaction because I think... Again, if I'm in the audience and I'm working for a company that defines quality and in terms of acceptability, and he says to me, if you improve quality, reduce scrap and rework, that's what I'm used to. And my concern is, in other ways he's explaining quality in terms of constantly improving. Well, how can you constantly improve quality once you get to 100% yield? So. if all the product is good, which is acceptability, if there's no scrap and no rework, can you improve quality? Not if you're focusing on acceptability. And so, what I'm saying there is, that if Dr. Deming is in one hand defining the chain reaction and using the term quality in reference to scrap and rework, then he's projecting quality as acceptability. But if he's talking about improving constantly and forever, and then we get into, can you improve the quality forever? That's what he's saying.

0:26:49.1 Bill: What if you get to 100% yield, which is the maximum value of acceptability? Well, only if you shift to desirability can you improve forever quality, if you think it's worthwhile to do. So, that's why I wanted to go back and look at those things. One is revisit acceptability, desirability, and point out what I think are some opportunities for confusion in trying to explain Deming's work. Alright. Now we'll talk about the Red Bead experiment, which is, the very first time... I remember reading about it in the earliest books I read. I think, who is it that wrote the first books on Deming management, Deming management? She's a...

0:27:42.8 AS: Killian?

0:27:44.3 Bill: No, no, no. Cecilia Killian was Deming's admin.

0:27:48.9 AS: Mary?

0:27:50.5 Bill: Yeah. Mary Walton.

0:27:51.6 AS: Mary Walton.

0:27:52.5 Bill: Mary Walton. I remember reading a Mary Walton's book, that's when I first got exposed to this Red Bead experiment. So, The Deming Institute has a dedicated webpage, so, if you go to deming.org, or just do a Google search for deming.org Red Bead experiment, it's one of the most popular pages. I think that might be the second most popular, most visited page past the 14 Points. In there you can find short videos. There are longer videos, but there's enough on there to follow along with what I want to explain. So, Dr. Deming and the Red Bead experiment would take from the audience, and it could be four willing workers, six willing workers. He'd be the manager of the White Bead Company, and he would explain to them, he would share with them. He had a bowl, and in the bowl were 5,000 beads, maybe an eighth of an inch in diameter, small plastic beads, and there'd be 5,000 in the bowl, 4,000 white, 1,000 red.

0:29:00.6 Bill: And then there was a paddle, and the paddle could be roughly two inches by four inches, and the paddle had a little handle, and it had holes in it. So, the instructions he would provide to the willing workers, the production workers, is to take this paddle at a given angle, slide it in flat into the bowl, even the back of the beads. The beads are in one container, they get poured into another container.

0:29:27.7 AS: In a pan.

0:29:28.1 Bill: It's a mixing process, and then he pours them back in. So, just pour them from one to the other, and he would be very persnickety on pour at 45 degrees, tip from the corner. You pour back and forth, put the paddle in, and you'd end up with 50 of the beads would fill the paddle, and then you'd go to the inspector number one. And the inspector number one would count how many red beads, which is not what the customer wants. What the customer wants is white beads, but the raw material includes both. So, you go to inspector one, and they may count five beads. You go to inspector number two, and they quietly see five. The numbers get written down. Ideally, they're the same. And then you go to the, I think, the master inspector, and they say, five beads, and then "dismissed." And then write the five on a flip chart, and then the next person comes and does it, and the next person comes and does it. So, all six come up and draw beads, and then we count the number of red ones. The number of red ones go into this big table. Next thing you know we've done this over four different days. I've done this. This could take an hour. And even when you watch the videos, there's a fast forwarding.

0:31:00.1 Bill: I've done the Red Bead experiment, I think, just once, and I did it with a former student, which worked out really well, 'cause there was a lot of dead time, and the audience was watching, and so I was able to get conversation going with her. So, for those wanting to do this, boy, you've got to be pretty good on your feet to keep the audience entertained. To get to the point where you've got a table on the whiteboard, or on the flip chart, and on the table are the six willing workers on the left-hand side, and then day by day the red beads... Looking at the number of red beads. So, what are the red beads? Well, the red beads are not what the customer wants. What the customer wants are white beads, but in the production process, because the raw material includes red, well, then the red ends up in the output. So, I ask people, so, if the white beads are what the customer wants, what are the red beads? And typically, people say those are the defective, defects, scrap.

0:32:03.2 Bill: And, so now you get into this model is based on acceptability. The beads are either good, white, or bad, red. And so I would ask the students in class, in a work setting, what might the red beads be? I, in fact, asked our daughter. She said, is just moving from being a junior high school English teacher to a senior high school English teacher. Her undergraduate degree is from Cal State Long Beach.

0:32:34.3 AS: There you go.

0:32:34.3 Bill: So, her first day of school was today. She's also the varsity swim coach, which is way, way cool. Mom and dad are proud of her. So, I remember asking her a few years ago. So, I said, Allison, what are the red beads in the classroom? She said, well, the stapler doesn't work. The door doesn't close. The projector screen doesn't come down. The computer doesn't work. These are red beads in the classroom. So, I said, okay, Allison. What are the white beads?

0:33:01.1 Bill: Geez. So, we get so used to talking about the red beads are the defects or things that... Well, the white beads, by comparison, are the things that are good. So, I said, Allison, if the computer works, that's a white bead. If the door closes, that's a white bead. If you can close the window, that's a white bead. If you can pull down the screen, that's a white bead. So, the red beads are the things around us that are defects, broken, and the white beads are the others. And so, I wanna throw that out to do some stage setting. And ideally, this is a review for our listeners, and if not, you've gotta go watch as many videos as you can in The Deming Institute website. There's a lot of great content there. Watching Dr. Deming do this is pretty cool.

0:33:49.0 AS: He's a funny guy.

0:33:51.6 Bill: And I was very fortunate to be in Dr. Deming's very last four-day seminar. I did not participate in The Red Bead Experiment. I let somebody else do that, but it was classic. Well, the next thing I wanna get into is, and I would say to audiences many times, so we know... Well, a couple things. It's so easy to look at that data on a spreadsheet and say, Jill's the best performer. She has the minimum number of red beads. So, on the one hand, we can look day by day, and it could be Jill's number started off low. And we gave her an award, and then it went high, and then we started blaming her. So, there's variation in the number of beads, worker to worker and day to day. So, a given worker, their scores go up and down. So, that's called variation.

0:34:43.4 Bill: And so one of the aspects of the System of Profound Knowledge, which we haven't talked about too much, but ideally our listeners know Dr. Deming was really big about the value proposition of understanding variation. So, what Dr. Deming would talk about in his four-day seminars, and ideally anybody presenting this, is you take the data, you draw the usual conclusions. We're looking at data from an acceptability perspective. We look at the spreadsheet, and then voila, we turn it into a run chart and look at that data over time, calculate control limits, and then find that all the data is within the control limits and draw the conclusion that the process is in control. And then you move from in a non-Deming environment, looking at this data point versus this data point and drawing these conclusions that the white... The number of red beads is due to the workers.

0:35:33.7 Bill: So, the punch lines you'll find at Deming Institute webpage is that the workers are trying as best they can, that the red beads are caused not by the workers taken separately, but by the system, which includes the workers. A lot of great learning there. And a very significant piece is, in a Deming environment, where Deming's coming from is, again, this is before we go further in this in future sessions is, he's proposing that the majority of what goes on in the system relative to the performance of anything you measure is coming from the system. And if that is really, really understood, then you're hard pressed to blame people in sales for lousy sales or dips in sales or you look at grades of students in a classroom. So, for people looking at Dr. Deming's ideas, perhaps for the first time, realize that what he's talking about is coming from The Red Bead Experiment is a great eye opener for this is that, let's stop blaming the workers for the production issues and step back and look at our procurement system.

0:36:39.6 Bill: Do we have a procurement system where we're buying on price tag? If you buy on price tag, you end up with buying a lot of red beads. So, one aspect I wanna leave our listeners with today is, as you're studying this, realize there's a psychology aspect to The Red Bead Experiment. Not only the idea that there's variation up and down, but what are the implications of realizing that we can't be blaming the workers for the behavior of the system. The system includes the workers, but it also includes things that are well beyond their control. Well, where I wanna go next with this and then we'll next time get in and go further is, in appreciation of point five, "improve constantly forever the system," what I would ask audience is, so we know the red beads are caused by the system. We know the number of white beads goes up and down. But if we were to improve the system by not buying red beads or pre-sorting them out and get fewer and fewer red beads in there, then we get to the point that all the beads are white, perhaps. We have continuous improvement.

0:37:47.2 Bill: We end up with a 100% yield. Well, then we get into, again, and I've kind of set the stage in prior comments, what I would ask people is, what Dr. Deming's talking about trying to achieve zero red beads everywhere in the organization? Is that what we're striving for with the Deming philosophy, is to go around the organization, I want every single process to produce no red beads to make it to a 100% white beads? And if that's what Dr. Deming is talking about, then what does point five mean about continuously improving? Now we get into what I mentioned earlier is, you can improve the speed of operation to produce more white beads, so, we can do them faster, we can do them cheaper, but can we improve the quality of the white beads under that model? And the answer is no, because acceptability stops at a 100%. So, what we'll look at next time is, if you look at the beads and look closely, you'll see they have different diameters, different weights. They're not exactly the same color white. So, what is that Andrew? That's called variation.

0:39:00.9 Bill: And now it brings us back to desirability. So, what I encourage people to do, most of the times I see people presenting The Red Bead Experiment, they present it from an acceptability perspective. That's the starting point. But what I encourage our listeners to do is go through all that, and this becomes a great opportunity to move your audiences from acceptability focus to desirability by talking about the inherent variation in those beads. Again, we'll talk about the value proposition economically in future sessions, as well as the other paradigms of variation before we get there. So, that's what I wanna cover.

0:39:43.2 AS: Wow. Bill, on behalf of everyone at The Deming Institute, I wanna thank you again for this discussion. And for listeners, remember to go to deming.org to continue your journey. If you wanna keep in touch with Bill, just find him on LinkedIn, and this is your host, Andrew Stotz, and I'll leave you with one of my favorite quotes from Dr. Deming. It never gets old. "People are entitled to joy in work."

In this episode, John Dues and Andrew Stotz discuss the first part of John's path for improvement model - setting the challenge. Using an example from United Schools Network, John explains their aspirations for cutting chronic absenteeism rates.

TRANSCRIPT

0:00:02.4 Andrew 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 John Dues, who is part of the new generation of educators striving to apply Dr. Deming's principles to unleash student joy in learning. And the topic for today is "set the challenge." John, take it away.

0:00:24.6 John Dues: It's good to be back, Andrew. Yeah. Last episode, we kicked off this new series. I introduced this improvement model that we can use to help us set ambitious goals backed with a sound methodology. I think I made this disclaimer last time. I'll make it again that this is sort of like showing listeners a peek behind the curtain because we're sort of talking about this as this model is being built and used for the first time in my network of schools here in Columbus in United Schools. So I think that caveat's important, and I think maybe starting with just a quick review of the model we looked at last time would be a good refresher for this episode for those that are reviewing and I'll talk through it for those that are only listening. I'll go ahead and share my screen quick. You see that all right?

0:01:17.1 AS: Yep.

0:01:18.4 JD: All right. Yeah, so this is the model we kind of stepped through kind of an overview last time. I think it's important to remember a few things. One, basically the core idea of the improvement model is it gives us the scientific way of thinking so that we can work in a way that makes sense to close the gap between our sort of current conditions in our organization and sort of our aspirations. So we frame those two things as the voice of the process, as current conditions, what's happening right now. And then the future aspirations, that's the voice of the customer. That's sort of what we or someone else wants those conditions to be. And what we're doing throughout this process is stepping through the four steps that you can see displayed in the model. So kind of just stepping through those quick.

0:02:06.5 JD: The first thing is that we set the challenge or the direction, and that's gonna be... We're gonna dive deeper into that step today. Then the second step over on the left hand side of the model, for those that are viewing, you work to grasp the current condition, so what's going on currently in your organization. And then the third step is we establish the next target condition. So think of that as like the intermediate goal that we're working towards sort of on a more proximate timeline. And then fourth, what we're doing is once we understand those things, then we're experimenting to overcome obstacles or impediments. And so all of those things we talked about, doing that with a team that includes someone or people working in the system, in our case students, a lot of the time, those with the authority to work on the system like the teacher in a classroom or the principal of the school building. And then that System of Profound Knowledge coach that has that awareness of the System of Profound Knowledge and sort of brings that lens to the improvement efforts. So that's sort of a quick rehash of the model that we went over in episode one. And then I'll stop. Well, you want me to leave that up or I can stop sharing?

0:03:29.9 AS: Either way. I don't mind.

0:03:31.0 JD: Okay. Well I'll stop sharing for now and then we can always pull it back up if we want to. Yeah. So with that sort of in mind, what I thought would be helpful is then do this deep dive into step one. And so kind of what we'll do through the next several episodes is focus on each of the steps. So we'll take this deeper dive into step one. Set the challenge or direction. So last time I mentioned that in step one of the model we asked this primary question, where do we want to be in the long run? And this is... Think about this as a overall challenge or direction that's set by organizational leadership typically. So senior leaders, the CEO, typically the board, they're gonna be the ones framing this challenge, setting the direction for the organization.

0:04:27.2 JD: And we can also think about it as a sort of a longer range goal that if we accomplish it, it will differentiate us in our case from other schools or if you're in the business community, it would differentiate you from competitors in some way. But even though it's something that we're striving toward currently we're setting this in a way that it's gonna stretch us and right now it almost seems impossible to accomplish this thing far out into the future. And this direction or challenge, I think it's fairly typical. Sort of set this on a six month to three year timeframe. So that kind of gives you a sense of sort of how far out we're looking and the timeframe we're looking to sort of achieve this challenge is. And last time I shared an example from our most recent strategic planning where we're trying to reduce our chronic absenteeism from the current state, which is 52% chronic absenteeism. We're trying to take that down to something closer to 5% chronic absenteeism.

0:05:44.4 AS: Seems nearly impossible.

0:05:44.5 JD: It does if you're on the ground in schools right now, especially schools like ours, it really does seem nearly impossible to sort of cut it at that large of a rate. So.

0:05:55.6 AS: I have an ethics class that I teach here, an ethics and finance class here in Bangkok. And I tell the students it's not mandatory to attend class from my perspective. School may require you, but it doesn't matter to me. My job is to make it so exciting and interesting that you wanna be here. That's hard.

0:06:16.7 JD: Yeah. That's a good frame. That's a really good frame. We have, unfortunately we have so many obstacles that our kids are going through to get to school. Even something as simple as consistent transportation from yellow school buses is a major impediment to school attendance here in Columbus. So there's all kinds of obstacles that... Challenges in front of us that we're gonna have to improve and solve to get down to that 5% rate.

0:06:43.0 AS: When I was growing up in Ohio, in Hudson, outside of Cleveland, the farm that I worked on in the summer, Barlow's farm. Mr. Barlow was our bus driver because there wasn't much going on in the wintertime. And so, yeah, he never missed [laughter] I don't ever remember a bus not arriving in my whole youth.

0:07:07.6 JD: Yeah, yeah. It's something in many places you take for granted. And then in a number of other places, it is a major, major challenge for sure.

0:07:13.0 AS: Interesting.

0:07:14.8 JD: That's certainly the case in Columbus where we are, for sure. So when we think about this challenge it's this... I kind of think about it and this is why it needs to a lot of times be set at the leadership level or the senior leader level is it's this new future condition and it serves as a sort of compass for us to follow. And that's important 'cause we don't have an exact roadmap for how to get there. So it's sort of like a general direction, but the specifics are what we're gonna have to be filling in as we go through some of those other steps. Some of those intermediate goal setting, some of the experimentation that I talked about. But think about this direction or challenge is it's really the purpose behind our efforts. And then when you sort of put together the tough challenge and then the scientific thinking, that's really powerful. And those two things together can really sort of move you into this new territory. I think that you're looking to... I think this map territory compass metaphor is really sort of spot on for this particular model. Oh, go ahead.

0:08:29.8 AS: I had a question because I have a client of mine and one of their objectives is to list their company on the stock market here in Thailand. Like many companies, but in some ways that's kind of an owner's goal. Like we've talked about some of their other goals, like being the leading company in their field in asia, Southeast Asia or something like that, and/or maybe to have a happy workforce or whatever. And I'm just curious, like how do people think about goals? What is a good way to think about it? Is there such a thing as like an internal or a higher level goal versus a goal for the company versus an external goal? How do you guys think about those types of things and target conditions?

0:09:17.2 JD: Yeah, I mean, I think... I don't know the exact answer. I mean, I think when you set a goal at the leadership level, then you're gonna... Well, one, you're gonna have to explain it throughout the organization, whether it's a 100 people or a 1000 people or 10,000 people. And then depending on the size, there's probably gonna be different types of goals that are in different business units, I'm guessing by business type. We're a pretty small organization and so we're pretty close to the... In fact, our office... My office, it is on the ground floor of one of our middle schools, so we're very proximate compared to like a bigger company. So I think this can look different in different places. I think the consistent thing is it's gotta be clear, it's gotta be spelled out, it's gotta be clearly communicated. It has to be something that you're talking about frequently. Otherwise you're obviously not gonna move in this direction.

0:10:11.2 AS: Yeah, I mean, that kind of answers it too. 'cause I thought... When you said that, I also thought about how people care about with them, what's in it for me. And so, as you said, you gotta explain it and you're gonna have to do a lot of talking about it. So people need to see that that goal is something that's gonna bring them value, otherwise they're not gonna be excited to go do the hard work that it takes to get there.

0:10:37.0 JD: Yeah. Maybe in that respect, like sometimes in education is... Some of the goals that we have set are so self apparent that there's just sort of immediate buy-in 'cause like who's against kids coming to school? Almost nobody. So that's I think a fairly easy one to get buy in. And maybe in other settings more time needs to be spent on the buy-in part, the explanation part. Maybe... This can be kind of hard, but who's involved in setting the goals in the first place? Maybe there's ways to get more people involved in that process.

0:11:10.6 AS: Well, and maybe the kids aren't involved in the buy-in.

0:11:13.8 JD: Yeah, that's true. That's true. Although, yeah, like the yellow bus thing that's out of their control. And I'd say that's actually a major obstacle. But I think...

0:11:26.5 AS: That's true. Nowadays, I'm sure there's plenty of kids that wanna be there.

0:11:29.5 JD: Oh yes for sure.

0:11:30.9 AS: But there's obstacles all over the place for them.

0:11:34.3 JD: The vast majority wanna be there, actually, I think. But your point is good, and that goes back to that team they're the ones working in the system and so they're gonna be the best at identifying the obstacles. So to stay in our setting, they certainly need to be a part of the experimentation that happens to improve the chronic absenteeism rate. One other important caveat to point out at this step in the process, and we've talked about this a little bit but I got this little chart that I think will help sort of explain when we were setting this direction or challenge, it's what I would call like an improvement goal. And it's not an accountability goal. And I think it's really important to be explicit about the difference between those two things.

0:12:24.4 JD: 'cause they often get conflated. And so I had built this chart for another improvement project, but I think it does a really good job. So I'll share my screen again. I think it does a really good job of sort of outlining the difference. And it's not that one is necessarily better than the other, it is just really important to know what's the purpose of this particular type of goal and what's it used for. And so I was just gonna take a moment to kind of run through this. So on the left you have sort of some key questions that are answered either by... And here it says measurement for accountability, but you can sort of replace that with an accountability goal and improvement goal over there on the right. So you have measurement for accountability or accountability goal, and then improvement goals or measurements for improvement.

0:13:20.7 JD: And you have some questions that that particular type of goal or measure will answer. Then you have in the next row their specific uses. And then why quality measurement matters. So just starting with accountability goals or measurement for accountability what those types of goals are gonna do is answer questions about merit or status or accomplishment of someone or something. Who's performing well, who isn't, who should be considered knowledgeable enough to do X. We're talking about end of line outcomes, like end of year outcomes. They're often... Goals for accountability often happen once a year. So I've talked about this repeatedly, but state tests would be a very good example of an accountability goal. The point of doing that is to separate the good from the bad basically, when you look at state test. Down there in the use sell for those that are viewing, it says the purpose of, or the use for accountability goals is to determine the applications of rewards or sanctions. Right? And so it's none of this really has to do with improvement.

0:14:38.8 AS: Sanctions, what a word, [laughter]

0:14:40.4 JD: Sanctions, right? Yeah. I mean, this happens in schools all the time. Schools can be sanctioned depending on what the law is at the time as it relates to state testing and accountability system.

0:14:50.9 AS: I thought we only sanctioned Russia [laughter] Okay. So there's even sanctions in schools. Okay, got it.

0:14:58.0 JD: Definitely sanctions in schools. And then we can juxtapose the accountability measures with the improvement measures over there on the right or improvement goals. When we're talking about improvement goals or setting the challenge, we're really talking about questions about specific changes as potential improvements to systems like our systems. So we're thinking about questions like, are the changes I'm making leading to improvement? How are my changes affecting other parts of my system? And what's measured is outcomes and processes relevant to the object of change. You know and how often are we doing this? Frequently. Much more than once a year, like the state test. And the whole point is to learn our way to a better system, right. And so with chronic absenteeism this could be both a measure for accountability and a measure for improvement, depending on how it's framed.

0:15:57.8 JD: Chronic absenteeism is actually reported on state report cards, but in this case, I'm talking about an internally created goal that we have for ourself that we've created for ourself that our organization is gonna work towards. And there's gonna be various things that we do to see if things that we're trying as interventions, experiments work in improving those rates, basically. So I think it's really important to call this out that when we are talking about this particular improvement model and the four steps, we are not talking about accountability goals at all. We're talking about improvement goals, two very different things.

0:16:37.6 AS: Interesting. And the improvement goals is the type of thing that it seems like is not as common as the accountability. Like everybody's trying to, you do this, you've gotta achieve this, that type of thing. Whereas this is such a bigger picture.

0:16:51.3 JD: Yeah. I mean, I think the key difference is because you could actually have an internal accountability goal. You could set up a similar system internally as what the state does when they're looking at schools. And if our mindset was, we're gonna set this goal and you people over here go do this, figure out how to do it, that would be much more like an accountability goal. But our mindset is like hey, this is something we all gotta take a look at. This has to get better. This isn't working for kids, so what are we gonna do? How are we gonna figure this out? That's really the key difference, you know? You're not doing this for some other group of people. You're a part of that group that's trying to make this thing better.

0:17:36.5 AS: So I'm just curious too, as I think about the listener or the viewer out here is how do they get started in this concept of setting the challenge or direction and maybe there's people at the top of the company. I mean, the first thing that I thought when you started talking about it is Oh, there's so many target conditions, there's so many challenges. Like there should be this one and that one. And all of a sudden I started coming up with like three to five challenges. And then I thought, oh no. Now this is overwhelming.

0:18:11.8 JD: Yeah. So in our strategic plan, we have 13 of these key metrics. And each of one of those could be its own challenge or direction, but they are divided up sort of roughly in like different department areas. And so some of 'em have to do with our fiscal responsibility raising funds and stuff like that. And there's a specific team that does that. And that would be different from like an academic team or a school-based team that was working on something like chronic absenteeism. So there is sort of a divide and conquer. The CEO maybe our superintendent are focused on all 13, but there are different teams that are actually running the experiments and working towards improving these things. And then there's someone like me that's sort of serving as the System of Profound Knowledge coach across multiple teams that are working on each of these key metrics basically. But in terms of where to start, I think that's a good segue. I mean, I think we've answered the question or we've said that basically that this strategic challenge answers the question, where's our organization going next? And I think one good... One simple way to start is to think of completing this sentence: Wouldn't it be great if we could dot, dot, dot.

0:19:37.0 JD: What is that thing or what are those things in your organization? It's, again, going back to it seeming nearly impossible, it's something we can't achieve with our current systems and processes. It's not easy, but not impossible. We think it's achievable even if we're not quite sure how we're gonna get there. It's something that's gonna be measurable. So we know if and when we get there. And another thing is that, especially when you're talking about, you were talking about like communication of these challenges across the organization, these challenges or directions are often expressed as some type of catchy statement. So just a quick statement that brings to mind this entire sort of area of work. And so I was kind of brainstorming because we've been talking about this chronic absenteeism example and I think we can just kind of keep that going throughout these episodes. So I was thinking of something like, every student every day, and then everybody knows that we think it's important for every student to be at school every day. And we're sort of working to get back to that post pandemic.

0:20:52.3 AS: Yeah. I was thinking, wouldn't it be great if every parent was fired up.

0:21:00.1 JD: Yes, absolutely.

0:21:01.2 AS: About every student every day. Like, that's the way I was just thinking about it 'cause I think that, and I just like the kids. I'm sure there's plenty of parents that say, I want my kids to get a good education and I want them to get more than what I got, but I can't reach it or I can't do it. I got too much on my plate. But if somehow they were a party to this.

0:21:26.1 JD: Yep. I think, similar to the students, I mean, I think parents absolutely can be a part of an effort where you work. And in fact almost have to be, especially 'cause we're a K-8 system and certainly at the very least at the K-5 level, kids are almost entirely dependent in most cases on parents getting them to school. So, certainly parents...

0:21:49.2 AS: What is the catchment area of your schools? Like what's the farthest?

0:21:57.8 JD: Yeah, we have pretty, because we don't have a specific geographic assigned area assigned to our school buildings, like a traditional public school district would typically. So we have much wider areas. So let's say, a 15 mile radius around a building would catch the vast majority of the kids that attend. So, yeah. Yep. Well, I think, let's look at an example. Let's look at chronic absenteeism as our focus here. So, I've mentioned, we've just updated our strategic plan it includes these 13 metrics, and there's this one focused on chronic absenteeism. And when we sort of outline the key metrics in the strategic plan, each metric has four pieces of information that we're listing explicitly right in the strategic plan. The voice of the process, the voice of the customer, the operational definition, and then some type of visualization of the data, basically.

0:23:04.4 JD: So those four things go with each of the metrics. So just as a refresher, a lot of people know this, and we've talked about this, but I think it's good to refresh. The voice of the process is the metric that tells us how we're currently performing. The voice of the customer is the direction or challenge we have set, so that's the step one. The operational definition for the metric puts communicable meaning into the concept and includes a method of measurement or test, as well as a set of criteria for judgment. So basically we wanna make it clear to anybody that's looking at chronic absenteeism, that they know exactly what it is we're measuring, and they could come up with that same measurement independently. And then the fourth thing is this visualization that illustrates the performance of the metric over time, because that time factor is really, really important. So I'll share my screen one last time so that people that are viewing this can see what this actually looks like in our strategic plan.

0:24:07.4 JD: And I'll kind of walk people through this visualization for those that are just listening. So you sort of see this chart over on the left or on top of the chart it says key metric three student success, chronic absenteeism rate. So that's the metric. The voice of the process is 52%. So that means that 52% of our kids are chronically absent and the voice of the customer is 5%. So that's that far off thing. That's six months or probably more like three years off that we're working towards. And we're not quite sure how we're gonna get there right now. And then we have the operational definition of the concept of chronic absenteeism. So this says "a student is considered chronically absent if they miss at least 10% of instructional time for any reason. Our chronic absenteeism rate is the percentage of students at United Schools who are considered chronically absent."

0:25:08.9 JD: Now, this particular definition was fairly simple because there's already a sort of a federal and state definition of chronic absenteeism. And then down below the operational definition, you have the data that we have thus far charted over time. So in this case, we only have three years of this particular type of data 'cause that's when it sort of started getting measured at the state level. And so the y axis is the chronic absenteeism rate, the x axis is the school year. So this chart has 2021/2022, 2022/2023, and 2023/2024 school year data. And you can see the data is fairly similar across those three years. Not too unexpected, but it's right around, 53%, 54% in the '21/'22 school year, maybe 52% in the '22/'23 school year. And then slightly less than 50%, let's say 48% of kids were chronically absent.

0:26:11.5 AS: Just outta curiosity, where was that before covid? Let's say 2018/2019.

0:26:17.9 JD: Yeah. Lower. Definitely lower. I think going back historically, if we had that data, I would guess, and I'm sort of guessing based on overall attendance rates compared to what overall attendance rates are and like what chronic absenteeism probably was, it was down probably closer to like high 20s, low 30s, that type of thing. And obviously a chronic absenteeism rate of 52% is very high. But when you look at even the school district buildings that are sort of around these schools, generally speaking, their chronic absenteeism rates are even higher. They're in the 60, even into the 70% range. And so not that this is like a comparison, but you can kind of get some context there that these rates are even higher in the neighborhood schools that are closest to our campuses.

0:27:16.7 AS: It would be a bit shocking for someone in Asia, like myself in Korea, Japan, China, Thailand, who's, it's a much different view of education. But just for the purposes, for someone who doesn't know much about what's happening in the US, what are these kids doing? Are they out working or are they at home?

0:27:40.6 JD: It's hard to know exactly. I think one thing is, is that in some cases, older siblings, like in our middle schools, are often taking care of younger siblings for various reasons. I think that can be a common way, but I think it's hard to just pin on one or two things. I think this is a very complex problem with lots of causal things, causal variables that are going into this. So I think that's why it's so important to study it in our context and try to figure out besides the things that we already know, like busing being inconsistent, those types of things. What else is it that's contributing to this? And so that's sort of what the process that we're starting now is trying to figure this out.

0:28:32.3 AS: And would you equate the voice, is voice of the customer equate it to target condition? Or is there a difference between that?

0:28:42.1 JD: Well, in this case, the way I'm framing it is like the voice of the customer is that direction or challenge, that's step one. So we had to, because this is an internal improvement goal, we decided for ourselves, like what do we think that vision, that purpose, that challenge is out there on the horizon that we're not sure how to get to, but we want to get to in the next two or three years. So I would equate those two things in this case.

0:29:07.1 AS: And who is the customer in the case of a school, how would you view that?

0:29:15.0 JD: Well, so that can be a little tricky based on how you're asking the question. Just from the point of who's the customer and the voice of the customer. Well, it's the leadership that set this like a customer with a capital C, that's the voice of the customer in terms of who's the customer of the school system it depends on exactly what aspect of the school system that you're talking about. But in general, our families and our students, are customers of the school system. But then so are the high schools that we feed our eighth graders into. Those are also customers of the system. But in terms of who the customer was that set this challenger direction, that was our senior sort of leadership team.

0:30:00.7 AS: Okay. And the voice of the process where we're looking at the 52% absenteeism rate, would you call that the current condition?

0:30:11.5 JD: Yes. Yes.

0:30:14.0 AS: So voice of the process, current condition, then you have to have some operational definitions so that we know what we're really talking about. And then a visualization that helps people see kind of where things are at.

0:30:28.3 JD: Yeah. And ideally we would have more data than this, but this is the data that we have. And you can actually see there's this note here 'cause right now it's just a run chart. It's just the data points with a central line running through. But there's this note that says the natural process limits are not included until we have at least five data points. And so we won't include the control limits until we have more data, basically.

0:30:50.4 AS: And for the person looking at this from outside, they're like, so wait a minute. You gotta wait a full year before you get that. But I guess there's a lot of data underneath this that is input data that will eventually drive this output.

0:31:07.8 JD: Yeah, I mean, I think what we do with any data like this that comes once a year, you have to find some proxies. So some proxy outcome data that maybe you're measuring on a every other week or maybe on a monthly basis. And then you have some process data that you're measuring, here's the things that we think will move the outcome needle, and are we doing those things? So you set up different types of measures, sort of intermediate outcome measures, process measures that are sort of measuring the different things that you're trying. And then usually a sort of a third component to that measurement system is a balancing measure where you're making sure that other things in your system aren't, [laughter] going astray because you're putting all your focus on this chronic absenteeism concept. So it's complicated. It can be complicated.

0:31:54.2 AS: It is. And in the area of education, you're under so many different constraints set by government. I was having fun in my mind imagining like when we were young, the Keystone cops, and they were kind of funny, crazy cops. But I was imagining getting an old ambulance with a flashing light and arriving at student's homes and saying, we gotta get you to school urgently. [laughter] And all the fun things that you probably can't do.

0:32:27.4 JD: Yeah. Yeah. Well, that as a brainstorm is not too far off from some of the things that we're thinking about as possibilities in terms of different forms of transportation, taking more control over the transportation where we can 'cause this is a service that's provided by the school district.

0:32:51.0 AS: One thing I did with Google Maps many years ago is I uploaded the zip code or address of my students, and so that I could see clusters of where they were. And then from those clusters, I started recommending, Hey, why don't the five of you guys form a group here and you're in the same area? And then that would help them to make a connection that they may not have made themselves.

0:33:24.9 JD: Yeah, that's a great idea. We have the geo mapping already. Yeah. We.

0:33:29.1 AS: And there's pods basically. So pods are out there of 50 students in this area. So when one has a problem you've got 20 of them that got a problem. If a bus doesn't arrive, is there a way we can get those 20 students communicating with each other and say, we want to get to school, how do we do?

0:33:50.0 JD: Yeah. We said we have some beginning of the year challenges right now with busing and we were making some calls to some of the families, and one really awesome grandma actually said, I'm gonna look into how much it costs to rent a bus and I'm gonna go round. And so that type of problem solving is certainly happening on the ground. It's how to sort of make that systematic and consistent. That's the tougher thing.

0:34:12.5 AS: Yeah. Exciting. Great one, and I look forward to the next one. I'm learning a lot and I know the listeners and viewers are learning a lot. Is there anything you would just add to wrap this one up?

0:34:25.6 JD: Yeah, I mean, I just a couple points maybe to bring it home on set the challenge, I think, one thing is we have to have this model to bridge a gap between current conditions and future aspirations. So that's this improvement model as a whole. There's always gonna be this gap between current conditions and our aspirations. And I mentioned this improvement model has this combination of scientific way of thinking and working to close the gap. And what we did in step one was ask where do we want to be in the long run? And this overall challenge that we set is really set at the sort of senior leader level, becomes a key priority. And I'm really thinking about this. If we can figure this out and some of the other key metrics, it's gonna really differentiate us from other schools. And so I think that's sort of those four or five things are the key frames for "set the challenge."

0:35:19.9 AS: Exciting. Well, I'm looking forward to the next one. Well, on behalf of everyone at the Deming Institute, I want to thank you again for this fun and interesting discussion and really opening up what you guys are doing there and the challenges that you're facing makes it even more real for the listeners and the viewers, and for the listeners and viewers, remember to go to deming.org to continue your journey. You can find John's book Win-Win W. Edwards Deming, the System of Profound Knowledge and the Science of Improving Schools on amazon.com. This is your host, Andrew Stotz, and I'm gonna leave you with one of my favorite quotes from Dr. Deming. People are entitled to joy in wo

Continuing their discussion from part 3 of this series, Bill Bellows and Andrew Stotz talk more about acceptability versus desirability. In this episode, the discussion focuses on how you might choose between the two.

TRANSCRIPT

0:00:00.0 Andrew 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 Bill Bellows, who has spent 31 years helping people apply Dr. Deming's ideas to become aware of how their thinking is holding them back from their biggest opportunities. Today is Episode 4 of the Misunderstanding Quality Series, and the title is Quality, Mind the Choices. Bill, take it away.

0:00:31.3 Bill Bellows: All right, Andrew, welcome. So podcast three, I think the title was Acceptability and Desirability. And one correction there, when I went back and looked at the transcript the concept of... At least the first person I heard tie together acceptability, desirability, at least in the Deming community, was a professor, Yoshida, Y-O-S-H-I-D-A. He was a PhD student of Dr. Deming, I believe at NYU but I mispronounced or misspelled his first name. I thought I've heard people refer to him as Kauro, perhaps spelled K-A-U-R-O, maybe that's his nickname, and maybe I just didn't remember properly but his proper first name is Kosaku, K-O-S-A-K-U and he at one point in time was in Greater Los Angeles at Cal State Dominguez Hills. And then I think sometime in the mid '90s, early '90s, last I heard he moved to Japan.

0:01:51.1 BB: I've never met him. I've watched videos of him, there's a classic presentation. I don't know if it's got, it might be online someplace of he did a guest lecture. There was a... Dr. Deming was speaking in Southern California and needed an emergency surgery, had a pacemaker put in, so this would've been '92 timeframe. And Professor Yoshida was called in to give a guest lecture. And that ended up being something that I think was sold eventually. The video, the lecture was sold by Claire Crawford Mason and so he is... I don't know how much of that is online, but anyways.

0:02:38.4 AS: Is Kauro, Kauro wasn't that the name of Kauro Ishikawa?

0:02:43.7 BB: That may be where I... Yes that was a Kauro. There's two Ishikawas. There's a father and the son and I... So I'm not sure if Kauro was the father or the son, but anyway correction there. In the first series we did, going back to '23, 2023, I mentioned the name Edgar Schein, but I don't believe I've mentioned his name in this series. So I wanted to throw that, introduce that in this series today and give some background on him for those who have not heard his name or not aware, did not listen to the first series and Edgar Schein, who passed away January of this year. He was an organizational theorist, organizational psychologist, spent the greater part of his career at MIT. And one of the concepts I really like about what he talked about is looking at an organization in terms of its artifacts. So if you walk around an organization, what do you see? What are the artifacts? That could be the colors, it could be the artwork on the wall, but the physical aspect of the organization Schein referred to as the artifacts. And what he also talked about is if you dig beneath the artifacts, they come from a set of beliefs, and then the beliefs come from a set of values.

0:04:23.9 BB: And again, the first series we did, I talked about Red Pen and Blue Pen Companies, and Me and We Organizations, and Last Straw and All Straw organizations. And those titles should make it easy for our listeners who are not aware to go back and find those. And what I talked about is, this imaginary trip report, if you visited a Deming organization, if we could think in terms of two simple organizations, a Deming organization, and a non-Deming organization in this very simple black and white model. And I had people think about the physical aspects of both, if they were to go visit both. What I then followed up on in our conversation is what you see physically comes from a set of beliefs. Now, they may not be articulated beliefs, what Schein would call espoused beliefs. And then you have what they really believe and I forget the term, I use this for that, but it comes from a set... But anyway, the physical comes from the beliefs, the beliefs come from the values.

0:05:39.0 BB: And part of the reason I bring that up for our listeners, and I'm thinking in terms of the people that have a responsibility in their respective organizations. They could be consultants, internal consultants, working in quality likely, given the focus of this series. First of all, you have to start where you are. But even added on, included in start where you are, is you have to start where your management is. So, if your management is tasking you with an improving scrap and rework, then that's what you better be talking about. Now, you don't have to be guiding your actions based on acceptability because the other aspect is scrap and rework are typically associated... Well, not typically, they are associated with acceptability. The lack of acceptability, acceptability is the idea that this is good, it is acceptable, it meets the requirements, defines...the quality requirements that are defined.

0:06:52.0 BB: If it's good, it is acceptable, if it's bad. There's two categories of bad, bad could be I have to throw it away, that's scrap, which means I can't recover it or rework, which means I can do something with it and perhaps salvage it. And so if your management is tasking you with improving scrap and rework, then first of all, where they're coming from, quite naturally, is acceptability. And why do I say that? Because everywhere I've gone, that is the deepest foundation of quality in every organization I've ever met, worked with, I have met people that work from whether it could be... Whether it's clients that I've worked with, whether it's students, my university classes. Acceptability, scrap, and rework, all go together. And, so if that's where your management is, then they're asking you to focus on improving acceptability.

0:08:05.6 BB: But, you may find it invaluable to shift your focus to desirability to improve acceptability. And that will be a focus, well I get into some of that tonight and others or today, and then on a future podcast later. But, I remember once upon a time at Rocketdyne, the executives were, the VP of Quality was task master asking for improvements to scrap and rework and also things called process capability indices, Cp’s and Cpk’s. And if you've heard of a Cp or a Cpk, great, if you haven't all I could say is I find them dangerous. I find them, well I say they're all about acceptability. And what makes it, reason I would encourage people to stay away from them because they appear to be desirability, but they're really acceptability.

0:09:15.7 BB: We'll save that for later. But anyway you have to start where they are. So if people are asking for improvements in scrap and rework, then, instead of fighting them, you go with it. And then what we'll be talking about tonight is, is it worthwhile to shift? Well, what does it mean to improve acceptability and the difference between acceptability and desirability? And relative to the title tonight, Mind the Choices is being aware that there's a place for acceptability and there's a place for desirability. And going back to Yoshida in episode three, what I was referring to is, in presentations he was doing from the early '90s, maybe even going back to the '80s, he talked about Japanese companies are about desirability. So, he presented this model of acceptability and desirability. And then, his explanation of what makes Japanese companies, again, back in the '80s, Japanese companies were viewed as those setting the quality standards.

0:10:20.5 BB: And, he was trying to say that the way they're doing that is that they don't rely on acceptability as other companies in other countries do. They have a higher standard. And that's what I wanted to introduce in our last episode, Episode 3. And, what I wanted to do tonight in this Episode 4, is to put some, add some more to that. But, also reinforce I'm not saying that there's anything wrong with acceptability, it's a question of what does the organization need at that point of time? And, really it has to do with... Really, it has to do with how big a system you wanna look at. So if you're looking at something in isolation, which is, I mean, when you look at something and saying it's good or bad, that is the epitome of looking at something in isolation.

0:11:17.5 BB: You're looking at a pen and saying it's good. You're looking at the diameter of a hole and saying it's good. That is not looking at what goes in the hole, that is not looking at how the pen is being used. So by definition, that's what Ackoff would call analysis, which is looking inward. It's not what Ackoff would call synthesis, which is looking outward. And how far outward you look is all according... I mean you could look, it comes down to how big is the system. And I wanna introduce the name Shel Rovin, Sheldon was his full name. Shel was his nickname. I met Shel through Russ Ackoff in 2006. Shel was, he was in charge of the Chief Nursing Officer program, which was a two-week immersion program at the University of Pennsylvania.

0:12:14.5 BB: And he was doing that in the, 2003, 4, 5, timeframe when I met him. And Shel was a dentist by background. He was Dean of the School of Dentistry at University of Kentucky and University of Washington. And I met him through Russ and invited him to Rocketdyne on numerous occasions. And Shel spoke about relative to looking at a system, 'cause people talk about, well "Andrew, we've gotta look at the whole system," but how big is the system? And, so people say, well, systems thinkers look at the whole system. Well, how big is that? Is that 1,000 foot view? And people say, oh no, Bill, it's bigger than that. Is it a 10,000 foot view? Is it... How big is the system? Well, Shel's perspective, and the word I wanna introduce from Shel is relative to systems is boundarylessness.

0:13:12.7 BB: Say that a few times fast. 'Cause systems have no boundaries. So I'm sure our listeners... I'm sure you have heard, I don't if our listeners have all heard, Dr. Deming would say to executives, does your system include the future? He used to ask questions such as what business are you in? What business will you be in five years from now, 10 years from now? Well, why not 15 years from now? Why not 25 years from now? Native American Indians, associated with Native American Indians is the idea of looking at the seventh generation after you when you're making choices. And so what I would ask people is, well, why seven? Why not eight? Why not nine? Why not 10? I mean, within an organization, we could be working with our supplier to try to get across these quality ideas to our suppliers.

0:14:05.5 BB: Well, that's looking at the system. Well, wait a minute. Do our suppliers have suppliers? Yes. Do their suppliers have suppliers? And so relative to boundarylessness is this idea is when people start talking about the whole system, I don't know what "whole" means. What I'd rather look at is what size system are we looking at? That's a choice. That's a choice. So we could decide to look at our suppliers. We're gonna go one step, we're gonna look at procurement. Who do we buy from? Now, we may educate them and give them the responsibility of looking at their suppliers on... But that would be a way of managing quality. Likewise, we can look at the impact of our work on our customer and give them heads up as to how to look at the impact of their work on their customers. But that's looking at the system in an X, Y, Z, physical coordinate, add onto that, the time dimension. And so, again, all I wanna throw out there is that when it comes to making choices on acceptability, desirability, a lot of it has to do with how big is the system that we're looking at. Some everyday examples of acceptability.

0:15:23.5 BB: Again and what I wanna get across is, in part the difference to help people make choices. And so when we were on a vacation in Europe recently, I took a number of photos of people making choices. And,` when I travel, anywhere I travel, especially out of the country, I love walking into supermarkets just to see what they sell that perhaps is not sold in the States or in California. I know there are things you can't find in California that you can find on the East Coast. That's one thing. But I like going into supermarkets just to see what products are there. I mean, you can go to England and find in the refrigerator section, hard cider, apple cider, you know, alcoholic cider that I got exposed to going to a Deming conference in 2000. I've become a fan of it ever since. Well, in the States it's pretty hard to find hard cider, period. You go to England and you'll find, a dozen different brands and each brand may have a number of different types.

0:16:44.9 BB: And so that's, but anyway, relative to that when you walk into a supermarket, if you're looking at canned goods, or just look, well, looking at cider, we can look at this cider versus that cider. We treat a can as a can, whether it's buying tomato soup or cider, we treat all those cans as interchangeable, interchangeable parts. But when we go to into the bakery section, that's where I was taking photos in Amsterdam and I was watching people sort through the pastries. And yet what was laid out were a bunch of pastries of the same style. And yet people were, I want this one, I want that one.

0:17:26.0 BB: Well, part of acceptability is treating all those pastries as the same as we would treat all those cans of tomato soup as the same. Now relative to tomato soup I know you live with your mother, and I'm willing to bet your mom, early, early on when she took you to the supermarket, taught you how to buy canned goods, right? And she says "Andrew when you buy a can of something you pick it up, you're looking for dents," right?

0:17:55.1 AS: Mm.

0:17:56.0 BB: Because if it's dented, that's bad. And if it's not dented, that's good. I know my mother taught me that. So I know when it comes to buying canned good we look for dents. If dented, that's bad. If it's not dented, it's acceptable. But I don't see people sorting between cans of tomato soup made by the same manufacturer. They're just, we treat it as they're acceptable. Acceptable implies either one, the differences don't matter or I don't see differences.

0:18:33.0 BB: Desirability is, you wanna see a great example of desirability, go to the produce section and again, either watch people sort through pastries that are all acceptable, and yet they're looking for the biggest one, or... And when it comes to fruit, we're looking for the ripest banana, or maybe we're looking for bananas that are green because we're not gonna use them for a while. So acceptability, again, I'm trying to give everyday examples of acceptability is going in and saying, looking at all the fruit there, and just taking five peppers, whatever it is, and throwing them in the bag and saying, I need five 'cause my spouse said, go get five. And I throw them in the bag. And it could be time-wise, I don't have time to sort through them, or I quite frankly don't care that they're different. That's acceptability. So acceptability is either acknowledging they're different and saying, I don't care. Or...

0:19:29.6 AS: Seeing them as the same.

0:19:32.4 BB: Or pretending they're all the same. And I had a guy in class years ago, and I was asking about buying fruit and I was trying to use the example of we go into the supermarket. We sort through the oranges looking for the ripest one, and this guy says, well, I don't sort through the oranges. I said, well, how do you buy the oranges? I buy them by the bag. I said, do you sort between the bags? He says, no, I don't sort and his arms were crossed. I don't sort, I don't sort. So then I noticed that he had a ring on his left hand, a wedding ring on his left hand. So I said, I see you're wearing a wedding ring. And he said, yep. I said, did you sort?

0:20:15.2 AS: I don't sort.

0:20:15.3 BB: Meaning... I don't sort. And so when you're looking at things that meet all the requirements and saying there is no variation or the variation doesn't matter, that's acceptability, Andrew. When you look at all the things that meet requirements and you see them as being different and saying, I want this one, that's desirability. And so that could be, when it comes to selecting a spouse, when it comes to selecting an orange, when it comes to selecting a parking spot, in a university, you're looking for the, an ideal, the best professor for Thermodynamics II, and there's 10 professors the university says are acceptable. And you talk to classmates and you find out, oh, no, no, no, stay away from that one. What are you doing? You're sorting amongst things that meet requirements, that are acceptable and saying, that's not good enough for me in that situation.

0:21:17.2 BB: Well, what I wanna say then added to that is, this is not to say desirability is better than acceptability. It really comes down to is desirability worth the effort? Because when it comes to desirability, I am looking beyond, I'm looking at a bigger system. So I'm looking at the fruit in terms of how I'm using it. If I'm aware of that, I'm looking at the parking spots in terms of: I'm gonna be in the store for an hour and I want the most shade, or these parking spots have a little bit different distances between cars, and I want a spot with a little bit more width so somebody doesn't ding my car. So what I'm hoping is with these examples, people can appreciate that every day we make choices between acceptability and desirability.

0:22:11.3 BB: Every day we're making a decision based on saying, this is okay, code word for acceptable, or I'll take that one, that's desirability.

0:22:27.6 AS: That's quite a breakdown.

0:22:28.1 BB: Well, and the idea being... The other aspect of it is when you're choosing to say, I want... When you decide that acceptability is not worthwhile, my proposal it's because you're looking at a bigger system. You've got a bigger system in mind. You're not looking at that fruit in isolation. You are somehow saying, there's something about how I plan to use that, which is the reason for this decision. And then it gets into how big is the system that you're looking at? Are you looking at the person downstream of you at work, which that could be an internal customer. People used to use those terms. Are you looking at the person after them, two down from them, three down from them? And that gets into a choice. So what I would tell the folks I was mentoring at Rocketdyne is that they were designing things or going to see how they were used. And I'd say, first of all, nothing requires you to go see how that's used. Your job as a designer, whatever it is in engineering you design it, you give it to manufacturing. But you don't have to go downstairs and see how they're using it.

0:23:47.5 BB: I said, but if you do, you might learn a lot. And then they might say, "well, so I should go talk to the person who's first using it." Well that might be helpful. And then what about the person after that? Well, that might be helpful. And then what about the person after that? Well, that might be helpful. And I was trying to get across to them, we hire really bright people and if we just turn you down to don't look beyond, just deliver the thing, complete those drawings, do whatever it is, pass it to the next person. I said, the system may not require you to go look to see how it's used.

0:24:31.9 BB: But what Dr. Deming is proposing is, the better you understand how it's used, the better you can serve the system. But then you get into the question of how big is the system that you want to be thinking about? And there I would tell them that there's no right answer. I mean, you wanna be and this is what I would tell them is we hire really bright people and then we condition you to believe that it doesn't matter. What I'm proposing guided by Dr. Deming is that there's a possibility that it matters anywhere from a little to a lot, but you won't know unless you go look.

0:25:12.2 AS: Yeah. It's funny.

0:25:12.3 BB: And so what I wanna get... Go ahead Andrew.

0:25:14.4 AS: When I was a supervisor at Pepsi in Los Angeles at our Torrance factory, they asked me to help... Could I figure out how to quicken the pace with which we got 80 trucks or 100 trucks out the gate every morning because it mattered. If you got trucks out an hour late on the LA freeways, now you have overtime and all kinds of trouble. So, what I did is I climbed up... At 4:00 AM I climbed up on top of a building, one of our buildings.

0:25:54.1 BB: Wow.

0:25:54.9 AS: And I had a clipboard, which I always have. I have extra clipboards always with me, here's one right here. And I had paper and then I just observed, and I took a lot of notes. And what I was seeing was all these drivers were, they were checking their trucks and they were spending a lot of time with their trucks. So, after I observed it that morning, the next morning I went down and went around and I asked them, what are you doing? And they said, well I'm checking that the quantity that's on the paper is the quantity that's on the truck. And I said, how could that not be? And they said, the loaders at night don't fill it up right. So, the next night I went and talked to the loaders and I said, drivers are saying that you guys are making errors.

0:26:40.4 AS: No, we're not making any errors. Okay. So, now I gotta dig deeper into the loaders. And then I start to see, okay, the loaders are making errors. So, I went and talked to one loader and said, why are you making this error? He said, well, the production are supposed to put this particular Pepsi item in this spot. But they didn't, they put it in another and I got confused, but it's just 'cause it's normally always there. So, I go to talk to the manufacturer, hey guys come on, why did you put that stuff in the wrong spot? He said, well, sales told us to produce so much that we were overloaded. We didn't have any place to put all of this products. So, we had to basically put it anywhere we could as it's racing off the line and on and on.

0:27:27.9 AS: And then you start to realize like, okay, the system is bigger. Now I went and focused on the loaders and said, how do we make sure that when the loaders load that we can lock the truck and then tell the drivers, you must not open this truck. How do we build the trust between the loaders and the drivers that they're loaded correctly and that they can go, because the drivers don't want to get to San Bernardino or wherever they're going and find out, oh, I don't have what this particular customer wanted and it's supposed to be on here. So that's just a little bit of a picture of kind of a very narrow start that starts to bring in more of the system.

0:28:06.8 BB: Oh, yeah. Oh, that's a brilliant example. And also what you're talking about is a term we used the first series, which is the value of synchronicity. That those handoffs are smooth. And they disrupt...

0:28:26.7 AS: I love that word handoffs, by the way. I was just talking with a client of mine. We were talking about the core processes of the business. And I just now realize that what I was missing and what we were missing in our discussion was how do we make sure that the handoffs work.

0:28:43.6 BB: Well, then the other thing, again a concept you may recall from the first series is, I liken it... I think in terms of two types of handoffs. And, actually, I think in one of the first, maybe in the second episode we talked about this, is associated with acceptability. When I hand off to you something, my report, whatever it is I'm assigned to delivered to Andrew by 5 o'clock tomorrow, you look at it, you inspect it, and you're making sure before you accept it that it is acceptable, that it has all the content. And, if anything's missing a figure, a graph, a label, you send it back to me and then I go through and massage it and then send it off to you. And, part of acceptability is when you say, that's good, then the handoff we're talking about is physical.

0:29:51.6 BB: Right. I mean, there's nothing wrong with a physical handoff. I give it to you physically. And what you may recall me mentioning, I think, again likely episode 2, podcast 2 of this series is I would demonstrate this with people in the class. And I would say, if, if what I give you is not acceptable, what do you do? You give it back to me and you say it's incomplete. And then I go through, massage it. If I now give it to you and all the requirements have been met, it's acceptable. Now what happens? What do you say? And I would kid them and so now you say, thank you. But what I'd also point out is that part of acceptability in a non-Deming organization is the handoff is physical and mental. I mean, physical is: It is yours, not mine.

0:30:38.5 BB: Mental is that if you have trouble with how that fits into what you are doing with it, because that report does not exist in isolation, you're doing something with it. Right. So you're doing your things with it. Now we're looking at the system. And if in the system of you're using it, you have an issue and you come back to me, in non-Deming environment, acceptability is my way of saying "Andrew I'm not sure why we're having this conversation because what I gave you is acceptable." But in a Deming organization, the handoff is physical, but not mental. What does that mean? It means, I'm willing to learn from what you just said and the issues you're having. And now I'm beginning to wonder, there's two possibilities. Either one, what I gave you is not acceptable. There's something wrong with the inspection.

0:31:34.3 BB: Or two, what's missing is desirability, that there's some... What I give you is acceptable, but there's something about how it's, it's um, there's a degree of acceptability, and so instead of viewing it as it's good or it's bad, black and white. Now we're saying there's degrees of good. Desirability is degrees of good. And, so in a Deming environment, when I hand off to you and you have an issue with it, you come back the next day and say, "Bill, somehow this didn't get caught in the control chart." And I said, "well, let me take a look at it," and I may find there was something wrong with the inspection, or I may find that there's a degree of good I'm not giving you that I need to be giving you. So, that can either be an acceptability issue or a desirability issue. I'm willing to have that conversation with you in a Deming environment. So, in a Deming environment, the handoff is physical but not mental. And the learning, as you're demonstrating, the learning that comes from the ability to have those conversations, improves the system. That's a lot more work.

0:32:53.8 AS: So, if you were to sum it up, was that the sum up or would you add anything else to your summation of what you want people to take away from this discussion?

0:33:05.6 BB: Yeah, that's it. I'd like to say one is that there's, acceptability is fine. Choose acceptability, if that's all the situation demands then you've chosen that. But pay attention to how it's used, pay attention to the ramifications of that decision, which may show up an hour from now, may not show up until a year from now. And, the possibility that hiccup a year from now could be either it wasn't acceptable, in which case there's an inspection issue or it was acceptable, which means there's a degree of good, which means it's a desirability issue. And, that gets us into future conversations, talking about degrees of good and the whole idea of variation in things that are good. That's desirability, variation in things that are good.

0:33:57.6 AS: All right. Bill, on behalf of everyone at T      he Deming Institute, I want to thank you again for this discussion. And for listeners, remember to go to deming.org to continue your journey. And if you wanna keep in touch with Bill, just find him on LinkedIn. He responds. 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."

In this new series, Jacob Stoller and Andrew Stotz discuss five major management and productivity myths and how Lean and Deming thinking solve them. This first episode offers an overview and Jacob shares his journey from traditional management to a better way.

Jacob Stoller is the author of The Lean CEO: Leading the Way to World-Class Excellence and Productivity Reimagined: Shattering Performance Myths to Achieve Sustainable Growth.

TRANSCRIPT

0:00:02.3 Andrew 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'll be talking with Jacob Stoller, who is a journalist and Shingo prize-winning author of The Lean CEO, which provides a boardroom perspective of Lean initiatives. Now, he connected with Dr. Deming's criticism of command and control management and recently wrote Productivity Reimagined to explore the reasons why organizations fail to apply the Lean and Deming style of management at the enterprise level. Jacob, welcome to the show.

0:00:37.8 Jacob Stoller: Well, thank you, Andrew. It's great to be here.

0:00:40.5 AS: Yeah it was actually really fun to talk to you before we even turned on the recorder to kind of really help people understand where you come from and why you are here. So maybe you can just explain a little bit of your journey of how you got to this point in relation to Deming.

0:00:58.2 JS: Okay, well, interestingly, I started out in sales. I was a corporate sales rep selling services and software and all that kind of high-tech stuff. And I did that for quite a while. But what I liked best about corporate sales was the dialogue that I had with customers, being able to talk to people and ask questions and explore topics. So fortunately, I was able to turn that into a career. I left that profession about 2001 and became a writer, journalist, did research projects, gave talks, did some training, did all the things I wanted to do. And through that, I discovered Lean by accident. And that, I think, wasn't probably till about 2010. And I was writing for a magazine, and someone told me to write about this Lean thing. What is it? And I started to ask questions and talk to people and eventually discovered this wonderful way of running companies. I was totally impressed, not just with how efficient they were and all that, but how they treated people. I thought, this is, boy, I would have liked to have worked at some of these companies.

0:02:14.6 AS: And for someone who's never even heard, let's just imagine someone's never heard the word Lean. What does that mean anyway? And what did it mean when you first saw it and after you really became an expert in it? What does it mean to you now?

0:02:28.4 JS: Well, I thought it was going to be super high tech. That's what I first thought. As a matter of fact, when I went to Japan to actually see it firsthand, I was expecting just flashing screens and everything. And of course, it was a very different thing. It was a lot of people, very, very people-oriented environment, people talking to each other, lots of communication. So I thought, wow. And I started to learn that it was really all about people. And so that was a gradual transformation for me. But it was very rewarding to see the human side of this. So that led me, really led me to some writing. I started working with some lean organizations like the Kaizen Institute, and I started doing writing for them, writing newsletters. I also wrote, helped Misaki Yumi the late Misaki Yumi, a very well-known Lean promoter, write the new edition of his latest book. And I did all the case studies for that. And I also helped various other initiatives. But the main thing was that I decided to write my own book, and that was The Lean CEO.

0:03:57.2 JS: And what I was interested in at the time was I saw that people doing Lean were running into all this resistance, and I was interested in exploring that a little more. And I thought, well, the people that really understand that will be the CEOs because they'll been there. They've been in the boardroom discussions. So that's how The Lean CEO came to be. And in that process, I was asking questions about management and the various practices. Now, I was expecting that there would be a sort of a standard executive playbook for Lean. That was my hypothesis, I guess. And it would have been really nice, very, very easy to write the book and neat and tidy and all that, but it didn't work out that way. They were all different. They all had different ideas. And interestingly, a lot of the thinking that went into their work, actually, they had learned before they even discovered Lean. That had been stuff that they believed in. They learned about teamwork early on, so they were somehow predisposed towards the people side of Lean. So I was really fascinated by that. But my conclusion really was that there was no one way to implement Lean, that there were just many, many different variations on it.

0:05:20.5 JS: And that's when I became and started to discover that there was a lot of the thinking that made these people successful at leading Lean outside of the Lean community. And that's where I started to get interested in some other. How the tech sector was handling change, how the sustainability people doing sustainability projects were handling change. And one speaker that spoke out loud and clearly to me was Dr. Deming, because Dr. Deming understood the fundamentals behind the thinking. I think that makes Lean successful. He understood what was wrong with conventional management and the barriers that people were running into. So, Andrew, I don't know if you remember, but the 1980s, everybody was talking about this ABC show, If Japan Can, Why Can't We? And here we are looking at a productivity crisis. I mean the US was their crown jewels in the US industry had been trounced by the Japanese. They were being outproduced two to one, right? I mean, and so this was recognized as a crisis. It was an election issue at the time. And I, they got Dr. Deming on television and they asked him what are we doing wrong? And Deming was very clear.

0:06:51.1 JS: He said you're not going to learn this, you're not going to be able to imitate the Japanese, and you're not going to learn a few production tricks. You've got to fundamentally change the way you manage. So that was a very, very strong message that I picked up when I was writing that book. And what's wrong with conventional management? What's wrong with command and control management? And why does it not why does it create companies that are so wasteful and do such a bad job at being productive?

0:07:22.6 AS: And as a devil's advocate, if I think about a Lean a company that's trying to adopt Lean, what I would assume was that at the management level, the objective of management is really to reduce resources, to reduce, if you could reduce the cost of electricity, your profit margin would go up. If you could reduce the raw materials that you have in your production process, your profits would go up, as an example, and the value of your business would go up. So how could there be any resistance to a young engineer that's picked up Lean and is bringing it through the organization? It's a little bit odd to think why would there be resistance to that?

0:08:04.1 JS: Well, the resistance is that people are used to doing what they're doing, for one thing. And Dr. Deming has identified with his knowledge of complex adaptive systems a fatal flaw in the hierarchical structures that corporations are run by. You see, if you're using corporate logic, you assume that every department and every work group is like an independent component and that if each component functions as intended and according to measured objectives, then the corporation will succeed. And Deming said that that is completely false, and he had the evidence to prove that. So what people are resisting is not that, people aren't resisting the idea of reducing costs and being efficient, but they're measuring efficiency in the wrong way. They're measuring efficiency of independent assets. And they say if these independent components produce efficiently, then the sum of the total will have an efficient corporation. But that's not true. That's only true according to 17th century logic. If you follow Newton and Newton's laws, that seems to be the case. And it's intuitively, we do tend to think that way. But if you're running a company, a company is not a simple system. It's a complex adaptive system.

0:09:38.7 JS: And it's the interdependence of all these entities and all these components that determine the success of your company. And that's what Deming was trying to teach, and that's what people didn't want to hear.

0:09:50.7 AS: So if I hear you correctly, the first thing is kind of the first wall that someone would come to at the board level or at the management level is just trying to overcome inertia. This is the way we do things. Why do we need to change? It takes effort to change. And then the second thing you're talking about is the lack of systems thinking, thinking that if we could just optimize every part, we're going to get the optimal output of this system. They didn't understand that, as you said, it's a complex adaptive system, that it's much more difficult than just saying, everybody do your best. Is there any other resistance that you saw? So the inertia is number one that I saw. The second one is a lack of systems thinking. Is there any other things that you discovered as you were working on The Lean CEO?

0:10:38.3 JS: Oh, yeah. Well, there's the elephant in the room. And this is that most large corporations anyway are focused on short-term shareholder value. Right. And the way to make your short-term numbers is not to be productive. It's not to invest in good long-term strategies to develop a long-term competitive advantage. It's to make your quarterly numbers. And that can be manipulated fairly easily. Well, maybe not easily, but it can be manipulated by creating perceptions about value, about market value and that sort of thing.

0:11:17.3 AS: And even more, even more than manipulated, it's just that if you don't follow, if all you do is just try to hit numbers on a quarterly basis, you're losing your focus on the long term.

0:11:27.1 JS: Absolutely. And there was a study, and this goes way back to 2005, but it said that corporate CEOs would sacrifice or 74% would sacrifice a long-term profitable initiative to make their quarterly numbers. They would throw it out the window. I think, if anything, that was 2005. I would think if anything, things have gotten worse since then. So we're actually talking about a slice of companies that really do want to be productive, where long-term productivity is their strategy. And that is, a lot of these are privately owned companies, manufacturers, and perhaps, there's some smattering of public companies that are doing this kind of thing, but it's rare.

0:12:24.7 AS: So let's just. So what we've been talking about is kind of the wall that you started to see, the ceiling that was Lean had a challenge, or Deming's teachings had a challenge, and that was this, overcoming the inertia, the lack of systems thinking, and this focus on short-term quality, sorry quarterly numbers. And very few companies were able to really focus on long-term goals of being productive. Now, maybe you can just take a moment to explain how your newest book, your latest book, then took what you saw from a Lean CEO and Deming and then brought it to another level.

0:13:07.8 JS: Okay, well, I interviewed about 60 people, and it's interesting. I thought it might be fairly easy, I would say. What are the basic myths? What do people get wrong? Usually, these are people that are pretty smart about Lean stuff, and people found that surprisingly hard to answer. And I think that was because a lot of these people I talked to had already been practicing this approach for a long time, so they really had to think about it. So it took some digging and a lot of interviews, but I found the thread was in five sort of primary areas, and one was the systems thinking, the pyramid that we talked about.

0:13:50.4 JS: That Deming so articulately talked about. Also, and then the other myths, I think, are somewhat derivative of that. But there's finance. The myth that the bottom line tells you what you need to know about the productivity of your company and it doesn't show up in the finances. So I did a chapter about that. The notion that the boss knows best, and that's not just the boss, it's also professionals. This idea of professional knowledge. Someone can go to school, learn how to tell people what to do, and that will accurately create the right procedures, the right kind of work.

0:14:32.6 JS: And when people follow directions from professionals, they will be the most productive. So that's a myth. Myth number four is the myth that people are motivated by sticks and carrots. And psychologists have disproved this about 70 years ago, I guess, but people still, if you look at compensation plans and you look at the way companies are managed and you look at structures, it's still assumed that people are going to be motivated by externals, by threats and rewards. So we talk about that and some companies that have dealt with that one. And then finally, there's this myth of tech omnipotence. We tend to have way more optimism about technology than is warranted, and we're seeing a lot of that in AI now. We're seeing a lot of disappointment with things not turning out the way people expected. So I really explored those five myths and how they stymie productivity and how companies can build a strategy around count.. what's the word I want? Counterattacking those myths or whatever.

0:15:45.5 AS: And then for the person who reads it, what is the outcome? So once they understand these risks, like number one, you mentioned about the pyramid and not understanding systems thinking. You mentioned number two about finance, you mentioned number three, about the professional or the boss knows best. And number four, people are motivated by sticks and carrots. And number five, tech omnipotence. Once they understand those myths, where do they go from there? How can they then apply that into their life and their work?

0:16:16.2 JS: Well, I suggest that they go into companies that are actually successful at dispelling these myths. You got to see it. But I have a last chapter, a long chapter, but I provide a sort of a roadmap for moving in. But there is really no alternative. If you want to build long-term productivity, there is no alternative to continuous improvement because you're just going to have to keep improving. And Dr. Deming explained that very well in terms of variation. It's always going to be there, and you're always going to have to be dealing with it. So you're going to have to create a culture, and it's going to be people-based. I don't care what kind of technology you have, long-term productivity gain is going to have to come from building the culture in your company.

0:17:10.1 AS: And I want to wrap up our discussion about this just so the audience understands. When you say productivity reimagined, what do you mean by the word productivity?

0:17:23.5 JS: Productivity is customarily just used as sort of a ratio. You know, people say, "Oh, yeah, I'll just take the total sales and divide it by the number of employees" or something like that. So it's seen as a sort of an indicator rather than something that you have to actually do. Right? That's something you have to actually pursue in a direct sort of way. And another, I'll make another side point, is economists like to say that take the GDP and divide it by the number of worker hours or whatever and say that's productivity. But it really, you know when you, the US government website defines productivity as increasing output with a given set of inputs. So from time A to time B, you've got to actually make more with what you have. And that's these indicators that people use for productivity don't reflect that at all. So you've really gotta... Productivity is not that easy to measure, and there's some, actually, some qualitative sides of it, right? I mean, if I'm making, say, ballpoint pens, and let's suppose I increase the production by 10% using the equivalent amount of materials and all the machinery.

0:18:51.9 JS: Well, that's great, but what if the quality goes down? You know, I haven't really gained anything. So it's kind of tricky to measure productivity. You have to get right down there in the processes to understand it. And so I would tell the finance people that it's inside that black box. You have to be in, understand what's going on inside that black box of operations to really understand whether, which direction your productivity is going.

0:19:20.2 AS: Okay. So if I hear that right, I think a lot of us could get lost in some sort of ratios or something like that and think about a measure. But in fact, what you're talking about is to really do productivity right, it sounds like you also really have to understand trade-offs. If you cut in a particular area, that's going to cause another problem, and that's going to...you may not be able to get more out of your existing resources. In addition, it's going to require work because you're organizing your company in a certain way to get a certain level of output with the inputs that you have. But in order to get a much higher level of that, you've got to rethink: How do I get the maximum out of this organization, which is a real challenge.

0:20:09.8 JS: Well, I think this is where this is, you know, it depends on how you do it, right? I mean, you can do it in a siloed way, which says, I have a quality department, I have an operations department, I have a maintenance department. And you can invest in all these and play around with your investments and see what works out. Or you can get into the process, and you can, by really, really understanding the process and letting people in the process improve it. That's where you get Deming's magic chain reaction, which is that you improve quality, and then your efficiency is going to improve and your costs are going to go down. But that's only if you're looking at productivity in a very broad way. It's not looking at quality in terms of the tolerances that I made on my grinding or whatever I'm doing. It's about the quality of the processes themselves. Right? So Deming was looking at quality with a big Q that encapsulates a lot of things.

0:21:16.0 AS: Well, I think what, what's, this is very interesting. And I know we're going to have a series that we're going to start doing, going through more detail of what you've discovered and what you want to share. So I'm really looking forward to that. And so, I appreciate this introductory discussion. And Jacob, on behalf of everyone at the Deming Institute, I want to thank you again for this discussion and for listeners, remember to go to deming.org to continue your journey. You can find Jacob's book, Productivity Reimagined, at jacobstoller.com. This is your host, Andrew Stotz. And I'm going to leave you with one of my favorite quotes from Dr. Deming: "People are entitled to joy in work."

In this new series, John Dues and Andrew Stotz discuss John's model for improvement. This episode includes an overview of the model and how John uses it for goal-setting and planning in his school.

0:00:02.4 Andrew 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 John Dues, who is part of the new generation of educators striving to apply Dr. Deming's principles to unleash student joy in learning. The topic for today is building an improvement model. John, take it away.

0:00:24.8 John Dues: It's good to be back, Andrew. Yeah, so we sort of wrapped up this last series. We had a six-part series on organizational goal setting. And we, if you remember, we talked through those four conditions that are important for organizational goal setting, especially healthy goal setting, where before we set a goal, we understand sort of how capable our system is. We understand how our data is varying within our system. We are looking at our system and seeing if it's stable or unstable. And then, of course, we want to have a method for how we go about improving. And so you kind of have to have an understanding of those four conditions before you set a goal.

0:01:03.6 JD: And I thought sort of as an extension of that, or possibly a new series, we could kind of take a look at an improvement model that would help us sort of better set ambitious goals. Because when we did those four conditions, it kind of leaves you wondering, well, how ambitious should my goals be? Should I still do stretch goals, those types of things? And I think this improvement model that we're building here at United Schools sort of addresses that. And it's something we're building.

0:01:34.4 JD: And so I think the listeners kind of get like a little bit of behind the scenes on what it looks like now. I think we'll see a version of it. And perhaps through this dialogue, through the series, we'll even think about ways to improve it.

0:01:48.4 AS: Can I ask you a question about that?

0:01:49.6 JD: Sure.

0:01:50.0 AS: One of the things, I do a lot of lectures on corporate strategy and workshops, and the lingo gets so confusing, vision, mission, values, and all kinds of different ways that people refer to things. But when I talk to my clients and my students, I oftentimes just tell them a vision is a long-term goal. And it could be a five-year or a 10-year goal. And because it's long-term, it's a little bit more of a vision as opposed to, you can see it very clearly. Like my goal is to get an A in this particular class, this particular semester. Whereas what I try to say is, a vision is: I want to be in the top of that mountain. And I want us all to be at the top of that mountain in five years. And I kind of interchangeably call that a long-term goal and a vision. And I'm just curious what your thoughts are on long-term versus short and medium as we go into this discussion.

0:02:53.8 JD: Yeah. I think as we get into the model, we'll actually see both of those things, sort of a long-term sort of goal, sort of a more intermediate thing, and then how you work back and forth between those two things. So I think that's a good segue.

0:03:08.4 AS: Let's get in it.

0:03:08.4 JD: Yeah. And so just maybe just a few other things about the model before we get right into it. So one thing to know I've come to appreciate is when when I say a model, I just mean something visually representative that helps us understand and communicate how we think things should be functioning in reality. So when I say improvement model, I'm actually like talking about a diagram on a piece of paper that you can put in front of everybody on your team. So everybody has an understanding for how you're approaching goal setting in this case.

0:03:38.1 AS: Would you call it an improvement visualization? Or what's the difference between what you mean by model and like something that I would call, let's say, a visualization?

0:03:49.5 JD: Yeah, I'd say it's a type of visualization when I say model.

0:03:52.8 AS: Okay. Excellent.

0:03:53.8 JD: Yeah, that's what I'm talking about. And I think you'll see it when we get into the model that definitely there's credit due to Mike Rother and his concept of Improvement Kata because this model heavily borrows from the work that he's done, if you're familiar with that four-step Improvement Kata process.

0:04:15.1 AS: Yeah. Very.

0:04:19.7 JD: But anytime, whatever the thing is that you call like key performance metrics, key metrics, whatever you call that thing that we all set in our organizations, there's always this gap between what we want and what we're currently getting. And this model gives us the scientific way of thinking and working to close basically that gap. In this world, the gap between the voice of the process and the voice of the customer, how do we close that gap? So that's sort of what the model is addressing. So I'll share my screen so you can see that and anybody that's watching can see what the model looks like. And I'll just kind of leave that up as I'm talking about it, put it in slideshow.

0:05:08.7 AS: Great. We can see that now.

0:05:14.6 JD: Great. So we can just start by just kind of giving an overview, especially for those people who are listening, but you can kind of picture like a path going up a mountain and that path has twists and turns. It has obstacles. In this particular diagram or model, there's rocks in the way of the path. There's a water hazard, there's trees in the way, there's a roadblock. And as you go, it's kind of strange because you're working your way up. And I'll explain this all as we go through it kind of one step at a time. But as you're working from left to right in the model, this four-step improvement model, you have a team over on the left. This team's working on a goal that you're setting. And then over on the left, you actually have step two, which is grasp the current condition. And then you have this big crack in the path that's called the threshold of knowledge. And I'll talk about what that is.

0:06:11.1 JD: And sort of the next step is actually step four, experiment to overcome obstacles as you're working left to right. You go further up this path, up this mountain. And number three, the step three is establish your next target condition. And then when you get all the way up the mountain and you have this challenge or direction. So that's what you were just talking about. So what's that long-term thing that you're trying to accomplish? We call that a challenge or direction. So the steps that you're taking actually chronologically are you're going to do number one first.

0:06:43.2 JD: You're going to set that challenge or direction, but it actually is the thing that you're working toward. That's the sort of beginning with the end in mind. So that's why it's way up on the mountain, but you're going to do that first. And the next thing you're going to do is go all the way back down to the start of the path and grasp whatever that current condition is in your organization. And then you're going to run experiments on the way to trying to get to the next sort of intermediate step, that next target condition. So four steps, and then you have this team working on it.

0:07:16.8 AS: Which I would say for the traditional American style, as from my perspective, it can be a bit confusing because you're starting with number one at the farthest point away instead of closest to you. Then you're going to come to number two. From a timeline perspective, it feels like you're kind of zigzagging back and forth in your thinking.

0:07:38.8 JD: Yep. You definitely are. And it takes a little bit to wrap your head around it, but we'll kind of work through this piece by piece. So let's start with the team. So you have these people on the left-hand side of this diagram. There's sort of three different groups within that team. And we've talked about this a number of times, but remember that there's this key concept when you're going to take a thinking systems or a systems view of an organization. That you have to have these three different groups of people. You have to have the people that are working on the system, the people that are working in the system, and then from Dr. Deming's perspective, you have to have somebody that has profound knowledge, has that lens. So again, someone from the outside that has profound knowledge. And then in our case, the people working in the system, generally speaking, are the students. And then you have to have the managers that have the authority to work on the system. So in our system, that would be teachers and school leaders. But this model is not specific to educational organizations. You could translate this to any other type of organization.

0:08:50.4 JD: So if we were a hospital, then perhaps the people working in the system, depending on the improvement project, could be nurses. And then the managers that have the authority to work on the system, maybe the hospital management team. And then someone from outside with profound knowledge could be either someone internally that has familiarity with the System of Profound Knowledge or someone that they bring in externally, like a consultant to help out. So the point is, is that, again, this team, whoever's working in the system is going to differ by the organizational sector that you're working in. But it translates in the system basically.

0:09:31.0 AS: It's interesting that I've seen this type of diagram or concept about work on the system, work in the system and a System of Profound Knowledge coach. But it just kind of clicked for me to think about it. It obviously, like when I work with a company, I'm working with the owners and the top management. And when I do that, we're working on the system.

0:09:58.5 JD: Yep.

0:10:00.2 AS: And I have the knowledge of the System of Profound Lnowledge. So I'm coaching them about the system. And then within the system, they have the employees who are executing on what they're trying to improve and do, but it just perfectly explains it. So I love that diagram.

0:10:17.8 JD: Yeah. And I have the same experience. And I think we've mentioned on this podcast before that in my world, we often have school or district-based improvement teams. And it's typically leaders of the organization, sometimes teachers, but almost never is it students working in the system that are a part of, or, providing significant input into the improvement. So, I think if you can combine, in our case, students working in the system, because they have things that they can identify in terms of how they experience the system that are different than the people that work on the system. And then having that third group that, or that person that has that outside profound knowledge, if you put all the three of those things together, I think you have a much better chance to improve. But I think in schools, that's probably never happening. I'm assuming that's the same in other industries as well.

0:11:08.3 AS: And this also explains why when Dr. Deming would see slogans and things like that, encouraging the workers to do better and higher quality, he was like, they don't have the authority to change the system.

0:11:22.5 JD: Right.

0:11:24.1 AS: And what you've said is the group that's working on the system has the authority or the ability to change the system.

0:11:35.4 JD: Yeah. This is one...the makeup of this team that's using this four-step process, that's one innovation that we've done to this model that would be different from the Improvement Kata. So in the Improvement Kata, there's just coach and learner. Usually sometimes there's a coach of the coach, a coach and a learner, depending on how it's represented, but this is in my view, an innovation where you have the work on the system group, the work in the system group, and then the System of Profound Knowledge coach. I haven't seen that in this model.

0:12:07.4 AS: And could that be because when Mike Rother was writing his book, he was particularly referring to Toyota.

0:12:18.7 JD: Could be. Could be.

0:12:19.5 AS: Where the workers have more authority to impact the system. Whereas in the typical American system, the worker doesn't really have the authority to stop the production line or something like that to the extent of the Japanese. So interesting point.

0:12:36.1 JD: Yeah, that's a really good point. My understanding of Mike Rother's work is he sort of derived this improvement model by watching, observing, working with Toyota over a very long period of time. So that very well could be the case. Cool. So we have the team, so let's go to step one, that's the challenge or direction. And I really like that because again, when we did that six part series on Goal Setting is Often an Act of Desperation, one thing that I did think was missing was like, well, still as an organization, we want to move forward. We want to improve. We want to be ambitious in how we're setting our goals, but I don't think that fully came through in the four conditions. And so I think layering this model on top of the four conditions really helps because I think it is important to be ambitious, especially when we're talking about like a mission driven organization, we need to be setting ambitious targets for student learning, coming to school, those types of things.

0:13:39.6 JD: So really what we're doing in step one of the model is we're asking the question, where do we want to be in the long run? So this is a long term goal. This is a longer range goal that would differentiate us from other schools if we achieved it. But currently when we think about this goal, it actually seems nearly impossible because it's so far from where we are currently performing. We don't know how we're going to get there. So an example in my world is, schools have been paying much closer attention to chronic absenteeism, which is when a student misses 10% or more of the school year. And those numbers basically skyrocketed towards the end of the pandemic and then for the last several years. So that's something we're focusing on as an organization. So our chronic absenteeism rate is really high, like 52%, something like that over the last several years. And we want to get that down to 5%. So there's this huge gap.

0:14:53.6 AS: That's a huge move.

0:14:54.5 JD: Huge gap, order of magnitude, right? To go from 52%, that's the voice of the process. That's what's actually happening. And the voice of the customer, what we want is 5%. And we really don't know how to get there. And that's going to be the case at the point where you're at step one, but you're doing that first. You're setting that challenge or direction. And that really is something that needs to be set, in my view, at the leadership level, at the management level. So, that's step one.

0:15:22.9 AS: And you just said something that's interesting is we really don't know how to get there.

0:15:25.6 JD: And we really don't know...

0:15:26.9 AS: I mean, if we knew how to get there, we'd probably be there.

0:15:28.6 JD: Yeah. Yep. Yep. So that's step one. That's why if you're able to view the model and you're watching the podcast and you can see the video, that's why number one happens first, even though it's on the far right hand in the upper right hand corner at the top of the mountain in the model.

0:15:45.8 AS: And is there a reason why it's a relatively vague thing, right? Challenge or direction.

0:15:54.0 JD: Yeah.

0:15:55.5 AS: Why is it vague as opposed to specific target, goal or saying something like that?

0:16:03.7 JD: Yeah. I mean, I think, I like challenge or direction. One, it fits on the page. And it sort of conveys that it's going to be a challenge. And it also, if you're going to work in this way to achieve something like that, that it's actually setting the direction of the organization, the direction that the organization is moving toward. So.

0:16:24.0 AS: In other words, is it acknowledging that we really won't, we really don't know that target. We think we know it, we see that mountain, but as we go closer to it, we want to go in that direction, but as we get closer, it'll become more clear exactly where we're going to be or want to be.

0:16:44.7 JD: Well, I think this would be something that... I think in my view, we're still learning. But when we set that challenge or direction, I guess I could see some circumstances where we would come off that, but I think we kind of want to set it in a way that really pushes us. Right. So I'd be, I mean, I think you could learn some things that would say, okay, maybe that wasn't the exact right number to set, but I'd also be careful about just adjusting it because it's hard.

0:17:13.2 AS: Okay. So you mentioned 5%.

0:17:17.9 JD: Yeah.

0:17:19.1 AS: Would that be, would you state it as achieve 5%?

0:17:25.9 JD: Yeah. 5% or less of our students are chronically absent.

0:17:30.4 AS: Okay. Keep going. I don't want to slow it down. But listeners may get it faster than I do. I'm a little bit slow and I have a lot of questions as we go along.

0:17:37.0 JD: No, no. And I think what we could do in future episodes is dig into each of the steps a little bit more too, and use this as an overview session.

0:17:46.9 AS: Yep.

0:17:48.3 JD: So that was step one. So now what's going to happen in step two, you're going to come all the way back down. Now you're at the very start of the path.

0:17:56.6 AS: Back to reality.

0:18:00.6 JD: Back to reality, step two. And the first thing you have to do, okay, we've set the target, this very challenging direction we want to head into because it's the right thing to do. The next thing we're going to do is grasp the current condition. And so in step two of the model, we're going to ask, where are we now? So we know the long-term goal and now we need to study the current process and how it operates basically. So basically this study represents our current knowledge threshold about the process. And then it's going to contribute to how we define the next target condition we've set that sort of intermediate step on the way to the challenge. And so a lot of that six-part series on goal setting is often an act of desperation, a lot of that learning is right here at what we're doing at step two, because we're creating a process behavior chart in a lot of cases, and understanding how our data is performing over time in this particular area. That's what grasping the current condition means.

0:19:02.6 JD: So part of it, it's a data thing. So in this chronic absenteeism example, what I'm gonna do is I know where I want to be. Now I need to understand where are we historically. And then also as a part of grasping the current condition, I may wanna do some things like interview students and families that are chronically absent, then sort of dig into why that is. Interview teachers about why they think that is. There's a number of things that you could do at this step on the ground where the work happens to grasp the current condition. And I think there can be a sort of quantitative component to that and a qualitative component to that. Also, we sort of understand like how are things actually working on the ground that contribute to us not being where we want to in this particular area.

0:19:56.7 JD: So that's step two. That's what we're gonna do next. After we've set the challenge or direction, we wanna sort of understand the situation on the ground, grasp the current condition. And then next what we're gonna do is step three, which is establish your next target condition. So in step three of the model, we ask where do we want to be next? So we know we can't make this leap, from 52% to, 'cause we wanna decrease it down to 5%. We know we're not, that's too big a step that we're just gonna get there somehow magically. So our target condition, then it's our next goal, usually within a time bound, achieve by date. In Mike Rother's work, he suggests something on a pretty short term scale. Something like one week or one month. So something like chronic absenteeism, I think one month would be sort of where I would set the next target condition. Just having experience with something like attendance rates.

0:21:07.0 JD: And at this point we don't exactly know how we'll achieve the next target condition, but it also, it doesn't feel as impossible as the challenge. So it's a step towards the challenge. So we're gonna do that next. So we set the big challenge that may take us three years to get to. Then we understand the current conditions on the ground and we use that knowledge to set our next target condition. So that's step three. And then the fourth step is we're gonna experiment to overcome obstacles.

0:21:45.9 AS: And before you go to fourth, let me just ask a question about establish your next target condition. One of the things that's missing from that, obviously is, you know, coming from a different perspective, is that when we say, all right, here's where we want to be, and let's go back to reality, and here's where we are. Sometimes, when people work like myself and others, work with people who say, okay, let's map out all the steps to get to that vision. What are the next five things we have to do? Whereas here you're saying, let's focus on the next target condition rather than the next five.

0:22:25.4 JD: Yep. And keep in mind when I say establish the next target condition, what I literally mean is what's our next intermediate goal that we're gonna shoot for? So if we're trying to get all the way down to 5% from 52, remember decrease is good in this case, establish my next target condition, maybe over the next month, I wanna see if I can get that from 52% down to 35% or down to 40%. Part of what I would look at when I set that next target condition is what did the variation look like when I was charting in step two? So the magnitude of that variation will give me some indication of what would be a reasonable sort of next step target for step three basically.

0:23:11.9 AS: And maybe just explain for those people not familiar with Mike Rother's work and, you know, terminology that you're using, why do you say establish your next target condition?

0:23:28.0 JD: I think, I don't know. I think that, you know, really what I mean is just establish the next target, establish the next intermediate goal, basically. Now, I think using the word condition is because when you think about something like chronic absenteeism, there's conditions that probably contribute to that and part of that condition may be the things that you wanna work on. So I kind of think of like, you know, 'cause when you look at step four, you're gonna experiment. So you're creating a new set of realities, a new set of conditions in your organization. And so sort of that coincides with the metric that you're shooting for. So it's not just the metrics, it's also like what are the conditions surrounding that metric. If that makes sense.

0:24:15.8 AS: Yep.

0:24:16.9 JD: Cool. And then step four then is experiment to overcome obstacles. So basically in step four of the model, we move toward the target condition with experiments. And by experiments, what I'm talking about is Plan, Do, Study, Act cycles or PDSA cycles, which uncover obstacles we'll need to work on. So the path, and that's the path in the model is windy 'cause it's this path to the target condition is not gonna be straight line, but it's gonna require this rapid learning to move in that direction basically. And so let's say we've set that next target condition to be one month from now, that's what we're shooting for. And we're gonna run a series of experiments. Maybe it's four one-week PSDA cycles, maybe it's two, two week PSDA cycles. Maybe it's one one month cycle. It depends on sort of the nature of the Plan, Do Study, Act cycle. But running these cycles where we make a plan, including a prediction, run the experiment, and then study what happens and see if it's moving us in the direction of the target condition.

0:25:40.0 JD: And so in that way, we're rapidly learning what it's gonna take to hit that next target condition. And the other important part of this, you'll see in between the grasping of the current condition at step two and running those experiments, there's this huge fault line, this huge crack in the path that you can't just jump over. And it's kinda labeled there, it says Threshold of Knowledge. And basically it's the point at which you have no facts and data to go on. That's the threshold of knowledge. There's always a threshold of knowledge. And so to see further beyond that threshold of knowledge, that's where you conduct your next experiment.

0:26:28.7 AS: Interesting.

0:26:29.8 JD: So because you, like you were saying, we wanna outline these five steps that we're gonna do. So with chronic absenteeism, I read somewhere a Harvard study where if you text parents what a kid's attendance rate is on a regular basis, they're then more likely to come to school on a frequent basis. So you could see where a school system would spend all this money to get a texting system, maybe even allocate a person or a half of a FTE of a person to run this system. And they faithfully implement this texting system, and it has no impact at their school to impact those chronic, because it had nothing to do with what the actual problem was in that context. And you've spent all this money. And that was just a hypothetical.

0:27:21.2 AS: And you could have done a pilot test of 10 parents or 20 and done it manually and sent out some messages and just tested a little bit.

0:27:31.1 JD: Yeah. You run a test with 10 chronically absent kids. Just to see if you can improve their attendance for a week. And maybe you learn something or for a month and maybe you learn something. And then if the early evidence is pointing in the right direction, then you can run that experiment with more kids or for a longer period of time or under slightly different conditions. Those types of things.

0:27:54.6 AS: So an example that I would say in relation to this for one of my clients is that we've identified that they need to get a higher gross profit margin.

0:28:04.7 JD: Okay.

0:28:05.5 JD: And their gross profit margin is about 23%. And I know that the average is about 30 in the industry. And so my work with them is how are we gonna get that profit margin to be 30 or 35%? 35 would be showing that you've really got pricing power because of something that we've done. And so, I'm pounding away that we've gotta improve this, but you know what? We don't have data to understand the current condition. And this week we've... It's taken us about a couple months to pull that data together. But now we have absolutely comprehensive data that my team has calculated on the profitability of every product, the profitability of every customer, and the profitability of every process. We know the capacity utilization of each part of the production process. So now we have the knowledge that we didn't have before that's gonna, that once get, digest this knowledge, it's gonna give us the indication of what to do next. Which is it's gonna be shut down a particular production process or increase price there. We may lose customers, but it's not worth doing it at this low price or so, but without that knowledge, we're just, it's a dream.

0:29:21.4 JD: Yeah. It sounds like you guys have done step one and step two in that process.

0:29:28.0 AS: Yeah. Which is exciting. 'Cause now Friday's meeting is gonna be about, all right, how do we take this huge amount of data and effort that we've put in and now it's time to come up with what are the steps that we're gonna take?

0:29:40.4 JD: Yeah. And I think even just in that situation, even just acknowledging that there's the threshold of knowledge. Even just getting people to acknowledge that in a room that they actually don't know what's gonna happen. That's the power of the PDSA because it makes you predict, okay, you say this thing is gonna work and when you put in this plan in place, this is your prediction. And then when you come back next week and it doesn't work, then you have to explain that, you know, it's not a gotcha, but it very quickly makes you think in a different way.

0:30:13.0 AS: It keeps a record so someone has gone back, well, I didn't think it was gonna work, you know, for sure.

0:30:18.8 JD: Well, right. And it's usually very like, some of the things that I found in that is when people are off on their predictions, it's very mundane things that they didn't account for. We're in student recruitment season and we set a goal for the number of calls we're gonna make to prospective families. And then hypothetically a recruitment director could fall short and it's like, well what happened? It's like, well, oh, the two part-time people that we had, I forgot they are actually out two days last week right? And so it's usually things like that are actually getting in the way of us accomplishing these grand targets that we have set.

0:31:05.5 AS: By the way, where does the threshold of knowledge fit? We've got number one challenge or direction, number two, grasp the current condition. It's after the grasp the current condition that we come to the threshold of knowledge.

0:31:17.7 JD: Yeah. Because, well, we have somewhat of an understanding of the condition on the ground, but we don't know what's gonna improve it until we run the experiments. So we start running the experiments and we try to sort of narrow that knowledge gap basically. And this is sort of the final part is basically like what do you do when you get to that experiment and when you hit that target condition, when you reach that by the achieve-by date, well now there's a new condition and you repeat the four steps because you haven't reached the challenge or the direction. You just met that sort of intermediate goal. And you basically keep running this four step cycle until that learned long-term challenge is achieved.

0:32:12.5 AS: Okay. Great. So we've got the establish your next condition down where it could be one week, it could be one month, in some cases it could be longer, but it's really our next intermediate goal. Where do we wanna go next? What's the next right step?

0:32:28.5 JD: Yeah. Well, so you go back to step two 'cause you're not gonna change the challenge or direction. Now there's a new set of conditions 'cause you've moved ahead, right? And now you're gonna go back and say, okay, what are the current conditions like? And now we're gonna, okay, let's say we move from 52% to 42%. Now we go back and sort of understand the experiments from that last cycle. And we're gonna set that next target condition. So maybe now we wanna get it down to 25%. And we're gonna run another round of experiments in a certain amount of time to see if it hits that next target condition. And basically you're just gonna keep doing this over and over again. That's really the continual improvement model that we're operating under.

0:33:22.7 AS: So how would we wrap this up?

0:33:24.4 JD: So the big thing for me is, you sort of have to have a model to bridge that gap between current conditions and future aspirations. Beause there's always a gap between those two things. And what this model does is it gives us a scientific way of thinking and working to close this gap. It's a more powerful model than I've ever sort of seen anywhere. And then literally you put it on a piece of paper like this and then you have to explain it to people over and over and over. And then you have to actually do it with people. So we're actually doing this, getting people excited about running PDSAs. And the most important thing is that the challenge or direction, especially for leaders that are listening to this, you don't stand on this mountaintop and set it and then say, go do it. That's why this team aspect is so important. We're setting this challenge or direction as a team, and then we're working together on the ground. Putting that work in, running those experiments to try to bring this thing about, is a completely different way of working. It's not an accountability system, it's an improvement system.

0:34:39.4 AS: Yeah. That's a great overview of this system that you guys are applying and it's exciting to learn more. So I wanna thank you on behalf of everyone at The Deming Institute, John. And I thought the discussion was very interesting myself. And for listeners, remember to go to deming.org to continue your journey. You can find John's book win-win W. Edwards Deming, the System of Profound Knowledge and the Science of Improving Schools on amazon.com. This is your host, Andrew Stotz, and I wanna leave you with one of my favorite quotes from Dr. Deming. "People are entitled to joy in work."

Is reaching A+ quality always the right answer? What happens when you consider factors that are part of the system, and not just the product in isolation? In this episode, Bill Bellows and Andrew Stotz discuss acceptability versus desirability in the quality realm.

TRANSCRIPT

0:00:02.5 Andrew 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 Bill Bellows, who has spent 31 years helping people apply Dr. Deming's ideas to become aware of how their thinking is holding them back from their biggest opportunities. Today's episode, episode three, is Acceptability and Desirability. Bill, take it away.

0:00:28.1 Bill Bellows: Thank you, Andrew, and welcome back to our listeners.

0:00:30.7 AS: Oh, yeah.

0:00:31.4 BB: Hey, do you know how long we've been doing these podcasts?

0:00:36.6 AS: No.

0:00:40.8 BB: We started... Our very first podcast was Valentine's Day 2023. I was gonna say 2013. 2023, so roughly 17 months of podcast, Andrew.

0:00:53.4 AS: That was our first date, huh?

0:00:55.0 BB: Our first date was Valentine's Day 2023.

0:00:58.9 AS: All right. Don't tell your wife.

[laughter]

0:01:03.1 BB: All right. And so along the way, I've shared reflections from my first exposures to Dr. Deming, as well as my first exposures to Genichi Taguchi. Talked about Edward de Bono, Tom Johnson, others, mentors, Bill Cooper, Phil Monroe, Gipsie Ranney was a great mentor. Last week, Andrew, while on vacation in New England with my wife, I visited for a day my 85-year-old graduate school advisor who I worked with for ten years, Bob Mayle, who lives in, I would say, the farthest reaches of Maine, a place called Roque Bluffs. Roque Bluffs. How's that for... That could be North Dakota. Roque Bluffs. He's in what they call Down East Maine. He's recently got a flip phone. He's very proud. He's got like a Motorola 1985 vintage flip phone. Anyway, he's cool, he's cool. He's...

0:02:15.9 AS: I'm just looking at that place on the map, and looks incredible.

0:02:19.0 BB: Oh, yeah. He's uh, until he got the phone, he was off the grid. We correspond by letters. He's no internet, no email. And he has electricity, lives in about an 800 square-foot, one-floor bungalow with his wife. This is the third time we've visited him. Every time we go up, we spend one day getting there, one day driving home from where my in-laws live in New York. And then one day with him, and the day ends with going to the nearby fisherman's place. He buys us fresh lobster and we take care of them. [chuckle]

0:03:01.3 AS: Yeah, my sister lives in Kennebunk, so when I go back to the US, I'm...

0:03:08.8 BB: Yeah, Kennebunk is maybe 4 hours away on that same coast.

0:03:15.3 AS: I'm just looking at the guide and map book for Roque Bluffs' State Park, and it says, "a beautiful setting with oceanfront beach, freshwater pond, and hiking trails."

0:03:25.9 BB: Yeah, he's got 10 acres... No, he's got, I think, 20, 25 acres of property. Sadly, he's slowly going blind. He has macular degeneration. But, boy, for a guy who's slowly going blind, he and I went for a walk around his property for a couple hours, and it's around and around... He's holding branches from hitting me, I'm holding branches from hitting him and there's... Let alone the terrain going up and down, you gotta step up and over around the rocks and the pine needles and all. And it was great. It was great. The week before, we were close to Lake George, which is a 32-mile lake in Upstate New York. And what was neat was we went on a three-hour tour, boat ride. And on that lake, there are 30 some islands of various sizes, many of them owned by the state, a number of them owned privately. Within the first hour, we're going by and he points to the island on the left and he says it was purchased in the late '30s by Irving Langmuir. Yeah, so he says, "Irving Langmuir," and I thought, I know that name from Dr. Deming. That name is referenced in The New Economics.

0:04:49.1 BB: In fact, at the opening of Chapter Five of The New Economics, the title is 'Leadership.' Every chapter begins with a quote, right? Chapter Five quote is, "You cannot plan to make a discovery," so says Irving Langmuir. So what is... The guy's describing this island purchased back in the late '30s by Langmuir for like $5,000. I think it's... I don't know if he still owns it, if it's owned by a nonprofit. It's not developed. It's privately held. I'm trying, I wrote to Langmuir's grandson who did a documentary about him. He was a Nobel Prize-winning physicist from GE's R&D center in Schenectady, New York, which is a couple hours south of there. But I'm certain, and I was looking for it earlier, I know I heard of him, of Irving Langmuir through Dr. Deming. And I believe in his lectures, Deming talked about Langmuir's emphasis on having fun at work, having fun. And so I gotta go back and check on that, but I did some research after the day, and sure enough came across some old videos, black and white videos that Langmuir produced for a local television station, talking about his... There's like show and tell with him in the laboratory. And in there, he talks about joy and work and all that.

0:06:33.5 BB: So I'm thinking, that's pretty cool. So I'm waiting to hear from his grandson. And ideally, I can have a conversation with his grandson, introduce him to Kevin and talk about Deming's work and the connection. Who knows what comes out of that? Who knows? Maybe an interview opportunity with you and Irving Langmuir's grandson. So, anyway.

0:06:52.7 AS: Fantastic.

0:06:54.7 BB: But going back to what I mentioned earlier in my background in association with Deming and whatnot, and Taguchi, and I offer these comments to reinforce that while my interests in quality were initially all things Taguchi, and then largely Deming, and it wasn't long before I stopped, stepped back and an old friend from Rocketdyne 20 some years ago started focusing on thinking about thinking, which he later called InThinking. And it's what others would call awareness of our... Well, we called it... Rudy called it, better awareness of our thinking patterns, otherwise known as paradigms, mental models.  We just like the way of explaining it in terms of becoming more aware of our thinking patterns. And I say that because... And what I'm presenting relative to quality in this series, a whole lot of what I'm focusing on is thinking about thinking relative to quality.

0:07:58.8 BB: And so last time, we talked about the eight dimensions of quality from David Garvin, and one of them was acceptability. And that is this notion in quality, alive and well today, Phil Crosby has created this focus on achieving zero defects. Everything meets the requirements, that gets us into the realm, everything is good. Dr. Deming and his red bead experiments talked about red beads and white beads. The white beads is what we're striving for. All the beads are good. The red beads represent defects, things we don't want. And that's this... Thinking wise, that's a thinking pattern of "things are good or bad." Well, then we can have high quality, low quality and quality. But at Rocketdyne, when I started referring to that as category thinking, putting things into categories, but in the world of quality, there's only two categories, Andrew: good and bad. This either meets requirements or it doesn't. And if it's good, then we're allowed to pass it on to the next person. If we pass it on and it's not good, then they're going to send it back to us and say, "Uh-uh, you didn't meet all the requirements." And what I used to do in class, I would take something, a pen or something, and I would go to someone in the seminar and I'd say, "If I hand this to you and it doesn't meet requirements, what are you going to say?" You're gonna say, "I'm not going to take it. It hasn't met the requirements."

0:09:36.4 BB: And I would say you're right. All the I's are not dotted, all the T's are not crossed, I'm not taking it. Then I would take it back and I'd say, "Okay, now what if I go off and dot all those I's and cross all those T's?" Then I would hand them the pen or whatever the thing was, and I'd say, "If all those things have been met," now we're talking acceptability. "Now, what do you say?" I said, "Can you reject it?" "No." I say, "So what do you say now that all those things... If you're aware that all those requirements have been met, in the world of quality, it is as good, now what do you say?" And they look at me and they're like, "What do I say?" I say, "Now you say, thank you." But what I also do is one more time... And I would play this out to people, I'd say, "Okay, Andrew, one more time. I hand you the pen, Andrew, all the requirements are met. And what do you say?" And you say, "Thank you." And I say, "What else just happened when you took it?"

0:10:45.4 AS: You accepted it.

0:10:47.3 BB: Yes. And I say, "And what does that mean?" "I don't know. What does that mean?" I said, "It means if you call me the next day and say, I've got a problem with this, you know what I'm going to say, Andrew?"

0:10:58.5 AS: "You accepted it."

0:11:01.5 BB: Right. And so, what acceptability means is don't call me later and complain. [laughter] So, I get a photo of you accepting it, you're smiling. So if you call me back the next day and say, "I've got a problem with this," I'd say, "No, no, no." So acceptability as a mental model is this idea that once you accept it, there's no coming back. If you reveal to me issues with it later, I deny all that. I'd say, I don't know what your problem with Andrew... It must be a problem on your end, because what I delivered to you is good. And if it is good, then there can't be any problems associated with it. So, if there are problems, have to be on your end, because defect-free, everything good, implies, ain't no problems, ain't no issues with it. I'm thinking of that Disney song, trouble-free mentality, Hakuna Matata.

[chuckle]

0:12:04.5 BB: But now I go back to the title, Acceptability and Desirability. One of Dr. Deming's Ph.D. students, Kauro [actually, Kosaku] Yoshida, he used to teach at Cal State Dominguez Hills back in the '80s, and I think sometime in the '90s, he went to Japan. I don't know if he was born and raised in Japan, but he was one of Dr. Deming's Ph.D. students, I believe, at NYU. Anyway, I know he's a Ph.D. student of Dr. Deming, he would do guest lectures in Dr. Deming's four-day seminars in and around Los Angeles. And, Yoshida is known for this saying that Americans are all about acceptability meets requirements, and the Japanese are about desirability. And what is that? Well, it's more than meeting requirements. And, I wanna get into more detail on that in future episodes. But for now, we could say acceptability is meeting requirements. In a binary world, it can be really hard to think of, if everything's met requirements, how do I do better than that? How do I continue to improve if everything meets requirements?  Well, one clue, and I'll give a clue, is what I shared with the senior most ranking NASA executive responsible for quality.

0:13:46.4 BB: And this goes back to 2002 timeframe. And we had done some amazing things with desirability at Rocketdyne, which. is more than meeting requirements. And the Vice President of Quality at Rocketdyne knew this guy at NASA headquarters, and he says, "You should go show him what we're doing." So I called him up a week in advance of going out there. I had made the date, but I figured if I'm going to go all the way out there, a week in advance, I called him up just to make sure he knew I was coming. And he said something like, "What are we going to talk about?" He said something like, "We're going to talk about that Lean or Six Sigma stuff?" And I said, "No, more than that." And I think I described it as, we're going to challenge the model of interchangeable parts. And he's like, "Okay, so what does that mean?" So the explanation I gave him is I said, "What letter grade is required for everything that NASA purchases from any contractor? What letter grade is ostensibly in the contract? What letter grade? A, B, C, D. What letter grade is in the contract?" And he says, "Well, A+."

[laughter]

0:15:01.2 BB: And I said, "A+ is not the requirement." And he's like, "Well, what do you mean?" I said, "It's a pass-fail system." That's what acceptability is, Andrew. Acceptability is something is either good or bad, and if it's bad, you won't accept it. But if it's good, if I dot all the I's and cross all the T's, you will take it. It has met all the requirements. And that gets into what I talked about in the first podcast series of what I used to call the first question of quality management. Does this quality characteristic, does the thrust of this engine, does the roughness of this surface, does the diameter of this hole, does the pH of this bath meet requirements? And there's only two answers to that question, yes or no. And if yes is acceptable, and if no, that's unacceptable. And so I pointed out to him, much to his chagrin, is that the letter grade requirement is not A+, it's D- or better. [chuckle] And so as a preview of we'll get into in a future podcast, acceptability could be, acceptability is passing. And this guy was really shocked. I said, "Procurement at NASA is a pass-fail system."

0:16:21.9 BB: Every element of anything which is in that system purchased by NASA, everything in there today meets a set of requirements, is subject to a set of requirements which are met on a pass-fail basis. They're either, yes, it either meets requirements, acceptable, or not. That's NASA's, the quality system used by every NASA contractor I'm aware of. Boeing's advanced quality system is good parts and bad parts. Balls and strikes. And so again, for our viewers, acceptability is a pass-fail system. And what Yoshida... You can be thinking about what Yoshida's talked about, is Japanese companies. And again, I think it's foolish to think of all Japanese companies, but back in the '80s, that's really the way it came across, is all Japanese companies really have this figured out, and all American companies don't. I think that's naive. But nonetheless, what he's talking about is shifting from a pass-fail system, that's acceptability, to, let's say, letter grades of A's or B's. That would be more like desirability, is that it's not just passing, but an A grade or a B grade or a C grade. So that's, in round terms, a preview of Yoshida... A sense of, for this episode, of what I mean by acceptability and desirability.

0:17:54.7 BB: In the first podcast which was posted the other day, I made reference to, instead of achieving acceptability, now I can use that term, instead of achieving zero defects as the goal, in the world of acceptability, once we continuously improve and achieve acceptability, now everything is passing, not failing. This is in a world of what I refer to as category thinking, putting things in categories. In the world of black and white, black is one category, white is a category. You got two categories, good and bad. If everything meets requirements, how do you continuously improve if everything is good? Well, part of the challenge is realize that everything is good has variation in terms... Now we could talk about the not all letter grade A, and so we could focus on the things that are not A's and ask the question, is an A worthwhile or not? But what I was saying in the first podcast is my admiration for Dr. Deming's work uniquely... And Dr. Deming was inspired towards this end by Dr. Taguchi, and he gave great credit to that in Chapter Ten of The New Economics. And what I don't see in Lean nor Six Sigma, nor Lean/Six Sigma, nor Operational Excellence, what I don't see anywhere outside of Dr. Deming's work or Dr. Taguchi's work is anything in quality which is more than acceptability.

0:19:32.0 BB: It's all black and white. Again, Boeing's Advanced Quality System is good parts and bad parts. Now, again, I'm not suggesting that there's anything wrong with that. And I would also suggest in a Deming-based organization there may be characteristics for which all we need is that they're good. We don't need to know how good they are, we don't need to know the letter grade. And why is that? Because maybe it's not worth the trouble to discern more than that. And this is where I use the analogy of balls and strikes or kicking the ball into the net.  If you've got an open net... That's Euro Cup soccer. There's no reason to be precisely placing the ball. All you want to do is get it into the net. And that's an area of zero defects, maybe all that is worthwhile, but there could be other situations where I want the ball in a very particular location in the strike zone. That's more of this desirability sense. So I want to clarify for those who listened to the first podcast, is what I'm inferring is I'm not aware of any quality management system, any management system in which, inspired by Dr. Deming and Taguchi, we have the ability to ask the question, is acceptability all that is required?

0:20:55.7 BB: And it could be for a lot of what we do, acceptability is not a bad place to be. But I'm proposing that as a choice, that we've thought about it and said, "You know what? In this situation, it's not worth, economically, the extra effort. And so let's put the extra effort into the things where it really matters." And if it doesn't... So use desirability where it makes sense, use acceptability elsewhere. Right now, what I see going on in organizations unaware of Dr. Deming's work, again, Dr. Taguchi's work, is that they're really blindly focusing on acceptability. And I think what we're going to get into is, I think there's confusion in desirability. But again, I want to keep that for a later episode. Now, people will say, "Well, Bill, the Six Sigma people are about desirability." No, the Six Sigma people have found a new way to define acceptability. And I'll give you one other fun story. When I taught at Northwestern's Kellogg Business School back in the late '90s, and I would start these seminars off by saying, "We're going to look at quality management practices, past, present, future." And so one year, I said, "So what quality management practices are you aware of?" And again, these are students that have worked in industry for five or six years.

0:22:17.6 BB: They've worked at GM, they worked at General Electric, they worked for Coca Cola, banking. These are sharp, sharp people. But you got into the program having worked somewhere in the world, in industry, so they came in with experience. And so they would say, zero defect quality is a quality management practice. And I'd say, "Okay, so where'd that come from?" And again, this is the late '90s. They were aware of the term, zero defects. They didn't know it was Philip Crosby, who I learned yesterday was... His undergraduate degree is from a school of podiatry. I don't know if he was a podiatrist, but he had an undergraduate... A degree in podiatry, somebody pointed out to me. Okay, fine. But Philip Crosby, his big thing was pushing for zero defects. And you can go to the American Society for Quality website to learn more about him. Philip Crosby is the acceptability paradigm. So, students would bring him up and I'd say, "Okay, so what about present? What about present?" And somebody said, "Six Sigma Quality." So I said, "So what do you know about Six Sigma Quality?" And somebody said," Cpk’s of 2.00." And I said, "So what's... " again, in a future episode, we could talk about Cpk’s."

0:23:48.5 AS: But I said to the guy, "Well, what's the defect rate for Six Sigma... For Cpk's or Six Sigma Quality or Cpk's of 2?" And very matter of factly, he says, "3.4 defects per million." So I said, "How does that compare to Phil Crosby's quality goal from 1962? Here we are, 1997, and he's talking about Motorola and Six Sigma Quality, a defect goal of 3.4 defects per million. And I said, "How does that compare to Phil Crosby's quality goal of zero defects in 1962?" And the guy says... [chuckle] So cool, he says, "Well, maybe zero is not worth achieving." 'Cause again, zero was the goal in 1962. Six Sigma sets the goal for 3.4 per million. Not zero, 3.4, to which this guy says... And I thought it was so cool, he says, "Well, maybe zero is not worth achieving." So, there. Well, my response was, "Well, what makes 3.4 the magic number for every process in every company around the world? So, what about that?" To which the response was crickets. But what I want to point out is we're still talking about zero... I mean 3.4 is like striving towards zero and admitting some. It is another way of looking at acceptability. It is... And again, and people claim it's really about desirability. I think, well, there's some confusion in desirability and my hope in this episode is to clear up some of that misunderstanding in acceptability as well as in desirability. And they... Let me just throw that out.

0:25:58.1 AS: Yeah, there's two things that I want to say, and the first one is what he should have replied is, for those older people listening or viewing that can remember the movie, Mr. Mom with Michael Keaton, I think it was. And he should have replied, "220, 221, whatever it takes." And he should have said, "Well, yeah, 3.4, 3.5, 3.6. It's could be around there."

0:26:27.5 BB: Well, the other thing is, why we're on that is... And I think this is... I'm really glad you brought that up, is, what I would push back on the Lean and the Six Sigma, those striving for zero defects or Cpk's of 2 or whatever they are is, how much money are we going to spend to achieve a Cpk of 2, a zero defects? And again, what I said and... Well, actually, when I posted on LinkedIn yesterday, "I'm okay with a quality goal of 3.4 defects per million." What I'm proposing is, instead of blindly saying zero defects is the goal and stop, or I want Cpk’s of 1.33 or whatever they are everywhere in the organization, in terms of the economics of variation or the new economics, is how much money are we going to spend to achieve zero or 3.4 or whatever it is? And, is it worth the return on the investment? And this is where Dr. Taguchi's loss function comes in.

0:27:49.2 BB: And so what I'm proposing, inspired by Genichi Taguchi and W. Edwards Deming is, let's be thinking more about what is... Let's not blindly stop at zero, but if we choose to stop at zero, it's an economic choice that it's not worth the money at this time in comparison to other things we could be working on to improve this quality characteristic and that we've chosen to be here... Because what I don't want people to think is what Dr. Deming and Taguchi are talking about is we can spend any amount of money to achieve any quality goal without thinking of the consequences, nor thinking about, how does this goal on this thing in isolation, not make things bad elsewhere. So we have to be thinking about a quality goal, whether it's worth achieving and will that achievement be in concert with other goals and what we're doing there? That's what I'd like people thinking about as a result of this podcast tonight.

0:28:56.0 AS: And I think I have a good way of wrapping this up, and that is going back to Dr. Deming's first of his 14 Points, which is, create constancy of purpose towards improvement of product and service with the aim to become competitive, to stay in business, and to provide jobs. And I think that what that... I link that to what you're saying with the idea that we're trying to improve our products and services constantly. We're not trying to improve one process. And also, to become competitive in the market means we're improving the right things because we will become more competitive if we are hitting what the client wants and appreciates. And so... Yeah.

0:29:46.3 BB: But with regard to... Absolutely with regard to our customers, absolutely with regard to how it affects different aspects of our company, that we don't get head over heels in one aspect of our company and lose elsewhere, that we don't deliver A+ products to the customer in a losing way, meaning that the A+ is great for you, but financially, we can't afford currently... Now, again, there may be a moment where it's worthwhile to achieve the A... We know we can achieve the A+, but we may not know how to do it financially. We may have the technology to achieve that number. Now, we have to figure out, is, how can we do it in an economically advantaged way, not just for you, the customer, but for us. Otherwise, we're losing money by delivering desirability. So it's gotta work for us, for you, but it's also understanding how that improvement... That improvement of that product within your overall system might not be worthwhile to your customer, in which case we're providing a... The classic...

0:31:18.8 AS: You're not becoming competitive then.

0:31:21.8 BB: The better buggy whip. But that gets into looking at things as a system. And this is... What's invaluable is, all of this is covered with a grasp of the System of Profound Knowledge. The challenge is not to look at goals in isolation. And even I've seen people at Lean conferences quote Dr. Deming and his constancy of purpose and I thought, well, you can have a... A non-Deming company has a constancy of purpose. [chuckle]  The only question is, what is the purpose? [laughter] And that's when I thought, a constancy of purpose on a focus on acceptability is good provided all of your competitors are likewise focusing on acceptability. So I just be... I just am fascinated to find people taking Deming's 14 Points one at a time, out of context, and just saying, "Well, Dr. Deming said this." Well, there we go again. [laughter]

0:32:29.9 AS: Bill, on behalf of everyone at The Deming Institute, I want to thank you again for this discussion. For listeners, remember to go to deming.org to continue your journey. If you want to keep in touch with Bill, just find him on LinkedIn. 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."

In this episode, Bill Bellows and Andrew Stotz discuss David Garvin's 8 Dimensions of Quality and how they apply in the Deming world. Bill references this article by Garvin: https://hbr.org/1987/11/competing-on-the-eight-dimensions-of-quality

TRANSCRIPT

0:00:02.4 Andrew 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 Bill Bellows, who has spent 31 years helping people apply Dr. Deming's ideas to become aware of how their thinking is holding them back from their biggest opportunities. This is the Misunderstanding Quality series, episode two, The Eight Dimensions of Quality. Bill, take it away.

0:00:30.4 Bill Bellows: Welcome back, Andrew. Great to see you again. All right, episode two, we're moving right along. So in episode one, which the title I proposed, waiting to see what comes out, the title I proposed was, Quality, Back to the Start. And that was inspired by some lyrics from Coldplay. Anyway, but this is a, it's going back to my start in quality and last time I mentioned discovering Taguchi's work long before I discovered Dr. Deming. In fact, Gipsie Ranney, who is the first president of the Deming Institute, the nonprofit formed by Dr. Deming and his family just before he passed away, and Gipsie became the first president and was on the board when I was on the board for many years. And I spoke with her nearly every day, either driving to work or driving home. And once, she calls me up and she says, "Bill," that was her Tennessee accent, "Bill."

0:01:50.5 BB: She says, "It says on The Deming Institute webpage that you infused Dr. Taguchi's work into Dr. Deming's work," something like that, that I... Something like I infused or introduced or I brought Taguchi's work into Deming's work, and I said, "Yes." I said, "Yeah, that sounds familiar." She says, "Isn't it the other way around?" That I brought Deming's work into Taguchi's work. And I said, "No, Gipsie," I said, "It depends on your starting point. And my starting point was Dr. Taguchi." But I thought it was so cool. She says, "Bill don't you have it? Don't you... " She is like, "Isn't it the other way around?" I said, "No, to me, it was all things Taguchi, then I discovered Dr. Deming." But I was thinking earlier before the podcast, and I walked around putting together how, what I wanna talk about tonight. And I thought, when I discovered Taguchi's work, I looked at everything in terms of an application of Dr. Taguchi's ideas.

0:03:29.7 AS: And one question about Taguchi for those people that don't know him and understand a little bit about him, was he... If I think about where Dr. Deming got at the end of his life, it was about a whole system, the System of Profound Knowledge and a comprehensive way of looking at things. Was Taguchi similar in that way or was he focused in on a couple different areas where he really made his contribution?

0:04:03.9 BB: Narrower than Dr. Deming's work. I mean, if we look at... And thank you for that... If we look at Dr. Deming's work in terms of the System of Profound Knowledge, the elements of systems psychology, variation, theory of knowledge, Taguchi's work is a lot about variation and a lot about systems. And not systems in the sense of Russ Ackoff systems thinking, but variation in the sense of where's the variation coming from looking upstream, what are the causes of that variation that create variation in that product, in that service?

0:04:50.9 BB: And then coupled with that is that, how is that variation impacting elsewhere in the system? So here I am receiving sources of variation. So what I deliver it to you has variation because of what's upstream of me and Taguchi's looking at that coupled with how is that variation impacting you? So those are the systems side, the variation side. Now, is there anything in Deming, in Taguchi's work about psychology and what happens when you're labelling workers and performance appraisals and, no, not at all.

0:05:37.6 AS: Okay, got it.

0:05:38.4 BB: Is there anything in there about theory of knowledge, how do we know that what we know is so? No, but there's a depth of work in variation which compliments very much so what Dr. Deming was doing. So anyway, so no. And so I discovered Taguchi's work, and I mentioned that in the first episode. I discovered his work, became fascinated with it, started looking at his ideas in terms of managing variation to achieve incredible... I mean, improved uniformity to the extent that it's worthwhile to achieve. So we were not striving for the ultimate uniformity, it's just the idea that we can manage the uniformity. And if we... And we'll look at this in more detail later, but for our audience now, if you think of a distribution of the variation in the performance of a product or a service, and you think in terms of... It doesn't have to be a bell-shaped distribution, but you have a distribution and it has an average and it has variation.

0:06:50.4 BB: What Dr. Taguchi's work is about in terms of a very brief, succinct point here in episode two is how might we change the shape of that distribution? How might we make it narrower, if that's a worthwhile adventure? It may be worthwhile to make it wider, not just narrower, but in both cases, we're changing the shape of the distribution and changing the location. So Taguchi's work, Taguchi's Methods, driven by variation comes to me, variation impacts you is how do I change the shape and location of that distribution? So on a regular basis, as I became more fascinated with that, I started thinking about, well, how might I apply Taguchi's ideas to these things that I encountered every day? Well, prior to that before discovering Taguchi's work, when I was a facilitator in problem solving and decision making training, I did the same thing, Andrew.

0:07:52.4 BB: I started looking at, oh, is this a problem? Is this a decision? Is this a situation that needs to be appraised? And so prior to that, what I was thinking about is when I was just a heat transfer analyst working on my Ph.D., I didn't look at how the heat transfer stuff affected all these other aspects of my lives. I didn't think about it when I went into a supermarket, but there was something about the problem solving and decision making that just infatuated me. And I would look at, oh, is Andrew talking about a decision or is Andrew talking about a problem? So I started hearing things. And so when I went into Taguchi's work, it was the same thing. And then shifting into Deming's work, it's the same thing. And I've... There's nothing else that I've studied that I look at things through those lenses. Anyway, so in studying, getting exposed to Taguchi, I mentioned that I had some time away from work, I went out on medical for some reasons and went and bought a book, a bunch of books.

0:09:02.4 BB: And one of the books I bought by David Garvin had come out in 1987, is entitled "The Eight Dimensions of Quality." There's a Harvard Business Review article that I wanna reference in this episode, and I'll put a link to the article. It's a free link. And so when you hear people talk about a quality product or a quality service or quality healthcare. We think in terms of it's quality as things, it's either good quality or bad quality or high quality, or somebody calls it low quality, or we just say it's a quality product. But what does that mean? So what I find is very loosely, we think in terms of categories of quality, good, bad, high, low. What we'll look at in a future episode is what would happen if we thought about quality on a continuum, which I believe Taguchi's work really demonstrates vividly as well as Dr. Deming's work.

0:10:07.4 BB: But even to back up before we talk about the eight dimensions of quality, I wanted to give some background on the word quality. The word quality, and this comes from an article and I'll put a link to this article, I wrote it for the Lean Management Journal a number of years ago, the word quality has Latin roots, beginning as qualitas, T-A-S, coined by the Roman philosopher and statesman, Marcus Tullius Cicero. He later became an adversary of this bad guy named Mark Antony. You've heard of him. Feared by Antony, this guy was feared by Antony because his power of speech led, you know what it led to, Andrew, his power of speech?

0:10:54.5 AS: What?

0:10:54.6 BB: His beheading.

0:10:55.8 AS: Oh my goodness.

0:10:56.5 BB: So for those of you with great powers of speech, watch out for your Mark Antony. But meanwhile, he introduced fellow Romans to the vocabulary of qualitas, quantitas, quantity, humanitas, humanities, essentia, which is, essence, he also is credited with an extensive list of expressions that translate into English today. Difference, infinity, science, morale. Cicero spoke of qualitas with his peers when focusing on the essential nature, character or property of an object. And this is kind of interesting. I mean, you can count how many apples do we have. And again, he came up with the term quantitas for quantity, but he is also talking about the essence of the apples. That's the quality word. And then 2000 years later when writing "The New Economics", Dr. Deming provided his definition and a little bit different.

0:12:05.3 BB: He says, "The problem anywhere is quality. What is quality?" Says the good doctor, "A product or service possesses quality if it helps somebody, it enjoys a good and sustainable market." And I said in the article, "As with Cicero, Deming saw quality as a property." And then some other background on quality before I talk about Garvin, "long after Cicero and well before Deming, quality as a property was a responsibility of guilds." Guilds. I mean, now we have writers guilds, we have actors guilds, and it's kind of cool that these guilds still exist and they are associations of artisans who control the practice of their craft, each with a revered trademark. So here in Los Angeles, we have writers guilds, actors guilds. They were organized as professional societies, just like unions.

0:13:00.2 BB: And these fraternities were developed, and within these fraternities they created standards for high quality. All right. So what is this quality management stuff from David Garvin? So this article was written 37 years ago and reviewing it for tonight's episode and I thought it fit in really, really well. I was reminded of... First time I read this article, 1989, I knew a lot about... Well, I knew, I was excited about Taguchi as I knew a lot about Taguchi, didn't know a lot about Dr. Deming. So I'm now reviewing it years later with a much deeper, broader Deming perspective than at that time. But I do believe, and I would encourage the listeners to get ahold of the article, look at it, if you wanna go into more depth, there's Garvin's book. And doing some research for tonight, I found out that he passed away in 2017, seven or so years ago.

0:14:04.6 BB: He was, I guess from, most of his career and education he was at the Harvard Business School, very well respected there. And so in the article it talks about, again, this, 1987, that's the era of Total Quality Management. That's the era in which Dr. Deming was attracting 2000 people to go to his seminars. 1987 is two years before Six Sigma Quality, two years before “The Machine That Changed The World.” And in the article, he says, "Part of the problem, of course, is that Japanese and European competition have intensified. Not many companies tried to make quality programs work even as they implemented them." This is back when quality was an era of quality circles. He says, "In my view, most of the principles about quality were narrow in scope. They were designed as purely defensive measures to preempt failures or eliminate defects, eliminate red beads."

0:15:10.3 BB: "What managers need now is an aggressive strategy to gain and hold markets with high quality," there we go again, "as a competitive linchpin." All right. So in the article, he has some interesting explanations of... Highlights. In the book is more depth. He talks about Joseph Juran, "Juran's Quality Handbook". Juran observed that quality could be understood in terms of avoidable and unavoidable costs. Dr. Deming talked about the economics. The New Economics, right? But Juran is looking at avoidable, unavailable costs resulting from defects in product failures. That's very traditional quality today.  The latter associated with prevention, inspection, sampling, sorting, quality control. And so this is what I found fascinating, is 37 years later, this is still the heavy sense of what quality is all about. Avoiding failure, avoiding defects.

0:16:18.3 BB: Then he talks about Total Quality Control coming from Armand Feigenbaum, who was a big name in the '80s. Again Dr. Deming's work kind of created this big quality movement but it wasn't just Dr. Deming people discovered, they discovered Philip Crosby in a Zero Defects advocacy, Feigenbaum, Juran, sometime later. Again, mid '80s, Dr. Taguchi's name started to be heard. All right. And then the reliability. All right. Now I wanna get into the... Oh, here's, this is good. "In 1961, the Martin Corporation, Martin Company was building Pershing missiles for the US Army. The design of the missile was sound, but Martin found that it could maintain high quality only through massive inspection programs."

0:17:13.0 BB: You know what Dr. Deming would say about inspection? It's after the fact. Sorting the good ones from the bad ones after the fact. No prevention there. But Martin found that it could only do it with inspection. And decided to offer... Again, this is 1961, and this is still the solution today, decided to offer workers incentives to lower the defect rate. And in December, 1961, delivered a Pershing missile to Cape Canaveral with zero discrepancies. Buoyed by this success, Martin's general manager in Florida accepted a challenge issued by the Army's missile command to deliver the first Pershing missile one month ahead of schedule. He went even further, he promised that the missile would be perfect. Perfect. You know what that means, Andrew?

0:18:12.3 AS: Tell us.

0:18:12.8 BB: All good, not bad.

0:18:14.9 AS: All good, not bad.

0:18:15.9 BB: He promised missile would be perfect with no hardware problems or document errors, and that all equipment would be fully operational 10 days after delivering. And so what was neat in going back to this is we still have this mindset that quality is about things being good, not bad. What is bad we call that scrap, we call that rework. That's alive and well today.

0:18:45.0 AS: The proclamations are interesting when you listen to what he's saying, when you're quoting that.

0:18:52.4 BB: Yeah, no, and I remember, 'cause again, I read this recently for the first time in 37 years and I'm going through it. And at the time I was thinking, "Wow, wow, wow, this is a really big deal. This is a really big deal." Now I look at it and say, "This is what we're still talking about today, 37 years later." The absence of defects is the essence of quality. All right. But so I would highly recommend the article. Now we get into what he proposes as eight critical dimensions of quality that can serve as a framework for strategic analysis. And I think even in a Deming environment, I think it's... I think what's really cool about this is it provides a broad view of quality that I think Deming's work fits in very well to, Dr. Taguchi's work fits in very well to, and I think covers a lot of what people call quality. So the first dimension he talks about is performance.

0:20:01.4 BB: And he says, "Of course, performance refers to a product's primary operating characteristics." He says, "For an automobile, performance would include traits like acceleration, handling, cruising speed. For a television, sound and picture clarity." He says "A power shovel in the excavation business that excavates 100 cubic yards per hour will outperform one that excavates 10 cubic yards per hour." So the capacity, that could be miles per gallon, carrying capacity, the resolution of the pixels, that's what he calls performance. Okay. Features is the second dimension of quality. Examples include free drinks on an airplane, but not if you're flying a number of airlines they charge you for those drinks, permanent press cycles on a washing machine, automatic tuners on a color television set. A number of people in our audience won't know what those are, bells and whistles. Features are bells and whistles.

0:21:17.2 BB: There was a time people would say the number of cup holders in your automobile, a feature could be intermittent wipers. So these are features. So again, I mean, so performance is kind of cool. What is the capacity, is it 100 horsepower, 200 horsepower, that's performance. Features, bells and whistles. Okay. Fine. Reliability, now we're talking. The dimension represents the probability of a product malfunctioning or failing within a specified period of time. So your car breaking down, are you gonna drive to work every day and one morning you're gonna go out and it's... That's a reliability issue. Okay. That's... When I think about reliability, that's a Taguchi thing, that's a Deming thing.  And looking at time between failures, okay, fine. Reliability comes down to... And if importance for the impact of downtime, if you're looking at engines not working and you're sitting at the gate, that's a reliability issue. The reliability is, it can be repaired, but it's gonna take some time, perhaps. Conformance. All right.

0:22:40.4 AS: Is number four, right?

0:22:42.2 BB: This is number four, a related dimension of quality is conformance or the degree to which a product's design and operating characteristics meet established standards. "This dimension owes to the importance of traditional approaches," it says, "to quality pioneers such as Juran." All products and services involve specifications of some sort. When new designs or models are developed, dimensions are set for parts or purity, these specifications are normally expressed as a target or a center. Now it's starting to sound a little bit like Dr. Taguchi's work, an ideal value, deviance from the center within a specified range. But this approach equates good quality with operating inside the tolerance band. There is little interest in whether the specifications have been met exactly. For the most part, dispersion within specifications is ignored. Ignored. That's balls and strikes, Andrew, balls and strikes.

0:23:51.2 BB: As long as the ball is somewhere in the strike zone, as long as the characteristic is somewhere within requirements, conformance, this gets into what I talk about in terms of the question number one of quality management. Has the requirement been met, the requirement for the performance, the dimension, is it within requirements? And there's only two answers, yes or no. That's conformance. I used to think that the American Society for Quality might be better known as the American Society for the Preservation of Conformance. I find there's a lot of conformance thinking. I'm reminded of, I'm a member of the American Society for Quality as I'm on the Deming Medal Committee, so I have to be a member of ASQ. So I get a daily or every other day newsletter with comments and conformance is a big part of the conversation. Good parts and bad parts, scrap and rework. All right.

0:25:02.3 BB: Conformance is number four. And it's not to say there isn't a place for the conformance, but conformance is then again different from what Dr. Taguchi is talking about. All right. Durability, the measure of a product life. Durability has both economic and technical dimensions. Durability is how long does it work before I throw it away? So reliability is about, I can repair it. Okay. And that's an inconvenience. Durability is like light bulbs. It runs and runs or a refrigerator and someone says, "Well, it’s time for a new one." That's a durability issue. Okay. Durability is the amount of use you get before you haul it off to the junkyard. That's durability. Okay. Serviceability. And back in the '60s, now I'm dating myself, there would be commercials for... I don't know which television brand, but what they talked about is, and these would be commercials. Commercials on television as to "our TV is easy to repair." And I thought, is that a good thing?

[laughter]

0:26:22.4 AS: Is that a foreboding?

0:26:24.4 BB: Yeah. And so... But again, the last couple of days I had to fix the sprinkler system in the backyard. And here in California we have, everybody has a sprinkler system. In the East Coast, people have above ground sprinkler systems. Here, they're all below ground. You don't have to worry about the lines freezing, at least in Los Angeles. And so anyway, one of the valves broke and I thought I was gonna buy a new one and take some of the parts from the new one to put it into the old one. And that didn't quite work. And so meaning to say, serviceability on the design was awful. I couldn't service it.

0:27:11.5 BB: I had to replace the whole damn thing, which was a lot more work than I was expecting. Anyway, however they designed it, serviceability didn't seem to be a consideration in the... That's dimension number six. Again, not to say there's anything wrong with thinking about serviceability. In terms of... Yeah. Okay, I'll leave it with that. Okay, serviceability. Number seven, aesthetics. The final two dimensions of quality are the most subjective, aesthetics, how a product looks, feels, sounds, taste, or smells is clearly a matter of personal judgment. Nevertheless, there seem to be patterns, a rich and full flavor aroma.

0:28:01.0 BB: That's got nothing to do with Dr. Taguchi's work. I mean, you can go off and do market research, find out what is the most appealing flavor, the most appealing taste, the most appealing aroma. And this is what I used to tell students is, and once you understand that or that vivid color that attracts the customer, then you could use Dr. Taguchi's work for, how can I reliably, predictably recreate, week after week, day by day, car by car, that aroma, that flavor, but Taguchi's work is not gonna tell you what it is. And then the last dimension of quality, you ready, Andrew?

0:28:45.8 AS: Give it to me, Bill.

0:28:47.7 BB: Perceived quality. "Consumers do not always have complete information on a product's attributes and direct measure is maybe their only basis. A product's durability can seldom be observed." And so we talk about perceptions of quality. Again, this is 1987, he says, "For this reason, Honda, which makes cars in Marysville, Ohio, and Sony, which builds color TVs have been reluctant to publicize that their products..." Ready? "Are made in America." Because the perception in 1987 is we want them to be made in Japan. And then we could talk about the perception of Cadillac quality, the perception of Jaguar quality.

0:29:35.7 BB: My father's gas station back in the early '70s, it was a block away from the nearby hospital. So a lot of our customers were doctors and they came in in their Cadillacs and Mercedes. And it was just a lot of fun. It was pretty cool. And one doctor against all of his peers' recommendations bought a Jaguar XJ12, V12, 12 cylinders, and they told him again and again, they said, "It'll spend more time in the shop than you driving it." No, no, no, he had to have one, he had to have one. And sure enough, it spent most of the time in the shop, but I got to drive it now and then, which was pretty cool. But that's perceived quality.

0:30:27.5 BB: So I just wanted to, in this episode, throughout those eight dimensions of quality. Again, I encourage our listeners, viewers, I think to get a broader sense of quality before you just look at quality from Dr. Deming's perspective, quality from anyone else's. I think that Garvin has done a really good job covering eight bases, if I can use that term, of quality. And then what I think is neat is to look at which of these tie into Deming's work, which of these tie into Dr. Taguchi's work? And that's what I wanted to cover in this episode.

0:31:01.8 AS: Fantastic. Well, let's just review that for the listeners and the viewers out there, eight dimensions. The first one is performance, the second one is features, the third one is reliability, the fourth one is conformance, the fifth one is durability, the sixth one is serviceability, the seventh one is aesthetics, how it feels and all that, and then the eighth one is perceived quality. Woah, that was...

0:31:29.4 BB: All about... Yeah. And it is reputation. You either have a great reputation or not.

0:31:38.3 AS: All right. Well, Bill, on behalf of everyone at the Deming Institute, I want to thank you again for this discussion. For listeners, remember to go to deming.org to continue your journey. And if you wanna keep in touch with Bill, just find him on LinkedIn. 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."

Where did your "quality journey" start? In this first episode of a new series on quality, Bill Bellows shares his "origin story," the evolution of his thinking, and why the Deming philosophy is unique.

TRANSCRIPT

0:00:02.3 Andrew Stotz: My name is Andrew Stotz, and I'll be your host as we continue our journey in the teachings of Dr. W Edwards Deming. Today, I'm continuing my discussion with Bill Bellows, who has spent 31 years helping people apply Dr. Deming's ideas to become aware of how their thinking is holding them back from their biggest opportunities. This is a new series called Misunderstanding Quality, and the topic for today is Quality Management, what century are we in? Bill, take it away.

0:00:35.7 Bill Bellows: Thank you, Andrew. [chuckle] All right.

0:00:39.5 AS: Exciting. I'm excited to hear what you've got going on in your mind about this Misunderstanding Quality.

0:00:45.6 BB: Well, first let me say that whether you're new to quality or looking for ideas on quality and quality management, quality improvement, quality management, the aim I have in mind for this podcast series is to improve your ability to manage quality through deepening your appreciation of the Deming philosophy and how to apply it. But specifically, a focus on quality, time after time, which is where most people heard about Deming, was through Quality, Productivity and Competitive Position. For example, the title of his first book. And relative to the title, what came to mind is an anecdote shared with me by two mentors that both spent a good deal of time with Dr. Deming. The first, Gipsie Ranney, who was a professor of statistics at University of Tennessee when she met Dr. Deming, went on to become a senior statistical consultant to GM and the first president of the Deming Institute, when Dr. Deming and his family, shortly before he died, formed a nonprofit called The Deming Institute. Gipsie and I used to speak literally every day, driving to work, driving home, we... "What's up, what's up?" And we always... It was so cool. I wish I had the recordings. Anyway, she once shared that she once asked Dr. Deming, "What do they learn in your seminars? What do attendees learn in your seminars?" To which she said Dr. Deming said, "I know what I said, I don't know what they heard."

[laughter]

0:02:26.0 BB: And along those lines, in the same timeframe, Bill Cooper who just turned 90, he and my wife share a birthday. Not the same year. Bill turned 90 last November and he was senior civilian at the US Navy's aircraft overhaul facility in San Diego, known as North Island. So as aircraft carriers are coming into San Diego, which is like the... I think they call it... It's like the headquarters of the Pacific Fleet. So as aircraft carriers are coming back, planes for which the repair work cannot be done on the carriers fly off to North Island. And Bill was in charge of, he said, some 5,000 civilians. And his peer on the military side, Phil Monroe was in charge of all the military people, and they got exposed to Dr. Deming's work in the early '80s, went off, left there, became Deming consultants. Anyway, Bill said he once asked Dr. Demings, says, "What percent of the attendees of your seminars walk away really understanding what you said?" And he said... Bill said Dr. Deming said, "A small percentage."

[laughter]

0:03:44.0 BB: And so what I had in mind in this series is... One is, what makes it hard to understand what Dr. Deming is talking about? And so for the listeners, what I'm hoping we can help you understand, what might be some invisible challenges that you're having in your organizations trying to explain this to others. So maybe you think your understanding is pretty good, but like Dr. Deming, maybe people are having a hard time understanding what you're saying. And I know what it's like to be in a room, presenting to people. And I had that same experience. I had one Rocketdyne executive... Rocketdyne was sold a few times. Every time it got sold, our Deming transformation efforts got set back a few years. So when the latest management team came in six, seven years ago, I met with one of the very top people, was explaining... Trying to explain to him for the first time what we had accomplished with some, I thought, absolutely amazing work by managing variation as a system. And he said something like, "So are people rejecting what you're saying?" And I said, "No, that's not it." He says, "So they're accepting what you're saying?" I said, "Well... " he said, "What's the problem?" I said, "What they accepted is not what I said." [laughter]

0:05:19.5 BB: I said, we're not in disagreement, but what they think they heard is... And that's when I found that I've experienced that. So anyway, so I wanted to get some background. So my first exposure to quality circles, and this is like... So I was living in this parallel universe, a heat transfer engineer working on rocket engines, and Quality comes into the organization. And unbeknownst to me, there's this quality movement going on, inspired by Dr. Deming, and we're on this wave. I had no idea. All I know is all of a sudden, we got Quality Circles, quality teams, every department...

0:06:03.8 AS: What year was that, roughly?

0:06:06.1 BB: 1984.

0:06:08.9 AS: Okay.

0:06:10.5 BB: Yeah. And I remember a book I was... I remember there was a pamphlet... You mentioned that. The company was AVCO, A-V-C-O, the Aviation Corporation, which is nearly as old as the Boeing Company. So it was one of the... So, Boeing gets into airplanes, the Wright Brothers get into airplanes, people are... Investors getting in, and AVCO, A-V-C-O, was formed by someone you likely heard of, Averill Harriman, major Wall Street guy at the time. And so anyway, I remember there being an AVCO book on quality circles. As you mentioned, I remember seeing that. And I remember just going along for the ride. I'm new to corporations, I'm just a subject matter expert in gas turbine heat transfer, and we're going to the... We got these things called quality circles, whatever. And I remember our department formed... Our department was a team, we had goals, and I remember going to these quality meetings, and let's say the goal would be that we read an article about heat transfer or something. I was just kind of fumbling with this thing called quality circles.

0:07:28.6 BB: But I remember, looking over the shoulder of the department secretary with a IBM Selectric typewriter, and this is before PCs, so we're using IBM 3270, dumb terminals. And I remember being over near the secretary, Kathy, and she's typing away the weekly activity reports, Friday morning kind of thing. And on a routine basis, I'd be over there and she'd be typing along. And then on the very last page, under the title, "Quality Circles," she would type in "Quality Circles are progressing as planned." [chuckle] 'Cause then these would be distributed to people in the department. So I'm watching her now create the next original. And it dawns on me, two things. One is, it's the very last topic in the meeting, in the weekly minutes, and two is it's the same damn thing every time, "Quality Circles are on plan." And I remember saying to her, "Why don't we just have that printed into the stationary?" [laughter]

0:08:39.5 BB: This is before I knew... For me, quality was just a seven-letter word. I don't know. So this is my exposure. And I remember thinking one of the quality goals we're thinking of in our department is... I think somebody even really brought this up, is we're gonna answer the phone by the second ring. That's gonna be our quality goal. And then, I remember we're negotiating for cleaning services. The floors were a mess. Tile floors, they were just a mess. And I remember in our department, we were lobbying to get better janitorial services, have the things cleaned more often. And next thing, we're negotiating with the VP of Engineering relative to, "Well, if your quality circles are on track, then I'll think about that." And it was just like... So it's some really ugly memories [chuckle] of this whole quality thing.

0:09:34.3 BB: But then I got into... I mentioned on the very first of our previous podcast, getting involved as a problem solving decision-making facilitator. I was hanging out with the HR training people, they had some... Their director of training, our director of training was a very astute guy and he was... I'm convinced, having met many people in that role, he knew what was going on. He knew a lot of the names in quality, not so... He knew of Deming's name, he knew of De Bono's name, Kepner-Tregoe, but he seemed to know his stuff. He's a fun guy to be with. And so, that's likely where I first heard Deming's name and that first book would've been Quality, Productivity and Competitive Position, which is... It's almost impenetrable, but I can remember at some point looking at that.

0:10:29.7 BB: But anyway, but in the fall of '87, I started being assigned a taskforce as helping... 'cause now I'm a problem-solving facilitator. But I still don't know... I don't know what quality is. All I know is I get invited to help solve problems. And we were looking at a very bad wear problem, these gears wearing each other out, enormous visibility to the Pentagon, because the tank engines we were making, 120 a month, were being shipped to the tank plant. And then, these tanks with these engines were being sent... The majority of them, sent to Europe. And they were the frontline of defense in Western Europe. This is the Cold War, Andrew.

0:11:17.4 AS: Right.

0:11:19.2 BB: And so the problem that came up was that a couple of these tanks had these gears wear through each other within 50 hours. And I've never been on such a high visibility taskforce because the Generals concern was that every one of those tanks was likely to not operate. And that might be the opportunity for the "Russki's" to launch World War III, because, what a great time, the tanks... If they knew these tanks weren't working. So it was a lot of stress, a lot of pressure. And after months of slow progress, the Army said, "Hey, why don't you guys go look at this Taguchi thing. The transmission people from General Motors who make the tank transmission, anytime they have a snafu like this, they use this Taguchi stuff." So I got assigned the action to go look at that. And I remember, this is pre-internet. And somehow, I did a literature search. I remember it was through something called Nerac, N-E-R-A-C. And out comes these pages. And the thing on Taguchi was... So first of all, who is this Taguchi guy?

0:12:29.0 BB: What is this quality stuff? I don't know. I'm a problem solving guy. And then I remember the first article on reference to Taguchi says, "Quality is the minimum of loss imparted to society by a product after a shipment to the customer." And I thought, "What does that mean?" So I don't know what... I mean, minimum of... I'm thinking... And I thought, "This can't be anything." So anyway, went out to General Motors and got exposed to what they were doing, and a few years later, realized it wasn't exactly Taguchi, but it was... There's some nuances there. But anyway, they exposed me to Design of Experiments and what's known as fractional factorial testing. And coupled with shifting how we look at the measurement process, we solved this problem within weeks, a problem that had been going on for months. So then I got excited about... This Taguchi thing's kind of cool. I'm liking this. And it was a lot more exciting than what I was doing. And I thought, "I think I wanna do this." So the following year, I went to the Taguchi conference. So we had the application and I was so excited, Andrew, that I was turned down for funding. The Army would have paid for me to go to this conference, 'cause the Army, by that point, had invited me to work on at least two problems.

0:13:54.4 BB: Once we solved the first one, when problems came up, the Army literally turned to the program management people at Lycoming and said, "Do a Taguchi study, get Bill Bellows involved." So I was walking on water. I thought it was kind of cool. So I wanted to go to this Taguchi conference, and it was turned down. And they said, "It's not your job." So I told my boss when they told me it was gonna be turned down, I said, "I'm going to this conference." I said, "Whether the company pays for it or not, I am going." So I drove 14 hours each way to Detroit. And in the room are all the US experts on Taguchi's ideas at the time. I didn't know who Deming was at the time. I still didn't know what quality was, but I walked outta there thinking, "This is what I wanna do." And then, where I'm getting to is, a few months later, I was gonna go out on medical I had surgery planned.

0:14:53.1 BB: I was gonna be out for about two months. So my wife and I lived in New Haven, maybe 10 miles north of Yale. And I remember going to the... Again, this is pre-Amazon. I mean, talk about dating ourselves. What century are we in? So I remember going with my wife to the Yale bookstore, the Yale co-op bookstore, and every book they had on quality, I bought. And I'm gonna sit home for two months and read all these books. And I remember buying books. I'm pretty sure I got books about Deming, some about Taguchi, some by Phil Crosby about Zero Defects. Six Sigma Quality entry was a year away.

0:15:35.7 BB: And so I sat down... I got out of the hospital, I'm resting at home, sitting on the couch every day and reading, and also calling the Taguchi people that I had met, I think, at the previous conference. I met some big names. So I'm reading the books, calling them up. And again, these are like my personal professors. And I remember saying to a few of them... What blew me away, and I don't... It somehow dawned on me, I was naive. In the world of engineering, we use... Most of my exposure, at least in heat transfer, we use the same terms the same way. We talk about radiation heat transfer, conduction heat transfer, convection heat transfer. So many of the terms are the same terms, so we can have a conversation. So I'm thinking the same thing applies in quality, that we're all like the heat transfer people. It's easy to communicate 'cause we got the same models. We're using the same words the same way. Then I started thinking, I'm no longer... And this is a real shock. I'm no longer thinking we're using the same words the same way, hence my introduction to misunderstanding quality, [laughter] or I would say, the beginning of a journey to better understand the... I think there are incredible opportunities for people in quality organizations, or people that wanna get into quality.

0:17:08.3 BB: I think it's an ideal opportunity to introduce Deming's ideas. And I say that because everybody else is doing their own thing. Engineering's off designing, Manufacturing's off producing, and Quality has an incredible opportunity to bring together Deming's sense of a systems view of quality. Nobody else has that charter. So my hope is in our conversations, we can help people that are trying to do some things, whether it's jumpstart their continuous improvement program or get their quality program out of what it currently is. In fact...

0:17:52.4 AS: By the way, I wanna...

0:17:55.9 BB: Go ahead, go ahead.

0:17:56.0 AS: I wanna ask a question about that, because what you've mentioned is interesting, that the systems aspect... Is that unique? Would you say that's unique to Deming? I mean, if we think about Taguchi and I think about the Taguchi Method, I'm thinking about a really powerful tool for understanding variation. But explain what you mean by that.

0:18:24.0 BB: A couple of things come to mind when you ask that question. One is the predominant explanation of quality. And if we have time, I wanna talk about that. The term quality, "qualitas," comes from Cicero, a Roman in ancient times. But by and large, in manufacturing, in corporate quality, in corporations, the operational definition, what do we mean by quality? This thing is... What are Quality organizations doing? And what I find they're doing is calling balls and strikes. They're looking at a given quality characteristics, whether it's the fuel economy of an engine, of a gas turbine engine, the performance, the thrust level of a rocket engine, the diameter of a hole, and asking, "Does that characteristic of surface roughness diameter, does it meet a set of requirements?"

0:19:30.4 BB: And the requirements are typically set... There's a lower one and an upper one. We don't say the meeting is gonna start at 10 o'clock, because if you understand variation, we can't get exactly 10. We can't get exactly 1.00 inch thickness for the plate, for the hole diameter. So then, we define quality. Typically, this is what people do in organizations. This is what I... I didn't know anything about this until I started... Well, what are quality people doing? They're asking, "Does this thing meet requirements?"

0:20:07.4 BB: And even towards that end, I remember asking a... I had a coworker who's a quality engineer, I've got many friends who are quality engineers, and this one guy came into a class one day that I was doing, and he's just beating his head against the wall over... I said, "What's...what have you been doing lately." He says, "All I'm doing Bill is dispositioning hardware, dispositioning hardware," which translates to trying to find out why something doesn't meet requirements and coming up with a corrective action, or buying it as is. So either changing the requirements or explaining why we can use it as is. But he's just like, "That's all I'm doing lately. I'm just getting overwhelmed with all this." So I said, "Well, what if overnight, by some miracle, you were to come in, and beginning first thing tomorrow morning, everything meets requirements." And that's the goal of quality in most organizations, is that everything meets requirements. So I said, "If everything beginning tomorrow morning, through some overnight miracle, meets requirements, hence forth, how would your life change?" He says, "I wouldn't have a job." [laughter]

0:21:26.9 BB: I said, "What other changes would you begin to see throughout the day, the coming days?" He says, "My boss's job wouldn't exist." I said, "Okay, keep going, keep going." He says, "Well, the whole organization will have no reason to exist." [laughter] And that's not farfetched. And I throw that out, the challenge to our listeners is, seriously, if everything in the organization beginning tomorrow morning met requirements through some... Dr. Deming would say as you know, by what method? Let's say the method exists, what would change? Now, I'm not saying these people necessarily get laid off. Maybe they get moved elsewhere. Maybe we set our sights higher and try to do things we've never done before, 'cause now everything's gonna be a home run. But that's what I find in corporations, I think, a very extremely commonplace 21st century Andrew explanation of quality is, "Does it meet requirements?" And that goes... And this whole idea of setting requirements, setting a lower and an upper, allowing for variation, that goes back to the early 1700s. And I've also read that it might go back even longer in China. We were talking earlier about China.

0:22:58.2 BB: And so if it goes back longer, all the better. And the point being, fast forward to today, that's largely where we are today, in this early 1700s. Does it meet requirements? Yes or no? And what Dr. Deming is talking about is not acceptability. First of all, he would say there's a place for acceptability. There's a place for meeting requirements, maybe based on the circumstances, all that matters is that it meets requirements. So if you're a pitcher and you're throwing a ball and the batter can't hit the ball, and as long as it's somewhere in the strike zone, or if you're kicking the ball into the net in a football match or otherwise known as soccer in the States, maybe the goalkeeper's so bad, all you gotta do is... They'll jump out of the way.

0:23:49.7 BB: Now, on the other hand, there may be a different batter or a different goalkeeper where you've gotta go where they aren't. And that gets into understanding variation and where we are in meeting requirements matters. And what I find is most organizations I've ever interacted with, and this is through Rocketdyne, as owned by Boeing, going to many different divisions of Boeing around the country, doing seminars across England, across New Zealand, university classes and university lectures, hundreds of them. I've never come across... With rare exception have I ever come across anyone who says, "Bill, in our organization, quality is more like what Dr. Deming is talking about." Meaning, "We are doing more than meeting requirements, we are focusing on where the ball is placed in the strike zone, where the ball is placed in the net, and we specialize in that because we have seen great advantage." Most people I present this to don't even know that's a possibility, don't even know it's anything to lobby for.

0:25:12.0 BB: And so to that I'd say, whether you're looking at Operational Excellence, which is kind of a hybrid of Lean and Six Sigma or Six Sigma alone, or Lean alone, everything I've studied in all of those go back to the question of quality being... Quality's defined Phil Crosby-wise, which is striving for zero defects, striving for everything meeting requirements, and then we're done. And when I joined The Deming Institute, part of my excitement was helping the organization differentiate Dr. Deming's ideas over these other quality management ideas and other management ideas as uniquely positioned to differentiate, to understand that there's an opport... There are incredible opportunities for realizing that everything that meets requirements is not the same. And how do we put a value on that? And one is, the better we understand that, the better we can minimize scrap and rework problems if we're paying attention to where we are, if the process is in control, if we can use that concept from variation. And then simultaneously, another...

0:26:35.7 BB: There's two opportunities. One is, I think the better we manage variation, the less likely we're gonna have scrap and rework. Wouldn't that be great? And two is that that buys us time to think about... 'cause now that we're not in that constant firefighting mode, now we can start to think about how to manage variation of the system and to improve how things integrate. And we did both of those at Rocketdyne. But I've yet to find many organizations who say, "Been there, done that. Been there, done that."

0:27:12.1 AS: So, if we think about the takeaways for someone listening or watching this, you've talked about Misunderstanding Quality, you've talked about everything meet requirements, you've talked about, what century are we in? So, what should they take back to their business from this discussion that can give them a foundation of a starting point of this series and what you're saying on this point? What do you want them to take away?

0:27:40.3 BB: First, I would say I wouldn't necessarily go tell anybody about this yet. [laughter] I'd say, "Hmm, this Deming stuff. There's something to this. What I'm hearing from Bill is there's something here that I can't get elsewhere." You can listen to our prior sessions. There's 22 of them. We're gonna be adding new aspects to that...

0:28:07.9 AS: Okay. So, let's talk about that for a second. So, learn on your own first. Maybe it's a personal transformation. Start with that?

0:28:09.9 BB: Yes.

0:28:14.8 AS: Okay.

0:28:16.1 BB: Absolutely... Yes, absolutely...

0:28:18.1 AS: What would be number two that you want them to get away from this?

0:28:22.9 BB: Well, my advice is, you're not crazy that there's things about the Deming philosophy that are unique, that are... I think so much... There's a lot of people excited by what Dr. Deming's offering. I think there's more than meets the eye. I mean...

0:28:46.1 AS: Okay, so let's talk about that for a second. So, there's unique things about Deming, and one of them that you talked about is the systems thinking?

0:28:54.6 BB: Yeah. I mean, imagine... What I liken it to, instead of zero defects being the goal, which is what most organizations are striving for, and their quality systems are about, "We wanna get zero defects over here, over here, over here." We're juggling all these places, trying to get to zero defects all over the place. What if they saw zero defects as not the destination, but the starting point? That, to really understand continual improvement, zero defects is not the goal. Imagine that as the starting point. At least, imagine the ability to go across that apparent finish line and realize... Or the analogy I would use is, go through the door called "zero defects is the end," and realize there's a lot more, there's so much more to do when you start to look at things with a Deming view. And so, instead of thinking, we're striving for zero defects and then we're done, to me, that's the starting point to really begin to appreciate what it means to look at systems.

0:30:07.7 AS: Okay. So we've got, start with your own personal transformation and learn the material, and understand that there's some unique things about the Deming teachings, in particular, systems. And understand that... I kind of visualized while you were talking, a person walking along with no knowledge of many things, but they're inquisitive, and what they find is a wrench. And then they start to find that there's ways to use this wrench in their daily life. And then later, they find that there's other tools like a screwdriver. And all of a sudden, they found this world of tools, and now they have this amazing toolbox. But then all of a sudden, they meet someone that's taking those tools and creating a car, or a this, or a that. And then they realize, maybe the tool has gotta be the starting point, or is a starting point. But what the tools can create and what additional tools can create is so much bigger than just that first wrench that you picked up.

0:31:14.2 BB: It's the appreciation. And I'm glad you brought those points up. Dr. Deming talks about tools and techniques. A control chart is a tool. A run chart is a tool. Design of Experiments are... These are tools. And so that's a tool. A technique is, how do we create a control chart? That's a technique. What I try to do with audiences, whether it's clients or university classes or whatever, is help them differentiate. Tools and techniques are about improving efficiency, doing things well. Doing something faster or cheaper... What's unique to Dr. Deming is not the tools you'll find him talking about, but the concepts he's talking about, and the idea of looking at things as a system. Dr. Deming defines quality, and it can be obtuse for people. I find it fascinating. He says, "Product or service possesses quality if it helps someone and enjoys a sustainable market." So, traditional quality is me throwing the ball to you, Andrew, or passing a football or basketball, whatever it is, and judging the quality of the pass when the ball leaves my hand. And we say, "That was a good pass."

0:32:49.9 BB: What Dr. Deming's talking about is, it's a good pass, just as if it's a good conversation, if you can hear what I say, we can go back and forth. And so, Deming's perspective on quality is not what's good for me, the producer, but it's how well does it fit you that I'm delivering something that matches... That we're synchronous, that... It has to be good for you, not just me checking off and saying, "This is good, this is good, this is good. Boom." That it's not good until you say it's good. That's a different view. It's the same thing as, "Well, I told you." Then you say, "Well, I didn't hear it." I says, "Well, then why don't you have your ears checked?" [laughter] Dr. Deming's talking about, it's not a conversation if you can't hear it. And so, when he's explaining to Bill Cooper and Gipsie that people are having a hard time, he was struggling to improve that 'cause he knew that when you begin to understand that what you're saying is not heard, Deming understood it was his obligation to try harder. And part of the Deming philosophy is understanding that it's not just me throwing it and saying, "There it is." It's listening for the feedback as to, "Did it make sense?" So, quality in that arena is a mutual phenomenon, not unilaterally my thing.

0:34:16.7 AS: Okay.

0:34:17.8 BB: And I would welcome anyone, as we've done in the past, to reach out if there are questions, comments, observation you'd like to share, and we can use that feedback in future sessions.

0:34:30.6 AS: Fantastic. Well, that's an excellent kickoff. And let's end with the idea that quality is a mutual phenomenon. I think that's a good statement. So Bill, on behalf of everyone at The Deming Institute, I want to thank you again for this discussion. And for listeners, remember to go to deming.org to continue your journey. And if you want to keep in touch with Bill, just find him on LinkedIn. 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."

In the final episode of the goal setting in classrooms series, John Dues and Andrew Stotz discuss the last three of the 10 Key Lessons for implementing Deming in schools. They finish up with the example of Jessica's 4th-grade science class.

TRANSCRIPT

0:00:02.4 Andrew 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 John Dues, who is part of the new generation of educators striving to apply Dr. Deming's principles to unleash student joy in learning. This is episode six about goal setting through a Deming lens. John, take it away.

0:00:26.4 John Dues: Hey, Andrew, it's good to be back. Yeah, for the past handful of episodes or so, we've been talking about organizational goal setting. We covered these four conditions of healthy goal setting and then got into these 10 key lessons for data analysis. And then we've been looking at those 10 key lessons applied to an improvement project. And we've been talking about a project that was completed by Jessica Cutler and she did a Continual Improvement Fellowship with us here at our schools. And if you remember, Jessica was attempting to improve the joy in learning of her students in her fourth grade science class. So last time we looked at lessons five through seven. Today we're gonna look at those final three lessons, eight, nine and ten applied to her project.

0:01:15.7 AS: It's exciting.

0:01:17.1 JD: Yeah. So we'll jump in here. We'll kind of do a description, a refresher of each lesson. And we'll kind of talk about how it was applied to her specific project, and we'll look at some of her data to kind of bring that live for those of the folks that have video. Let's jump in with lesson number eight. So we've talked about this before, but lesson number eight was: more timely data is better for improvement purposes. So we've talked about this a lot. We've talked about something like state testing data. We've said, it can be useful, but it's not super useful for improvement purposes, because we don't get it until the year ends. And students in our case, have already gone on summer vacation by the time that data comes in. And you know that the analogous data probably happens in lots of different sectors where you get data that lags, to the point that it's not really that useful for improvement purposes.

0:02:15.8 JD: So when we're trying to improve something, more frequent data is helpful because then we can sort of see if an intervention that we're trying is having an effect, the intended effect. We can learn that more quickly if we have more frequent data. And so it's, there's not a hard and fast rule, I don't think for how frequently you should be gathering data. It just sort of needs to be in sync with the improvement context. I think that's the important thing. Whether it's daily or a couple times a day or weekly, or monthly, quarterly, whatever, it's gotta be in sync with whatever you're trying to improve.

0:02:50.5 AS: You made me think about a documentary I saw about, how they do brain surgery and how the patient can't be sedated because they're asking the patient questions about, do you feel this and they're testing whether they're getting... They're trying to, let's say, get rid of a piece of a cancerous growth, and they wanna make sure that they're not getting into an area that's gonna damage their brain. And so, the feedback mechanism that they're getting through their tools and the feedback from the patient, it's horrifying to think of the whole thing.

0:03:27.7 JD: Yeah.

0:03:28.3 AS: It's a perfect example of why more timely data is useful for improvement purposes 'cause imagine if you didn't have that information, you knock the patient out, you get the cancerous growth, but who knows what you get in addition to that.

0:03:43.7 JD: Yeah, that's really interesting. I think that's certainly an extreme example, [laughter], but I think it's relevant. No matter what our context, that data allows us to understand what's going on, variation, trends, whether our system is stable, unstable, how we should go about improving. So it's not dissimilar from the doctors in that example.

0:04:06.8 AS: And it's indisputable I think, I would argue. But yet many people may not, they may be operating with data that's not timely. And so this is a reminder that we would pretty much always want that timely data. So that's lesson eight. Wow.

0:04:22.6 JD: Lesson eight. Yeah. And let's see how we can, I'll put a visualization on the screen so you can see what Jessica's data look like. All right. So now you can see. We've looked at these charts before. This is Jessica's process behavior chart for joy in science. So just to reorient, you have the joy percentage that students are feeling after a lesson on the x-axis, sorry, on the y-axis. On the x-axis, you have the school dates where they've collected this survey information from students in Jessica's class.

0:04:57.0 AS: Can you put that in Slide Show view?

0:05:00.4 JD: Yeah. I can do that. Yeah.

0:05:02.7 AS: Just it'll make it bigger, so for the...

0:05:06.5 JD: There you go.

0:05:07.8 AS: For the listeners out there, we're looking at a chart of daily, well, let's say it looks like daily data. There's probably weekends that are not in there because class is not on weekends, but it's the ups and downs of a chart that's ranging between a pretty, a relatively narrow range, and these are the scores that are coming from Jessica's surveying of the students each day, I believe. Correct?

0:05:34.2 JD: Yeah. So each day where Jessica is giving a survey to assess the joy in science that students are feeling, then she's averaging all those students together. And then the plot, the dot is the average of all the students sort of assessment of how much joy they felt in a particular science lesson.

0:05:54.7 AS: And that's the average. So for the listeners out there John's got an average line down the middle of these various data points, and then he is also got a red line above and a red line below the, above the highest point and slightly below the lowest point. Maybe you can explain that a little bit more.

0:06:15.4 JD: Yeah. So with Jessica, you remember originally she started plotting on a line chart or a run chart when we just had a few data points just to kind of get a sense of how things are moving so she could talk about it with her class. And over time what's happened is she's now got, at this point in the project, which she started in January, now this is sort of mid-March. And so she's collected two to three data points a week. So she doesn't survey the kids every day just for time sake, but she's getting two, three data points a week. And so by March, she started just a couple months ago, she's got 28 data points. So that sort of goes back to this idea of more timely data is better for improvement.

0:07:00.9 JD: And a lot of times, let's say a school district or a school does actually survey their students about how, what they think of their classes. That might happen at best once a semester or maybe once a year. And so at the end of the year you have one or two data points. So it's really hard to tell sort of what's actually going on. Compared to this, Jessica's got these 28 data points in just about two months or so of school. So she's got 28 data points to work with. And so what her and her students are doing with this data then, one, they can see how it's moving up and down. So we have, the blue dots are all the plotted points, like you said, the green line is the average running sort of through the middle of the data, and then those red lines are our process limits, the upper and lower natural process limits that sort of tell us the bounds of the system.

0:07:50.4 JD: And that's based on the difference in each successive data point. But the most important thing is that as Jessica and her students are looking at this, initially, they're really just studying it and trying to sort of see how things are going from survey to survey. So one of the things that Deming talked about frequently is not tampering with data, which would be if you sort of, you overreact to a single data point. So let's say, a couple of days in, it dips down from where it started and you say, oh my gosh, we gotta change things. And so that's what Deming is talking about. Not tampering, not overreacting to any single data point. Instead look at this whole picture that you get from these 28 data points and then talk about...

0:08:41.5 JD: In Jessica's case she's talking about with her students, what can we learn from this data? What does the variation from point to point look like? If we keep using the system, the fourth grade science system, if we leave it as is, then we'll probably just keep getting data pretty similar to this over time, unless something more substantial changes either in the negative or the positive. So right now they...

0:09:10.1 AS: And I think for the listeners, it's, you can see that there's really no strong pattern that I can see from this. It's just, there's some, sometimes that there's, seems like there's little trends and stuff like that. But I would say that the level of joy in the science classroom is pretty stable.

0:09:32.1 JD: Pretty stable. Yeah. Pretty high. It's bouncing around maybe a 76% average across those two and a half months or so. And so, they, you kind of consider this like the baseline. They've got a good solid baseline understanding of what joy looks like in this fourth grade science classroom. Did that stop sharing on your end?

0:10:00.2 AS: Yep.

0:10:00.2 JD: Okay, great. So that's lesson eight. So clearly she's gathered a lot of data in a pretty short amount of time. It's timely, it's useful, it's usable, it can be studied by her and her students. So we'll switch it to lesson nine now. So now they've got a good amount of data. They got 28 data points. That's plenty of data to work with. So lesson nine is now we wanna clearly label the start date for an intervention directly in her chart. And remember from earlier episodes, not only are we collecting this data, we're actually putting this up on a screen on a smart board in the classroom, and Jessica and her students are studying this data together. They're actually looking at this, this exact chart and she's explaining sort of kind of like we just did to the listeners. She's explaining what the chart means.

0:10:54.2 JD: And so over time, like once a week she's putting this up on the smart board and now kids are getting used to, how do you read this data? What does this mean? What are all these dots? What do these numbers mean? What do these red lines mean? That type of thing. And so now that they've got enough data, now we can start talking about interventions. That's really what lesson nine is about. And the point here is that you want to clearly, explicitly with a literally like a dotted line in the chart to mark on the day that you're gonna try something new. So you insert this dashed vertical line, we'll take a look at it in a second, on the date the intervention started. And then we're also gonna probably label it something simple so we can remember what intervention we tried at that point in time.

0:11:42.7 JD: So what this then allows the team to do is then to very easily see the data that happened before the intervention and the data that happened after the implementation of this intervention or this change idea. And then once we've started this change and we start plotting points after the change has gone into effect, then we can start seeing or start looking for those patterns in the data that we've talked about, those different rules, those three rules that we've talked about across these episodes. And just to refresh, rule one would be if we see a single data point outside of either of the limits, rule two is if we see eight consecutive points on either side of that green average line, and rule three is if we see three out of four dots in a row that are closer to one of the limits than they are to that central line.

0:12:38.3 JD: So that again, those patterns tell us that something significant, mathematically improbable has happened. It's a big enough magnitude in change that you wouldn't have expected it otherwise. And when we see that pattern, we can be reasonably assured that that intervention that we've tried has worked.

0:12:56.0 AS: And let me ask you about the intervention for just a second because I could imagine that if this project was going on, first question is, does Jessica's students are, obviously know that this experiment is going on?

0:13:08.3 JD: Yes.

0:13:09.8 AS: Because they're filling out a survey. And my first question is, do they know that there's an intervention happening? I would expect that it would be yes, because they're gonna feel or see that intervention. Correct?

0:13:25.1 JD: Sure. Yep.

0:13:25.2 AS: That's my first point that I want to think about. And the second point is, let's imagine now that everybody in the classroom has been seeing this chart and they're, everybody's excited and they got a lot of ideas about how they could improve. Jessica probably has a lot of ideas. So the temptation is to say, let's change these three things and see what happens.

0:13:46.5 JD: Yeah.

0:13:47.1 AS: Is it important that we only do one thing at a time or that one intervention at a time or not? So maybe those are two questions I have in my mind.

0:13:58.6 JD: Yeah, so to the first question, are you, you're saying there there might be some type of participant or...

0:14:02.3 AS: Bias.

0:14:03.3 JD: Observer effect like that they want this to happen. That's certainly possible. But speaking to the second question, what intervention do you go with? Do you go with one or you go with multiple? If you remember a couple of episodes ago we talked about, and we actually looked at a fishbone diagram that Jessica and her students that they created and they said, okay, what causes us to have low joy in class? And then they sort of mapped those, they categorized them, and there were different things like technology not working. If you remember, one was like distractions, like other teachers walk into the room during the lesson. And one of them was others like classmates making a lot of noise, making noises during class and distracting me. And so they mapped out different causes. I think they probably came up with like 12 or 15 different causes as possibilities.

0:14:58.7 JD: And they actually voted as a class. Which of these, if we worked on one of these, which would have the biggest impact? So not every kid voted for it, but the majority or the item that the most kids thought would have the biggest impact was if we could somehow stop all the noises basically. So they came up with that as a class, but not, it wasn't everybody's idea. But I think we've also talked about sort of the lessons from David Langford where once kids see that you're gonna actually take this serious, take their ideas serious and start acting on them, they take the project pretty seriously too. So maybe not a perfect answer, but that's sort of what we...

0:15:38.0 AS: I was thinking that, ultimately you could get short-term blips when you do an intervention and then it stabilizes possibly. That's one possibility. And the second thing I thought is, well, I mean ultimately the objective, whether that's an output from a factory, and keeping, improving that output or whether that's the output related to joy in the classroom as an example, you want it to go up and stay up and you want the students to see it and say, wow, look, it's happening. So, yeah.

0:16:11.7 JD: And there's different ways you can handle this. So this joy thing could go up to a certain point. They're like, I don't know if we can get any more joy, like, it's pretty high. And what you could do at that point is say, okay, I'm gonna assign a student to just sort of, every once in a while, we'll keep doing these surveys and we will sort of keep plotting the data, but we're not gonna talk about a lot. I'm just gonna assign this as a student's job to plot the new data points. And we'll kind of, we'll kind of measure it, but we won't keep up with the intervention 'cause we got it to a point that we're pretty happy with. And now as a class we may wanna switch, switch our attention to something else.

0:16:45.2 JD: So we started getting into the winter months and attendance has dipped. Maybe we've been charting that and say, Hey guys, we gotta, gotta kinda work on this. This is gone below sort of a level that's really good for learning. So let's think about as a group how we could come up with some ideas to raise that. So maybe you turn your attention to something else, 'cause you can't pay attention to everything at once.

0:17:07.2 AS: Yeah, and I think I could use an example in my Valuation Master Class Boot Camp where students were asking for more personal feedback and I realized I couldn't really scale this class if I had to get stuck into hundreds of grading basically. And that's when I came up with the concept of feedback Friday, where one student from each team would present and then I would give feedback, I would give a critique and they would be intense and all students would be watching, it would be recorded, and all of a sudden all the issues related to wanting this personal feedback went away. And therefore, once I instituted it on a regular basis, I went on to the next issue and I made sure that I didn't lose the progress that I had made and continue to make feedback Friday better and better.

0:17:56.2 JD: Yeah. Yeah. That's great. That's great. I'll share my screen so you can kinda see what this looked like in Jessica's class now, what the chart looks like now. So now you see that same chart, that same process behavior chart, exact same one we were just looking at except now you can see this, this dashed vertical line that marks the spot where the intervention was started that we just talked about. And what the kids are actually doing, and Jessica are running a PDSA cycle, a Plan-Do-Study-Act cycle. That's the experimental cycle in her class. And what they're running that PDSA on is, again, how can we put something in place to reduce the distracting noises. And so what the students actually said is if we get a deduction for making noises, then there will be less noises. And so in the school's sort of management system, a deduction is sort of like a demerit.

0:19:00.0 JD: If you maybe went to a Catholic school or something like that, or some public schools had demerits as well, but basically it's like a minor infraction basically that goes home or that gets communicated to parents at the end of the week. But the kids came up with this so their basic premise is, their plan, their prediction is if there are less noises, we'll be able to enjoy science class. And if we give deductions for these noises, then there'll be less noises. So some people may push back, well, I don't think you should give deductions or something like that, but which, fine, you could have that opinion. But I think the powerful point here is this is, the students created this, it was their idea. And so they're testing that idea to see if it actually has impact.

0:19:44.8 JD: And they're learning to do that test in this scientific thinking way by using the Plan-Do-Study-Act cycle, and seeing if it actually has an impact on their data. So at the point where they draw this dashed line, let's call that March 19th, we can see a couple of additional data points have been gathered. So you can see the data went up from 3/18 to 3/21. So from March 18th to March 21st, rose from about, let's call it 73% or so, up to about 76% on March 21st. And then that next day it rose another percent or two and let's call that 78%.

0:20:28.1 JD: And so the trap here is you could say, okay, we did this intervention and it made things better. But the key point is the data did go up, but we haven't gathered enough additional data to see one of those patterns that we talked about that would say, oh, this actually has had a significant change. Because before the dashed line, you can see data points that are as high or even higher than some of these ones that we see after the PDSA is started. So it's too early to say one way or another if this intervention is having an impact. So we're not gonna overreact. You could see a place where you're so excited that it did go up a couple of days from where it was on March 18th before you started this experiment, but that's a trap. Because it's still just common cause data, still just bouncing around that average, it's still within the bounds of the red process limits that define the science system.

0:21:34.2 AS: I have an experiment going on in my latest Valuation Master Class Boot Camp, but in that case, it's a 6-week period that I'm testing, and then I see the outcome at the end of the six weeks to test whether my hypothesis was right or not. Whereas here it's real time trying to understand what's happening. So yes, you can be tempted when it's real time to try to jump to conclusion, but when you said, well, okay, I can't really get the answer to this conclusion until I've run the test in a fixed time period, then it's you don't have as much of that temptation to draw a conclusion.

0:22:14.1 JD: Yeah. And if I actually was... I should have actually taken this a step farther. I marked it with this Plan-Do-Study-Act cycle. What I should have done too is write "noises" or something like that, deduction for noises, some small annotation, so it'd be clear what this PDSA cycle is.

0:22:32.1 AS: In other words, you're saying identify the intervention by the vertical line, but also label it as to what that intervention was, which you've done before on the other chart. I remember.

0:22:42.1 JD: Yeah. And then it'd be sort of just looking at this when she puts this up on the smart board for the class to see it again too. Oh yeah yeah, that's when we ran that first intervention and that was that intervention where we did deductions for noises. But the bigger point is that this never happens where you have some data, you understand a system, you plan systematic intervention, and then you gather more data right after it to see if it's having an impact. We'd never do that ever, in education, ever. Ever have I ever seen this before. Nothing like this. Just this little setup combining the process behavior chart with the Plan-Do-Study-Act cycle, I think is very, very, very powerful and very different approach than what school improvement.

0:23:33.4 AS: Exciting.

0:23:34.6 JD: Yeah. The typical approach is to school improvement. So I'll stop that share for a second there, and we can do a quick overview of lesson 10 and then jump back into the chart as more data has been gathered. So lesson 10 is: the purpose of data analysis is insight. Seems pretty straightforward. This is one of those key teachings from Dr. Donald Wheeler who we've talked about. He taught us that the best analysis is the simplest analysis, which provides the needed insight.

0:24:08.1 AS: So repeat lesson 10, again, the purpose of...

0:24:11.6 JD: The purpose of data analysis is insight.

0:24:14.7 AS: Yep.

0:24:15.6 JD: So just plotting the dots on the run chart and turning the run chart into the process behavior chart, that's the most straightforward method for understanding how our data is performing over time. We've talked about this a lot, but it's way more intuitive to understand the data and how it's moving than if you just stored it in a table or a spreadsheet. Got to use these time sequence charts. That's so very important.

0:24:42.2 AS: And I was just looking at the definition of insight, which is a clear, deep, and sometimes sudden understanding of a complicated problem or situation.

0:24:51.6 JD: Yeah. And I think that can happen, much more likely to happen when you have the data visualized in this way than the ways that we typically visualize data in just like a table or a spreadsheet. And so in Jessica's case, we left off on March 22nd and they had done two surveys after the intervention. And so then of course what they do is they continue over the next 4, or 5, 6 weeks, gathering more of that data as they're running that intervention, then we can sort of switch back and see what that data is looking like now.

0:25:28.3 AS: Exciting.

0:25:30.3 JD: So we have this same chart with that additional data. So we have data all the way out to now April 11th. So they run this PDSA for about a month, three weeks, month, three, four weeks.

0:25:47.9 AS: And that's 11 data points after the intervention. Okay.

0:25:54.0 JD: Yep. Purposeful. So what was I gonna say? Oh, yeah. So three, four weeks for a Plan-Do-Study-Act cycle, that's a pretty good amount of time. Two to four weeks, I've kind of found is a sweet spot. Shorter than that, it's hard to get enough data back to see if your intervention has made a difference. Longer than that, then it's you're getting away from the sort of adaptability, the ability to sort of build on an early intervention, make the tweaks you need to. So that two to four week time period for your PDSA seems like a sweet spot to me. So she's continued to collect this joy in learning data to see... Basically what her and her class are doing is seeing if their theory is correct. Does this idea of giving deductions for making noises have an impact? Is it effective?

0:26:44.0 JD: So if they learn, if the data comes back and there is no change, no indication of improvement, then a lot of people will say, well, my experiment has failed. And my answer to that is, no, it hasn't failed. It might not have worked like you wanted, but you learn very quickly that that noise deduction is not going to work and we're gonna try some other thing, some other intervention. We learn that very very quickly within 3 or 4 weeks that we need to try something new. Now, in the case of Jessica's class, that's not what happened. So you can actually see that dotted line, vertical dotted line is still at March 19th, we have those 11 additional data points. And you can actually see, if you count, starting with March 21st, you count 1-2-3-4-5-6-7-8-9-10-11 data points that are above that green average line from before.

0:27:45.5 JD: So originally the red lines, the limits and the central line would just be straight across. But once I see that eight or more of those are on one side of that central line, then I actually shift the limits and the average line, 'cause I have a new system. I've shifted it up and that actually is an indication that this intervention has worked, because we said... Now for those that are watching, it doesn't appear that all the blue dots are above that green line, but they were before the shift. Remember the shift indicates a new system. So I go back to the point where the first dot of the 8 or more in a row occurred, and that's where I have indicated a new system with the shift in the limits and the central line. So this, their theory was actually correct. This idea of giving a deduction for noises actually worked to improve the joy in Jessica's science class. It was a successful experiment.

0:28:52.7 AS: Can I draw on your chart there and ask some questions?

0:29:00.5 JD: Sure. Yeah.

0:29:00.6 AS: So one of my questions is, is it possible, for instance, in the preliminary period, let's say the first 20 days or so that things were kind of stabilized and then what we saw is that things potentially improved here in the period before the intervention and that the intervention caused an increase, but it may not be as significant as it appears based upon the prior, the most recent, let's say 10 days or something like that. So that's my question on it. I'll delete my drawings there.

0:29:46.3 JD: Yeah, I think that's a fair question. So, the reason I didn't shift those before, despite you do see a pattern, so before the dotted line, I considered that period a baseline period where we were just collecting 'cause they hadn't tried anything yet. So Dr. Wheeler has these series of four questions. So in addition to seeing a signal, he's got these other sort of questions that he typically asks and that they're yes/no questions. And you want the answer to all those to be yes. And one of 'em is like, do you know why an improvement or a decline happened? And if you don't, then you really shouldn't shift the limits. So that's why I didn't shift them before. I chose not to shift them until we actually did something, actually tried something.

0:30:33.2 AS: Which is basically saying that you're trying to get the voice of the students, a clear voice, and that may be that over the time of the intervention, it could be that the... Sorry, over the time of the initial data gathering, that the repetition of it may have caused students to feel more joy in the classroom because they were being asked and maybe that started to adjust a little bit up and there's the baseline, so. Yep. Okay.

0:31:01.6 JD: Yeah. And so this is sort of where the project ended for the fellowship that Jessica was doing. But, what would happen if we could sort of see what happened, further out in the school year is that, either Jessica and the class could then be sort of satisfied with where the joy in learning is at this point where the improvement occurred. Or they could run another cycle, sort of testing, sort of a tweaked version of that noise reduction PDSA, that intervention or they could add something to it.

0:31:43.0 AS: Or they could have run another fishbone point, maybe the noise wasn't actually the students thought it would be the number one contributor, but, maybe by looking at the next one they could see, oh, hey, wait a minute, this may be a higher contributor or not.

0:32:01.2 JD: Yeah. And when you dug into the actual plan, the specifics of the plan, how that noise deduction was going to work, there may be something in that plan that didn't go as planned and that's where you would have to lean on, 'cause we've talked about the three sort of parts of the improvement team that you need. You need the frontline people. That's the students. You need the person with the authority to change the system. That's Jessica. And then someone with the knowledge of the system, profound knowledge. That's me. Well, those, the Jessica and her students are the one in that every day. So they're gonna have learning about how that intervention went, that would then inform the second cycle of the PDSA, whatever that was gonna be, whatever they're gonna work on next. The learning from the first cycle is gonna inform that sort of next cycle.

0:32:51.4 JD: So the idea is that you don't just run a PDSA once but you repeatedly test interventions or change ideas until you get that system where you want it to be.

0:33:01.1 AS: So for the listeners and viewers out there, I bet you're thinking gosh, Jessica's pretty lucky to have John help her to go through this. And I think about lots of things that I want to talk to you about [laughter] about my testing in my own business, and I know in my own teaching, but also in my business. So that I think is one of the exciting things about this is the idea that we just, we do a lot of these things in our head sometimes. I think this will make a difference and, but we're not doing this level of detail usually in the way that we're actually performing the tests and trying to see what the outcomes are.

0:33:43.9 JD: Yeah I think that for school people too, I think when we've attempted to improve schools, reform schools, what happens is we go really fast and the learning actually happens very slowly and we don't really appreciate what it actually takes to change something in practice. And what happens then is to the frontline people like teachers... The reformers have good intentions but the people on the front line just get worn out basically, and a lot of times nothing actually even improves. You just wear people out. You make these big changes go fast and wide in the system and you don't really know exactly what to do on the ground because the opposite is having Jessica's classroom. They're actually learning fast but trying very small changes and getting feedback right in the place where that feedback needs to be given right in the classroom and then they can then learn from that and make changes.

0:34:49.8 JD: And again, it may seem smaller. Maybe it doesn't seem that revolutionary to people but to me, I think it's a completely revolutionary, completely different way to do school improvement that actually kind of honors the expertise of the teacher in the classroom, it takes into account how students are experiencing a change and then I'm kind of providing a method that they can use to then make that classroom better for everybody so and I think in doing so students more likely to find joy in their work, joy in their learnings, teachers more likely to find joy in their work as well. So to me it's a win-win for all those involved.

0:35:34.9 AS: Fantastic. Well, should we wrap up there?

0:35:40.6 JD: Yeah, I think that's a good place to wrap up this particular series.

0:35:45.1 AS: And maybe you could just review for the whole series of what we've done just to kind of make sure that everybody's clear and if somebody just came in on this one they know a little bit of the flow of what they're gonna get in the prior ones.

0:36:00.4 JD: Yeah. So we did six episodes and in those six episodes we started off just talking about what do you need to have in place for healthy goal setting at an organizational level, and we put four conditions in place that before you ever set a goal you should have to understand the capability of your system, you have to understand the variation within your system, you have to understand if the system that you're studying is stable, and then you have to have a logical answer to the question by what method. By what method are you gonna bring about improvement or by what method you're gonna get to this goal that you wanna set. So we talked about that, you gotta have these four conditions in place and without those we said goal setting is often an act of desperation.

0:36:49.7 JD: And then from there what we did is start talking about these 10 key lessons for data analysis so as you get the data about the goal and you start to understand the conditions for that system of process we could use those 10 data lessons to then interpret the data that we're looking at or studying and then we basically did that over the first four episodes. In the last few episodes what we've done is look at those lessons applied to Jessica's improvement project and that's what we just wrapped up looking at those 10 lessons.

0:37:23.7 AS: I don't know about the listeners and viewers but for me this type of stuff just gets me excited about how we can improve the way we improve.

0:37:33.4 JD: Yeah. For sure.

0:37:34.9 AS: And that's exciting. So John, on behalf of everyone at the Deming Institute I want to thank you again for this discussion, and for listeners, remember to go to deming.org to continue your journey. You can find John's book Win-Win W. Edwards Deming, the System of Profound Knowledge and the Science of Improving Schools on amazon.com. 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."

In this episode, John Dues and Andrew Stotz apply lessons five through seven of the 10 Key Lessons for implementing Deming in classrooms. They continue using Jessica's fourth-grade science class as an example to illustrate the concepts in action. 

TRANSCRIPT

0:00:02.2 Andrew 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 John Dues, who is part of the new generation of educators striving to apply Dr. Deming's principles to unleash student joy in learning. This is episode five about goal setting through a Deming lens. John, take it away.

0:00:23.2 John Dues: Yeah, it's good to be back, Andrew. Yeah, like you said, for the past few episodes we've been talking about organizational goal setting. We covered four healthy conditions, or four conditions of healthy goal setting and 10 key lessons for data analysis. And then what we turn to in the last episode is looking at an applied example of the 10 key lessons for data analysis and in action. And, if you remember from last time we were looking at this improvement project from Jessica Cutler, she's a fourth grade science teacher, and she did the improvement fellowship here at United Schools Network, where she learned the tools, the techniques, the philosophies, the processes behind the Deming theory, continual improvement, that type of thing. And in... And in Jessica's specific case, in her fourth grade science class, what she was settled on that she was gonna improve was, the joy in learning of her students. And we looked at lessons one through four through the eyes or through the lens of her project. And today we're gonna look at lessons five through seven. So basically the next, uh, the next three lessons of those 10 key lessons.

0:01:34.8 AS: I can't wait. Let's do it.

0:01:37.3 JD: Let's do it. So lesson number five was: show enough data in your baseline to illustrate the previous level of variation. Right. So the basic idea with this particular lesson is that, you know, let's say we're trying to improve something. We have a data point or maybe a couple data points. We wanna get to a point where we're starting to understand how this particular concept works. In this case, what we're looking at is joy in learning. And there's some different rules for how many data points you should, should have in a typical base baseline. But, you know, a pretty good rule of thumb is, you know, if you can get 12 to 15, that's... That's pretty solid. You can start working with fewer data points in real life. And even if you just have five or six values, that's gonna give you more understanding than just, you know, a single data point, which is often what we're... What we're working with.

0:02:35.6 AS: In, other words, even if you have less data, you can say that this gives some guidance.

0:02:40.9 JD: Yeah.

0:02:41.1 AS: And then you know that the reliability of that may be a little bit less, but it gives you a way... A place to start.

0:02:46.9 JD: A place to start. You're gonna learn more over time, but at least even five or six data points is more than what I typically seen in the typical, let's say, chart where it has last month and this month, right? So even five or six points is a lot more than that. You know, what's... What's typical? So I can kind of show you, I'll share my screen here and we'll take a look at, Jessica's initial run chart. You see that right?

0:03:19.3 AS: We can see it.

0:03:21.2 JD: Awesome.

0:03:22.3 AS: You wanna put it in slideshow? Can we see that? Yeah, there you go.

0:03:24.9 JD: Yeah, I'll do that.

0:03:25.4 AS: Perfect.

0:03:26.3 JD: That works better. So, you know, again, what we're trying to do is show enough data in the baseline to understand what happened prior to whenever we started this improvement effort. And I think I've shared this quote before, but I really love this one from Dr. Donald Berwick, he said "plotting measurements over time turns out in my view to be one of the most powerful things we have for systemic learning." So what... That's what this is all about really, is sort of taking that lesson to heart. So, so you can look at Jessica's run chart for "joy in science." So just to sort of orient you to the chart. We have dates along the bottom. So she started collecting this data on January 4th, and this is for about the first 10 days of data she has collected. So she's collected this data between January 4th and January 24th. So, you know, a few times a week she's giving a survey. You'll remember where she's actually asking your kids, how joyful was this science lesson?

0:04:24.4 JD: Mm-hmm.

0:04:27.2 JD: And so this is a run chart 'cause it's just the data with the median running through the middle, that green line there, the data is the blue lines connected by, or sorry, the blue dots connected by the points and the y axis there along the left is the joy in learning percentage. So out of a hundred percent, sort of what are kids saying? How are kids sort of evaluating each of these science lessons? So we've got 10 data points so far, which is a pretty good start. So it's starting to give Jessica and her science class a decent understanding about, you know, when we, you know, define joy in science and then we start to collect this data, we really don't have any idea what that's gonna look like in practice. But now that she started plotting this data over time, we have a much better sense of what the kids think of the science lessons basically. So on the very first day...

0:05:25.4 AS: And what is the... What is the median amount just for the listeners out there that don't see it? What would be the... Is that 78%?

0:05:33.8 JD: Yeah, about 78%. So that very first day was 77%. The second day was about 68%. And then you sort of see it bounce around that median over the course of that, those 10 days. So some of the points are below the median, some of the points are above the median.

0:05:50.4 AS: And the highest point above is about 83, it looks like roughly around that.

0:05:54.4 JD: Yeah. Around 82, 83%. And one technical point is at the point that it's a run chart we don't have the process limits, those red lines that we've been taking a look at and with a run chart and, you know, fewer data points, we only have 10. It's fairly typical to use the median, just so you know, you can kind of better control for any outlier data points which we really don't have any outliers in this particular case but that's just sort of a technical point. So, yeah, I mean, I think, you know what you start to see, you start to get a sense of what this data looks like, you know, and you're gonna keep collecting this data over an additional time period, right? And she hasn't at this point introduced any interventions or any changes. Right now they're just learning about this joy in learning system, really. Right.

0:06:51.8 JD: And so, you know, as she's thinking about this, this really brings us to... To lesson six, which is, you know, what's the goal of data analysis? And this is true in schools and it's true anywhere. We're not just gonna look at the past results, but we're also gonna, you know, probably more importantly, look to the future and hopefully sort of be able to predict what's gonna happen in the future. And, you know, whatever concept that we're looking at. And so as we continue to gather additional data, we can then turn that run chart from those initial 10 points into a process behavior chart. Right. You know, that's a, sort of a, you know, it's the run chart on steroids because not only can we see the variation, which you can see in the run chart, but now because we've added more data, we've added the upper and lower natural process limit, we can also start to characterize the type of variation that we see in that data.

0:08:00.1 AS: So for the listeners, listeners out there, John just switched to a new chart which is just an extension of the prior chart carrying it out for a few more weeks, it looks like, of daily data. And then he's added in a lower and upper natural process limit.

0:08:18.9 JD: Yeah. So we're still, we're still plotting the data for joy in science. So the data is still the blue dots connected by the blue lines now because we have 24 or so data points, the green line, the central line is the average of that data running through the data. And we have enough data to add the upper and lower natural process limit. And so right now we can start to determine do we only have natural variation, those everyday ups and downs, that common cause variation, or do we have some type of exceptional or special cause variation that's outside of what would be expected in this particular system. We can start making...

0:09:00.7 AS: Can you...

0:09:02.2 JD: Go ahead.

0:09:02.8 AS: I was gonna... I was gonna ask you if you can just explain how you calculated the upper and lower natural process limits just so people can understand. Is it max and min or is it standard deviation or what is that?

0:09:18.3 JD: Yeah, basically what's happening is that, so we've plotted the data and then we use that data, we calculate the average, and then we also calculate what the moving range, is what it's called. So we just look at each successive data point and the difference between those two points. And basically there's a formula that you use for the upper and lower natural process limits that takes all of those things into account. So it's not standard deviation, but it's instead using the moving, moving range between each successive data point.

0:09:52.9 AS: In other words, the data that's on this chart will always fall within the natural upper and lower. In other words it's... Or is, will data points fall outside of that?

0:10:05.7 JD: Well, it depends on what kind of system it is.

0:10:07.8 AS: Right. Okay.

0:10:09.8 JD: If it's a stable system, that means all we see is sort of natural ups and downs in the data. And we use those formulas for the process limits. The magnitude of the difference of each successive data point is such that it's not necessarily big or small, it's just based on what you're seeing empirically. It's basically predictable. Right. And if it's not predictable, then we'll see special causes. So we'll see special patterns in the data. So I think maybe last time we talked about the three patterns, or you know, in some episode we talked about the patterns that would suggest there's a special cause that goes to the study. Those three patterns that I use are, is there a single one of these joy in science data points outside of either the upper or lower natural process limit that'd be a special cause.

0:11:05.4 JD: If you see eight data points in a row, either above the central line or below the central line, that's a special cause. And if I see three out of four in a row that are either closer to the upper limit or to the lower limit than they are to that central line, that's a pattern of the data that suggests a special cause. So we don't, in this particular dataset, we don't see any special causes. So now we have... Now we have a very solid baseline set of data. We have 24 data points. And when you're using an average central line and get... Getting technical, once you get to about 17 data points, those upper and lower natural process limits start to solidify, meaning they're not gonna really change too much 'cause you have enough data unless something really significant happens. And then if you're using the median, that solidification happens when you get to about 24 data points.

0:12:07.5 JD: So when you're, you know, when you're getting to 17 to 24 data points in your baseline, you're really getting pretty solid upper and lower national process limits. So, as of this March 1st date, which is the last date in this particular chart, there are 24 data points. So you have a pretty solid baseline set of data. Right now, the upper natural process limit is 95%. That lower limit is sitting at 66%, and then the average running through the middle, that green line is 81%. So this basically tells us that if nothing changes within Jessica's fourth grade science system, her classroom, we can expect the data to bounce around this 81% average and stay within the bounds of the limit. So we would call this a common cause system because we don't see any of those rules that I just talked about for special causes. And that's important.

0:13:07.4 JD: So do we have an unstable system or a stable system? We have a stable system. A stable system means that the data is predictable and unless something happens, you know, and this could be something that happens in the control of the teacher in the class, or it could be out of the control of the teacher in the class, but unless something happens that's significant, this data is just kind of keep humming along like this over the course of March, April, May of this particular school year. Right. So once we get to this point, so we have baseline data we've collected in a run chart, we start to understand how that data is moving up and down. We got some more data and we added the upper and lower natural process limits. Now we can assess not only the variation, but also the stability and the capability of the system, all of those things, those questions can start to be answered now that we have this process behavior chart.

0:14:09.3 JD: And this brings us to the final lesson for today, which is lesson 7, which is the improvement approach depends on the stability of the system under study. So that's why one of the reasons why the process behavior chart is so powerful is because now I have an understanding of what I need to do, like what type of approach I need to take to improve this particular system. Right? So in this particular case, I have a predictable system. And so the only way to bring about meaningful improvement is to fundamentally change this science system, right?

0:14:52.6 JD: The flip side would be if I did see a special cause let's say, it was an unpredictable system. We saw special cause on the low side. I'd wanna study that, what happened on that particular day. Because if I see a special cause, let's say on February 2nd I saw a special cause, let's say I saw a single data point below the lower natural process limit that's so different and unexpected, I'd actually wanna go to her classroom and talk to her in her class and say, okay, what happened on that day? I'm gonna try to remove that special cause. Study of that specific data point is warranted. If you don't see those special causes, then those, even though there are ups and downs, there are increases and decreases. They're within that, you know, the expected bounds of this particular system. Right.

0:15:46.9 AS: And I was gonna say, I can't remember if I got this from Dr. Deming or where it came from, but I know as an analyst in the stock market analyzing tons and tons of data in my career, I always say if something looks like a special cause or looks strange it's probably an error.

[laughter]

0:16:03.2 AS: And it could just be for instance, that a student came in and they didn't understand how to fill it out or they refused to fill it out or they filled out the form with a really bizarre thing, or maybe they thought that number 10 was good and number one was bad, but in fact on the survey it was number one that was good and number 10 that was bad. And you find out that, you know, that special cause came from some sort of error.

0:16:26.6 JD: That's certainly possible. That's certainly possible.

0:16:29.5 AS: As opposed to another special cause could be, let's just say that the school had a blackout and all of a sudden the air conditioning went off for half of the class and everybody was just like really frustrated. They were burning hot. It was really a hot day and that special cause could have been a legitimate cause as opposed to let's say an error cause but you know, it causes an extreme, you know response on the survey.

0:16:56.9 JD: Yeah. And the thing is, is yeah, it could be a number of different things. Maybe she tried, maybe she had gotten some feedback about her lessons and maybe even she tried a different lesson design and it was new to her and it just didn't work very well. Maybe she tried to use some new technology or a new activity and it just didn't go well. But you know, if I'm seeing that data show up as a special cause and let's say I'm seeing that the next day or a couple days later, it's still fresh in my mind and I can even go into my chart and label what happened that day. Okay. And I... Now, okay, I'm gonna remove that thing or I'm, you know, if it's a lesson I'm trying, maybe I don't wanna give up on it, but I know I need to improve it 'cause it led to some issues in my classroom, but it's close enough to the time it actually happened that I actually remember what happened on that particular day and I can sort of pinpoint that issue.

0:17:52.9 AS: Yeah.

0:17:54.5 JD: And the data told me it was worth going into studying that particular data point because it was so different than what I had seen previously in this particular 4th grade science system.

0:18:06.5 AS: Makes sense.

0:18:09.9 JD: But in this case, we don't see that, that was a hypothetical. So all we see is sort of the data moving up and down around that green average line. So we have a stable system. So again, that tells me I need to improve the science system itself. There's no special causes to remove. So, the next question I think I would ask, and if you remember one of the data lessons is that we sort of combine the frontline workers, which is the students in this case. We have the manager or the leader, that's the teacher, and then someone with profound knowledge from the Deming lens, that's me, we're bringing these people together and we're saying, okay, you know, we're seeing this hum along this joy in science thing, hum along at sort of like an 81% average. So I think it's a reasonable question to ask, is that good enough? And should we turn our attention to something else. Now, there could be some situations where it's not good enough or some situations where that is good enough. They chose to keep moving to improve that joy in learning. But I think it'd be perfectly reasonable in some context to say, well, you know, sure, maybe we could get a little better here, but maybe it's not worth the effort in that particular area. Maybe we're gonna turn our attention to something else. You know.

0:19:23.7 AS: So you learn something from the chart and that could be...

0:19:26.4 JD: Learn something from the chart. Yeah, yeah.

0:19:27.9 AS: Because when I look at this chart, I just think hard work is ahead.

0:19:31.2 JD: Yeah. Yeah.

0:19:34.7 AS: 'Cause in order to, if you have a stable system with not a lot of extreme... Firefighting is kind of a fun thing, right? When you got special causes, you feel really important. You go out there, you try to figure out what those individual things are, you're the hero. You fix it, you understand it, you see it, whatever. But then when you get a stable system, it's like, oh man, now we got to think about how do we make some substantial changes in the system. It doesn't have to be substantial, but how do we make changes in the system, you know? And then measure whether that has an impact.

0:20:06.4 JD: Yeah. And to your point about fire... Fighting fires, like I didn't know, we had never measured joy in learning like this before, so I didn't know what we were gonna get with Jessica. And so you know what I think you also see here is a pretty well-run classroom. These are kids that are finding a pretty high amount of joy in their lessons. I think that you can kind of objectively say that, but they did choose to move on with the project and keep focusing on this particular system. And I thought it was really interesting. They actually... I'll flip slides here.

0:20:45.6 JD: They actually made this sort of rudimentary fishbone diagram, so you can, if you're viewing the video here you can see that Jessica just took a pen and a piece of paper and put this on the overhead in the classroom, and basically just drew a fishbone. And on the fishbone diagram is also called a cause and effect diagram. So out on the right it says effect. And she wrote low enjoyment, so she's meaning low enjoyment of science class. And they started brainstorming, those are the bones of the fish, what's leading to what's causing the effect of low enjoyment in science class. And so they... She did this brainstorming activity with the kids. So some of the things they came up with were why is there low enjoyment with science class? Well, the computers are sometimes lagging when the kids are trying to use them. They're mad at Ms. Cutler for one reason or another. There's a lot of writing in a particular lesson. There's a lot of reading in a particular lesson.

0:21:58.2 AS: Other teachers coming into the room.

0:22:00.7 JD: Other teachers coming into the room and disrupting the class.

0:22:02.7 AS: Stop bothering me.

0:22:04.1 JD: Yeah. I mean, you know, these are the things you don't often think about. And then they talked about classmates making noises throughout classes, another distraction. And they basically categorized these into different categories. So there were sort of things that made the lesson boring. That was one category. Accidents happening, those are like the computers not working correctly. Scholar... We call our student scholars. So students getting in trouble was one, and then distractions was another category. And so then they did another activity basically after they had this fishbone. And they basically did like a voting activity where they would figure out which of these is the most dominant cause of low enjoyment. And actually what they came up with is their classmates call, like making noises, like students making a lot of noise, making noises, random noises throughout the lesson, they identified that particular thing as the thing that they're gonna then do something like design a plan, do study around, like how are we gonna reduce the amount of noise in the class?

0:23:12.7 JD: And this is all the students coming up with these ideas. Of course, Jessica's guiding these conversations as the adult in the room, but the kids are coming up with this. Like I never would have, well, maybe I shouldn't say I would never have, but it probably wouldn't likely have been on my radar that teacher, other teachers coming into the room was a main source of distraction. You know, who knows what they're doing, dropping off papers that have to be passed out, that dismissal or coming to find a kid for this thing or that thing. Who knows why they're stopping by. But schools are certainly rife with all kinds of disruptions, announcements, people coming into the room, those types of things.

0:23:51.0 AS: It's interesting too to see mad at Miss Cutler because... I was just reading a book about or some research about how to get rid of anger and that type of thing. And they talk about meditation and I do breathing exercise before every class, when every class starts. And it's a way of just kind of calming down and separating the class time from the chaos of outside, but it also could be something that could help with feeling mad.

0:24:27.9 JD: Yeah. And I think if in certain classrooms that certainly could have risen to the top. And then what you do is then design the PSA around that. So how do you do meditation? How do you know if you're going to do... How do you know if you're doing it right? How long do you do it? You know? Does it have the intended impact? You could study all kinds of different things with meditation, but...

0:24:52.4 AS: And are you really mad or is there... Are you really mad at Ms. Cutler or are you... Are you frustrated about something else? Or that...

0:24:58.1 JD: Exactly. Yeah. Is it warranted? Is there actually something that she should stop doing or start doing? There's all kinds of possibilities there. But the main point, and I think this kind of would bring us to the wrap up is taking this approach is very different. Even just the step, Jessica's step of saying, I'm gonna work on joy in science, joy in learning in science class. That's a very different approach. And then step beyond that, I'm gonna involve my students in this improvement approach. And we have these various methods and tools for systematically collecting the classes input, and that those are improvement science or continual improvement tools that we're using. And then we're applying some of the knowledge about variation, Deming sort of data methods to understand that data, that we've systematically collected from students.

0:25:58.7 JD: And now students are involved. So they're actively coming up with both the reasons, the problems that are happening. And then they're like what we'll get into in the last few lessons is their input into the solutions, the change ideas that are gonna make things better. But all of this represents a very different approach than what's typical when it comes to school improvement. These things are not being handed down from on high from someone that has no connection to this classroom whatsoever. Instead, it's actually the people in the classroom that are developing the solutions.

0:26:36.9 AS: I just was thinking about the idea of imagining that this group of students is working really hard on that, and they come up with so much knowledge and learning about how to create a more joyful classroom. And then imagine that they've now codified that together with Ms. Cutler to create kind of the standard operating procedures. Like we put up a sign on the door outside that says, do not disturb until class is over, or...

0:27:06.1 JD: Something simple. Yeah.

0:27:07.0 AS: And that they come up with, and a breathing exercise or whatever that is. And then you imagine the next group of students coming in for the next year, let's say, or whatever, that next group who can then take the learning that the first group had and then try to take it to another level, and then upgrade how the operations of the room is done. And you do that a couple of iterations, and you've now accumulated knowledge that you are building on until in a business, you're... You're creating a competitive advantage.

0:27:40.4 JD: Yeah, absolutely. And another thing that these guys did was they didn't say we're gonna improve X, Y, or Z and then set an arbitrary goal, which is one of the things we've talked about that often happens at the outset of any type of improvement. They didn't... They sort of avoided this act of desperation. We talk about goal setting as an active... Are often goal setting is often an act of desperation. They avoided that completely. Instead, what they did was we gathered some baseline data to understand what is the capability of our system when it comes to joy in learning. That's what they did first. They didn't set the goal first. A lot of wisdom, a lot of wisdom in 10 year olds for sure.

0:28:22.1 AS: That's interesting. Well, John, on behalf of everyone at the Deming Institute, I want to thank you again for the discussion and for listeners, remember to go to deming.org to continue your journey. You can find John's book Win-Win: W. Edwards Deming, the System of Profound Knowledge and the Science of Improving Schools on amazon.com. This is your host, Andrew Stotz, and I'll leave you with one of my favorite quotes from Dr. Deming, and its absolutely applicable to today's discussion. People are entitled to joy in work.