32 min

Goal Setting Is Often An Act of Desperation: Part 2 In Their Own Words

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Do you struggle to meet your goals or targets? Find out how you can change your thinking about goals and your process for setting them so you can keep moving forward. In this episode, John Dues and host Andrew Stotz discuss the first five of John's 10 Key Lessons for Data Analysis.
TRANSCRIPT
0:00:03.0 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 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 two of four in a mini-series on why goal setting is often an act of desperation. John, take it away.
 
0:00:32.3 John Dues: Hey, Andrew, it's good to be back. Yeah, in that last episode, that first episode in this mini-series, we talked about why goal setting is often an act of desperation and I basically proposed these four conditions that organizations should understand prior to setting a goal. So it's not the goals in and of themselves that are bad, but it's with this important understanding that's often lacking. So those four things that organizations should understand, one, what's the capability of a system under study? So that's the first thing, how capable is the system or the process? The second thing is what's the variation within that system or process under study? So that's the second thing we talked about last time. The third thing is understanding if that system or process is stable. And then the fourth thing was, if we know all of those things, by what method are we going to approach improvement after we set the goal, basically? So you gotta have those four things, understanding the capability of the system, the variation of the system, the stability of the system, and then by what method, prior to setting a goal. And so I think I've mentioned this before, but absent of an understanding of those conditions, what I see is goals that are, what I call it, arbitrary and capricious.
 
0:01:48.8 JD: That's a legal characterization. You look that up in the law dictionary. And it basically says that an "arbitrary and capricious law is willful and unreasonable action without consideration or in disregard of facts or law." So I'm just now taking that same characterization from a legal world and applying it to educational organizations and accountability systems, and I just switched it to "a willful and unreasonable goal without consideration or in disregard of system capability, variability, and/or stability." And we see these all over the place for education organizations, for schools, school districts, teachers, that type of thing.
 
0:02:31.6 JD: And so what I tried to do in the book and tried to do here in my work in Columbus is develop some sort of countermeasures to that type of goal setting and develop the 10 key lessons for data analysis. An antidote to the arbitrary and capricious goals seen throughout our sector. And this process behavior chart tool, looking at data in that format is central to these lessons. So what I thought we would do in this episode and the next is outline those 10 key lessons. So five today and then do another five in the next episode. And in the fourth episode of the series, what we would do is then apply those examples to a real life improvement project from one of our schools. It's helpful, I think too, to sort of, to understand the origin of the key lessons. So there's the lessons that I'll outline are really derived from three primary sources.
 
0:03:36.0 JD: So the first two come from Dr. Donald Wheeler, who I've mentioned on here before, a lot of Deming folks will, of course, have heard of Dr. Wheeler, who's a statistician in Tennessee, a colleague of Dr. Deming when Dr. Deming was alive and then has carried on that work to this day. The two books, two really great books that he wrote, one is called Understanding Variation, a thin little book, a good

Do you struggle to meet your goals or targets? Find out how you can change your thinking about goals and your process for setting them so you can keep moving forward. In this episode, John Dues and host Andrew Stotz discuss the first five of John's 10 Key Lessons for Data Analysis.
TRANSCRIPT
0:00:03.0 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 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 two of four in a mini-series on why goal setting is often an act of desperation. John, take it away.
 
0:00:32.3 John Dues: Hey, Andrew, it's good to be back. Yeah, in that last episode, that first episode in this mini-series, we talked about why goal setting is often an act of desperation and I basically proposed these four conditions that organizations should understand prior to setting a goal. So it's not the goals in and of themselves that are bad, but it's with this important understanding that's often lacking. So those four things that organizations should understand, one, what's the capability of a system under study? So that's the first thing, how capable is the system or the process? The second thing is what's the variation within that system or process under study? So that's the second thing we talked about last time. The third thing is understanding if that system or process is stable. And then the fourth thing was, if we know all of those things, by what method are we going to approach improvement after we set the goal, basically? So you gotta have those four things, understanding the capability of the system, the variation of the system, the stability of the system, and then by what method, prior to setting a goal. And so I think I've mentioned this before, but absent of an understanding of those conditions, what I see is goals that are, what I call it, arbitrary and capricious.
 
0:01:48.8 JD: That's a legal characterization. You look that up in the law dictionary. And it basically says that an "arbitrary and capricious law is willful and unreasonable action without consideration or in disregard of facts or law." So I'm just now taking that same characterization from a legal world and applying it to educational organizations and accountability systems, and I just switched it to "a willful and unreasonable goal without consideration or in disregard of system capability, variability, and/or stability." And we see these all over the place for education organizations, for schools, school districts, teachers, that type of thing.
 
0:02:31.6 JD: And so what I tried to do in the book and tried to do here in my work in Columbus is develop some sort of countermeasures to that type of goal setting and develop the 10 key lessons for data analysis. An antidote to the arbitrary and capricious goals seen throughout our sector. And this process behavior chart tool, looking at data in that format is central to these lessons. So what I thought we would do in this episode and the next is outline those 10 key lessons. So five today and then do another five in the next episode. And in the fourth episode of the series, what we would do is then apply those examples to a real life improvement project from one of our schools. It's helpful, I think too, to sort of, to understand the origin of the key lessons. So there's the lessons that I'll outline are really derived from three primary sources.
 
0:03:36.0 JD: So the first two come from Dr. Donald Wheeler, who I've mentioned on here before, a lot of Deming folks will, of course, have heard of Dr. Wheeler, who's a statistician in Tennessee, a colleague of Dr. Deming when Dr. Deming was alive and then has carried on that work to this day. The two books, two really great books that he wrote, one is called Understanding Variation, a thin little book, a good

32 min