Clayton Christensen: Hi. This is Clay Christensen, and I want to welcome you to a podcast series we call The Disruptive Voice. In this podcast, we explore the theories that are featured in our course here at HBS, Building and Sustaining a Successful Enterprise. In each episode, we'll talk to alumni of our course and others who are trying to put these theories to use in their lives and in their organizations. It's great fun to hear from them, and I hope that you find these conversations inspiring and useful. If you have an idea about a topic or a speaker that you'd like to hear more about or if you'd like to comment on their work, please reach out to us here at the school.

Shaye Roseman: Hi. I'm Shaye Roseman, and you're listening to The Disruptive. Voice. I'm so excited for our conversation today. We have Todd Rose and Bob Moesta in the studio.

Shaye Roseman: Todd is a faculty member at Harvard's Graduate School of Education and the director of its Laboratory for the Science of Individuality. He also cofounded the public think tank Populace and is the bestselling author of The End of Average and, most recently, of Dark Horse, both of which we'll talk more about in a minute.

Shaye Roseman: Bob Moesta is, along with Clay Christensen, one of the principle architects of the Jobs-to-be-Done theory. He cofounded the Rewired group, an end-to-end innovation consultancy where he continues to advance and apply the theory to real business challenges every day. He's also the reason we're all here, as the one who recommended The End of Average to me and the team, which just blew me away.

Shaye Roseman: So Bob, Todd, we're all huge fans of your work here at the forum. Thank you so much for joining us in the studio.

Todd Rose: Yeah, thanks for having me.

Bob Moesta: Yeah, thanks for having me. I'm as excited, I think, as you guys are. I've been working through Todd's books a lot, and so this is a pleasure.

Shaye Roseman: Great. So, Todd, you published a book called The End of Average. Tell us what you mean by the end of average.

Todd Rose: It's funny, because it can sound almost like a bumper sticker, right? No one's average or whatever, but, actually, it's a pretty important scientific insight that I think has implications for most of society. It's this: For about 150 years, we've basically viewed human beings through the lens of the average person, and that's true in even how we think about ourselves, but how we design education, workplace, products.

Todd Rose: What we've found out over the last couple of decades is that, kind of shockingly, there actually isn't an average person and that it turns out individuality matters quite a bit. That doesn't mean individualism. It doesn't mean selfishness. It just means the reality that people are distinct and those distinctions actually matter quite a bit.

Shaye Roseman: Yeah. What are some ways that people, our listeners may be used to thinking about themselves in terms of the average person?

Todd Rose: Well, I mean, it might even be easier to think about the ways they don't. It's so embedded in our society. So almost all of standardization is based on averages, at some level. If you're a parent and you take your kid to the pediatrician and they say, "Well, how are they doing?" Right? They say, "Well, let me show these growth charts." Well, those growth charts are literally just the average at each age stitched together, and it turns out that not a single kid that has ever been looked at actually follows them, those growth charts, like they say they should.

Todd Rose: We do it in the way we think about school. We give kids standardized tests, and did anyone ever wonder, "Where did we come up with the amount of time kids get to take those tests?" It's quite literally the time it takes the average of a representative sample of people to finish.

Todd Rose: So, basically, the way we've designed our classrooms, the way we've built our products, the way we think about employees, just about every aspect of our life is dictated by this average person that turns out to be a myth.

Bob Moesta: I always like to talk about it in terms of healthcare. What's your blood pressure? What's your average max heart rate? All of that, it comes from exercise, all those things, all from averages. When you look at my body type and other people's body types, they're all very different. So the reality is ... But, "Yep, 166 is my max heart rate." How do we know that, and am I really working out enough if it's 166 and it's really 187? So this is where, again, being able to understand the details is really, really important.

Todd Rose: To that point, there was literally a person who invented the idea of the average man. It was a Belgian astronomer named Adolphe Quetelet. He also invented the body mass index. So, to this daym we're stuck with this thing that works well in the population. If you know the body mass index of a country, it's a pretty good indicator of health for the country. It is a miserable predictor of individual help, because it confounds fat and muscle and bone into one number that just doesn't represent any particular person.

Shaye Roseman: Why is that so problematic?

Todd Rose: Almost everything starts with an accurate understanding of yourself, and if you don't have that, you get in big trouble, right? So if we have built everything, from our science to our society, on an idea that the average is a good approximation for most people, then you're just going to be off in almost everything you do.

Todd Rose: Now, the implications, some of them are more just about on the commerce side, which is still important in a market economy, to be accurate in terms of who people are and what they want. But it can become profound too, right?

Todd Rose: So most of medicine, until recently, was based on average-based research, right? So you take something like cancer progression. So colon cancer is the second most diagnosed and lethal cancer in the world, last time I checked, and, for 35 years, we had a theory that was based on average progression. There was one pathway, one precursor lesion, a series of genetic mutations, and manifestation.

Todd Rose: Turns out there's actually three, and that average progression only accounts for less than 10% of people diagnosed with colon cancer. So you are literally condemning people to death by treating them as averages.

Todd Rose: Now, in medicine, we've blown past that. You are never, ever going to accept average-based medicine anymore. We have personalized medicine. You get molecular fingerprinting. You want to know. "Treat me as an individual, because this is about life and death."

Todd Rose: We want that same urgency brought to the rest of society where we may not have the sort of life or death scenario, but it's our human potential, it's our happiness, it's our productivity, and it matters.

Shaye Roseman: So, Bob, you have a very particular view of the way in which that matters. Can you talk about why this idea that the average is not necessarily representative of a set is so important in your work, as it relates to jobs?

Bob Moesta: Yeah. So, for me, part of it goes back to this notion that nothing is random, everything is caused, and what they call the N-of-One. So this is the work I did with Taguchi and Deming really early in my career, and the aspect here is that underlying the causality of what causes people to do what they do is what's really, really important.

Bob Moesta: In Todd's work, he's really been able to kind of talk about this notion of pathways, where what we would tend to do is average all that data together and kind of say, "Well, here's the best way we should do this." The reality is that there's probably four ways or five ways, and it depends on where you start and what your outcome is.

Bob Moesta: So jobs is really based on this notion of the progress people are trying to make in their lives and that, as we look at markets, there's a concept called personas, where they look at people and they'll average people out and say, "Here's a persona, and here's a different persona." But the reality is that, to me, it's really about the context and about the individuality of one situation or a set of situations that then talk about the progress they want to make with the outcome.

Bob Moesta: So, to me, it's helped me build way better products by not thinking about what's the average, because I end up being wrong. But if I can actually understand these pathways, I can actually figure out how to actually build way better products that have way more scale.

Todd Rose: One of the things that I love about the jobs theory is that it shows that sometimes when you think about individuality, you think of either chaos or just almost intractable, right? But, in truth, it's almost never that there's a million pathways.

Bob Moesta: That's right.

Todd Rose: Right? The systems don't sustain themselves that way. But it is a guarantee it's always more than one, right? In complex systems, it's called equifinality.

Bob Moesta: Yep.

Todd Rose: It's one of the only rules we have, and what's cool about jobs theory is you start to see, look, when you start by taking individuality seriously, you can arrive at a set of patterns that have broad applicability that you would not have arrived at had you started in the aggregate and tried to work your way down.

Bob Moesta: That's right, and you end up with trade-offs. So, ultimately, it's about understanding the trade-offs consumers are willing to make to make that progress. What are they willing to give up to get? It's typically a combination of that context, outcome, and trade-offs that allow us to design better, more valuable products for people.

Shaye Roseman: You mentioned the idea of personas, Bob.

Bob Moesta: Yeah, yeah.

Shaye Roseman: How does that fit into this larger idea of product design and the progress that people are trying to make?

Bob Moesta: I think personas end up as ... Again, I think it's pattern recognition and the demographics. So people will basically build patterns around combinations of, "They're this old. They have these many kids. They have this kind of income," and it's looking at the data set they have. So it's better than averaging it all. But, to me, a persona is kind of like a consumer without a soul. We know all the things about them, but we don't know what they value and how they make decisions.

Bob Moesta: So, to me, just because I'm 54 and I have this income and I live in this zip code, it doesn't cause me to buy this new car. So jobs is actually trying to strip away those other kind of larger, higher kind of demographic, I'll say, variables and literally just look at it and say, "What in the world was going on in your life today that said, 'Boy, I need to buy a new car'?" What were you hoping for the moment you said you pick that one?

Bob Moesta: If I can see those things irrelevant of the solution I picked and irrelevant of my demographics, I now have a way clearer way to design better products.

Todd Rose: I mean, to me, it's getting at the why, right?

Bob Moesta: Yep.

Todd Rose: I mean, like you said, demographics, it's better than nothing, probably. But it's soulless, right? It doesn't tell you anything about the motive forces behind the choices people make, and the reality is that, until recently, we didn't have the tools and even the capabilities to get at this at scale, but now we can. Right? The truth is that anytime you care about the motive forces, the why, it's always an individual-level phenomenon.

Bob Moesta: That's right, and the only way it can really be leveraged is through aggregation, as opposed to segmentation.

Todd Rose: Exactly.

Bob Moesta: So, to me, it's pulling it or aggregating together, as opposed to trying to pull it apart.

Shaye Roseman: Once you've identified the why, how does that change how you think about a product or a job spec, let's say, Todd? I know you talk a lot about education and sort of matching skills to future employment opportunities or in schooling in particular.

Todd Rose: Yeah.

Shaye Roseman: What sort of opportunities does that open up?

Todd Rose: So it gives you a couple of things. One is it starts to help you understand ... Clay has a theory called modularity interdependence, right? The notion is sometimes you have things that are very integrated and you can only do one thing with it, or you can actually create something that's very modular. They have trade-offs between the two.

Todd Rose: So part of this is once I understand a set of jobs, I can actually see if I could build a platform to do something and then have customization to do the different jobs in a different way, but have an underlying kind of a fundamental system to do that.

Todd Rose: So part of this, it allows you to actually get scale faster. But the other part is it allows you to actually drive satisfaction and in completely different variables and completely different situations for, in some cases, the same customer.

Todd Rose: The other part, and Todd hit on it, is systems thinking is at the core of this. So it's really thinking about the market as a core or what are the systems that enable consumers to make progress, and so if I can actually surround myself with context, outcome, trade-offs, hire-fire criteria, I then can actually design a whole bunch of different systems to do that job. So it allows me flexibility in cost and delivery and a whole bunch of other things.

Bob Moesta: If you imagine on the human side, too, I think that getting at and understanding the why behind things and having be able to understand that for themselves is the way forward to solving what I think is one of the biggest problems in corporate America today, which is just this profound lack of engagement by people.

Todd Rose: It's unreal that a majority of people are disengaged at their jobs.

Bob Moesta: So I was just listening to a little bit of book that on the way over this morning, when I was flying over, and I love the notion of ... and it just reminded me of just healthcare, which is the difference between choice and picking, right, and that so many people think that they have a choice in healthcare, but the reality is they just pick the program that fits best for their family and their budget and everything else.

Bob Moesta: But they actually don't engage with it. They have no idea what it does. They have no idea. There's no way that ... The language alone is so complicated that they can't even figure how to engage with it, and so the lack of engagement, it's not having them do stupid things they kind of know about. It's literally making sure it's relevant to their lives and they know how to make choices.

Bob Moesta: My wife had a medical emergency back in November, and we literally could not decide where to go. "Do we go to urgent care? Do we go to the emergency room? Do we wait for the" ... and all back and forth, and next thing you know, she's in the ICU for five days.

Bob Moesta: I'm a fairly educated person. We should know what we have. We know what our insurance is. But we actually don't even know how to engage in the right way, and part of it is the language. That notion of fit is really, really ... It's an important concept that I think is kind of the next thing of how do we actually describe fit? Because now it talks about a relationship between two things, as opposed to average, which can be just basically one thing.

Shaye Roseman: So this idea might help us get to a better fit between a spec, let's say, and an individual.

Todd Rose: Yeah.

Bob Moesta: Yeah.

Todd Rose: You think about the power that this unlocks, in the sense that there's this other variable that we're not considering, which is the why behind what people do. Even when we hire people, it's pretty remarkable to me that we'll spend a lot of time looking at your rank and grades and test scores and your strengths and yet rarely ask why. "Why do you care about this?"

Bob Moesta: Yeah, so I've been doing job interviews around people who have switched careers. It was like, "Why would you leave this company, and why would you join this company?" When you understand the causal mechanisms, you start to realize there's some patterns here, which is, "I don't feel like I can grow anymore. I feel like there's no sense of progress for me where I'm staying, and, to be honest, I'm more valued if I go out and come back."

Bob Moesta: All of a sudden, you sort of realize, like, "Oh, we have no way of which, actually, they feel like they're making progress," and like, "Oh, you want more money?" No, money has nothing to do with any of this. So you start to realize that the variable set I call the supply side has, which is HR, is money and benefits and vacation time. It's like, "No, no, no. I want challenge. I want a great team. I want" ... These are other variables that aren't even in the equation.

Todd Rose: Yep, and I think that, as we surface these patterns and they're actionable, I think you've seen companies, especially in talent-scarce industries, trying to fumble around, figuring out, "Well, we've got to do something to keep talent, right?"

Bob Moesta: Right.

Todd Rose: "So now we have Korean barbecue and seven other kinds of food." You're like, "Sure, that's great. But you're actually missing the point about what most people really want," and our ability to surface those patterns and say, "Look, address these, and you're going to have a very engaged, motivated workforce, and it'll probably cost you less than all the food."

Bob Moesta: Well, the other part is it runs out. So this is one of those things, it's like, "Okay, it's all about food," and you end up spending so much time and effort in all the wrong things that you're trying to do as opposed to digging why. So when I was in Japan, they have this thing, the five why's. You had to just ask why five times, and if it's food, you've got to ask why, why, why. Part of it is, "I want a sense of community. I want to eat with other people." All of a sudden, it's not the food. It's the environment that the food's served in that's sometimes more important.

Shaye Roseman: Yeah. So as a way of getting at that why, you've both talked in different ways about designing toward the edges, rather than to the average.

Bob Moesta: Yeah.

Shaye Roseman: Talk about what that means.

Todd Rose: When you're in systems that are optimized on average, we often confuse muddling through with actually thriving. Right? The people that can muddle through, it masks a whole bunch of things that could be optimized.

Shaye Roseman: What do you mean, muddling through?

Todd Rose: Okay, so let's take education. So just because I get straight A's does not mean you're actually developing my full potential. It doesn't mean I actually care, but that's what we use right now. Right? We don't know. It's like, well, wait a minute, this system more or less works because not everyone's failing, right? Some people get good grades. But if you're trying to develop people, how would we understand the pain points? How we understand where the need really is?

Todd Rose: What we find is when you go to the edges of the distribution and you actually play there and you figure out how to make things work there, those are not different people. They're not like those people over there. They're actually revealing the thing that is usually true in general.

Shaye Roseman: The people who may be failing the class?

Todd Rose: Yeah. Or you think about ... I mean, you can name the products, right? If you think about closed captioning and we said, "Well, it's going to be for a specific disabled community," except for they're I think third or fourth on the list of who actually uses it the most. It's me in in bed watching TV with my spouse ...

Shaye Roseman: Right.

Todd Rose: ... because I don't want to get divorced after having the TV on until one o'clock in the morning.

Bob Moesta: That's right. I think part of it also is that we ... I know you have, and we both kind of grew up on the fringes. Right? So I think the notion to me is that what I've learned is that when things are in the middle, when they're in the muddle, people have no language to articulate it. So if I ask if you use Tide every week, and I ask you, "How do you use Tide? Why do you buy Tide?", to be honest, you just make it up.

Bob Moesta: You have absolutely no idea, and what happens is we just get a larger sample size to help us get common language. "Oh, it smells good, and it gets the clothes clean," but they don't know how. But if I asked somebody who switches from Cheer to Tide or Tide to Cheer, I can learn really, really quickly what was going on. Why?

Bob Moesta: Because we're creatures of habit, the moment that we struggle with something and we make a change, there's motive behind it. There's outcome. There's intent. There's energy. So part of it is being able to dig through that and figure that out.

Bob Moesta: Clay and I talk about this a lot. We end up measuring all the wrong things. We measure the things that are easy to measure that aren't meaningful, but we very rarely measure the meaningful things that are hard to measure.

Bob Moesta: So you go to the doctor, and they measure my weight and my blood pressure and my temperature. How is that meaningful to my body and what I had need to do? So I have a different doctor, who basically helps me with all my thinking patterns because of my dyslexia. So she literally has tests that are way harder to measure, but they're so much more important to helping me be a better me. So, to be honest, I very rarely go to my primary care physician. Every 90 days, I'm in my neurologist's office.

Shaye Roseman: Yeah. So I want to talk about data and this idea of measuring things that we're able to measure that may not always be the most useful things to measure in a minute. But before we get there, Bob, this idea of designing to the edges and sort of going towards the end of the distribution to find really meaningful insights strikes me as related to something you've talked a lot about, which is this idea of hacks and even, in some cases, petty lawbreaking as a way of studying ...

Bob Moesta: Yep.

Shaye Roseman: ... those behaviors, as a way of identifying people's struggling moments ...

Bob Moesta: Yep.

Shaye Roseman: ... or sort of the causal drivers of behavior. Can you talk about that?

Bob Moesta: Yeah. So, in terms of trying to find where to innovate, first of all, consumers don't know. So if you actually go to ask them directly, they have no notion of what's possible. They're only going to repeat things they already know. Typically, they have no idea about any of the realities of trying to make any of that work, and, to be honest, they lie. They don't lie on purpose, but they lie for a whole host of different reasons.

Bob Moesta: So part of it is being able to understand what causes those things and taking a step back. So, to me, the struggling moment is that seed, and if I can find where people struggle and when they struggle, we can actually figure out where and when and how and who and the five whys behind all those things.

Bob Moesta: You start to realize Uber is just an extension of all those people hanging out at the airport, trying to give you a ride when they couldn't give you a ride saying, like, "Well, how do I make this legitimate?" There's points of how many people want to want a better cab, but can't have it? How many people want a better class or better teacher but can't find it? My favorite question here is is how do you shop for a doctor?

Bob Moesta: All these things where we struggle and we just kind of assume like, "Well, you just get the doctor you're assigned" is like, "No, that's just not acceptable." So how do we actually build a system where people have choice, and not picking, but choice? What's the difference between picking and choice?

Todd Rose: Yeah. I mean, picking is when you're given stuff and, usually, you don't actually care too much about the difference, but it's like someone else serves it up to you and you're like, "I guess A." Right, instead of B?

Todd Rose: Choice is very active. It's driven by an understanding of your own motives, which I think is a fundamental part of all of this, and we've already kind of touched on that. What's so fascinating is when you see choice-rich environments, genuinely choice-rich environments, it's not just serving up options for people. It's allowing them to carve off options that you didn't know existed. So we've spent a lot of time studying people who do this in spades.

Todd Rose: I think this kind of ability to genuinely understand how to make choices on your own behalf I think is fundamental to both good consumer markets, but also the ability to live fulfilling lives.

Shaye Roseman: Can you convert from one to the other? Can you take an environment in which people are picking and convert it to one in which they're choosing?

Todd Rose: To look to Bob's point, if you want to start to see how you convert those, go look on these margins of stuff that we would have looked at as behavior and would say, "Well, let's not encourage that." The way we think about it is, in economics, we think about things like preference signaling, right? Being very important to markets. People have got to be able to signal their preferences.

Todd Rose: Well, when it's in systems that don't have a lot of authentic choice, you can mistake having to go along as if you agree with it, right?

Bob Moesta: That's right.

Todd Rose: But so you go to these margins, you realize it's often not something unique about those margins. They're revealing the preference of the broader population, who either can't signal or don't have the ability to.

Bob Moesta: Don't have the language, yeah. So you're finding the anomaly, and that anomaly becomes the N-of-One. Then the question is how many people are there behind that N-of-One that actually want to do the same thing but can't, which is what we call non-consumption? So, ultimately, we're looking for places where people want to make progress, but they can't.

Bob Moesta: So the other part about choice is that they're engaged and that there's an assumption of a preference. So the fact is I can pick one, but that doesn't mean I actually prefer it. So part of this is really digging way past almost where the boundaries are. So, to me, the notion of a standardized system is like how do I get outside the standardized system so I can actually see free will at its best? Freewill will say it's about fit, not about kind of failure.

Todd Rose: Yeah. What's so powerful about this is when you think about all the social systems that we're trying to disrupt right now, so you take something like education. Well, if you follow this to its conclusion, you realize the place I start to look is things like homeschooling or where parents are supplementing their education, because they're making choices. They're either spending their own time or money to get their kids something, and sometimes they can't really articulate it. You have to help them figure out.

Todd Rose: But behind it is a motive or a set of motives that turns out to be way more prevalent in folks that are just almost captive. "I don't know. My kid has to go to this school down the street, because that's what it is."

Bob Moesta: That's right. No, they're hating school. They're getting bullied. This is happening. That's happening. It's like, "How do I actually decide to take them somewhere? So how did you decide to homeschool your kid?" Then they'll tell you the story, and you'll be like, "Oh my gosh, we've heard that story about 300 times before, but they just didn't come up with homeschooling."

Todd Rose: Yep.

Bob Moesta: So once you understand these voids where people are trying to make progress and they can't, now it's actually time to say, "Hey, some people went to a new school. Some people moved. Some people actually homeschooled. Some people" ... and you start to see what do these solutions have in common, and how do I actually put them together and weave it for those people who can't afford it or don't have access to it? How do I actually design access?

Todd Rose: What I love about this is that, to me, the distinction between this and the system we have is its respect for individuals. Either you respect people and you believe that they have a right to be able to exercise choice and you think that, if we provide a supportive environment that, actually, it becomes mutually beneficial for everyone, or you believe that you should have a few people on top, dictating the sort of efficiency of the system. We've played that game out now. It doesn't work.

Bob Moesta: It doesn't work. So Michael Horn has done a great book called Blended where he walks through and basically says, "If you do whole classroom teaching, you're teaching to the middle of the class. But now I've got these kids who are on the top end who literally move through it so fast, they're bored, and if I don't give them something, they get in trouble. Then I've got the kids who are a little bit slower in the subject, and they need some extra help. I'm trying to manage the variation in the room."

Bob Moesta: The reality is there's a whole set of new ways to do this, which is how do we actually get kids engaged in understanding what are their learning objectives? How do we actually have them be held responsible for actually making progress? How do we get them to help each other? So the role of the teacher goes from being the sage on the stage to a guide on the side of literally orchestrating the process of learning, as opposed to being the knowledge guru.

Bob Moesta: I think those kind of things, when you start to see people doing amazing progress in math and in science and some of these subjects where ... I'm talking as young as kindergarteners, where they're learning colors and shapes and stuff, and they're doing it with guidance, as opposed to, basically, memorization and standards.

Shaye Roseman: Does it ever work? I know, Todd, you talk about some of the quantitative basis for this idea of the average in your book. Is it ever okay ...

Todd Rose: Sure.

Shaye Roseman: ...to use those kinds of methods?

Todd Rose: Sure.

Shaye Roseman: Is it always harmful?

Todd Rose: So, first of all, you're a sociologist. Go crazy. Averages are awesome, right? If you care about populations, that is your go-to thing. So when it comes to making statements about individuals, this is what I would say. Can averages sometimes work? Yeah, sometimes, but we even have a mathematical theorem. It's called the ergodic theorem, that tells us the conditions that have to be true for you to be able to use group averages for individuals, and we violate them every time. So if it works, it's sort of lucky that it did.

Shaye Roseman: Yeah.

Todd Rose: So what I would say is there's no reason to go ahead and keep assuming it'll work when you can start at the individual level and work your way up, and guess what? If it turns out to work, there you go. Right? You're not out anything. You will arrive at that same pattern through individuals if you start at an average, but almost always what you find is, at a minimum, it wasn't enough. There's always more than just that that exists through averages.

Todd Rose: Sometimes you realize that the average literally was an artifact, and it doesn't represent anybody at all. We found this out in neuroscience and brain imaging, where we spent so much time looking at average brains, and my colleagues like Mike Miller found that the patterns we found for memory retrieval, on average, literally didn't apply to any single person.

Bob Moesta: Wow.

Todd Rose: So we had whole theories of how your brain retrieves memory that relate to absolutely nobody.

Shaye Roseman: So we're violating these conditions left and right?

Todd Rose: What are the conditions?

Shaye Roseman: Yeah. What are those circumstances?

Todd Rose: You have to be a frozen clone, is what we call it. So, quite literally, no kidding, this is the mathematical requirements for it to work: You have to be identical to the other people in the group on all the important dimensions, identical, and you cannot change over time.

Todd Rose: So let's see. The very definition of learning would be change over time. The definition of development would be change over time, right? The mere fact that even if we don't change over time, we are wildly individual right now in this room.

Todd Rose: So it's one of those things where, if we were having this conversation a hundred years ago, we didn't have the ability to do anything else. So what we had to do is say, "Well, how could we use aggregate data, and what has to be true?" We're like, "Okay, it's probably close enough," and you never had a way to really validate whether these statements were actually true. Now we do.

Todd Rose: So I think that what's really interesting is, in the fields where there's moral imperative, we've moved on so fast. If you're in medicine and you know that relying on averages is killing people, it's just immoral. So that's already changing. It's not for nothing that's gone first.

Todd Rose: But I think, in these other places, it's not surprising that you're seeing in the consumer behavior, consumer areas that that's going quick, because there's an obvious incentive. What we're after, I think we both share this thing, is we have to bring that to the rest of our systems, right? It's not okay to put people in a standardized education system that views them as an interchangeable part.

Bob Moesta: The way I would say is average is actually really important on the supply side for me to build standards. So if I want to build an engine, I need to make sure that I'm manufacturing the cylinders at this diameter, at this consistency, on these things. So what we did is we've kind of overused the notion of average from the physical things and things that we use from an engineering perspective into the social sciences. I think the social sciences, it's a different system.

Bob Moesta: So the reality is that, because there's about motivation and there is about intent and there is about fit and there's choice, it's very different. An assembly line that builds engines doesn't have choice. There's people who make settings. They have to basically make sure that they start at the end. They have certain requirements they have to do, and, in those kinds of things, to get scale, I need the average. I need to know variation. I need to know when something's outside a variation. I need it to improve quality. But this is not a quality problem. This is actually a market problem or, basically, a human problem, not a machine problem

Todd Rose: I think that was really well-said, and I think that one of the big distinctions that I think, for most listeners, is when you take this approach that we're talking about here, it changes the way you think about individuality. So, historically, we either see it as a nuisance variable or we see it as something to select on. So it's about classification and selection. This shifts to it's a design challenge. When you realize that this individuality matters in a motive way, right? It actually matters, then you design for it.

Todd Rose: When you design for it, what you find is a lot of people are capable of doing really great things in the right context. But when you've designed it a way, it's not surprising you get a pretty narrow talent pool and a narrow sense of satisfaction and engagement.

Shaye Roseman: So if we have the analytical tools now, we have the ability to design for these kinds of complex systems, why are we all still so wedded to this idea of the average?

Bob Moesta: I think part of it is that we have to get people to step back from the problem, because, again they confuse, for example, the notion of a root cause. What's the one thing that caused this to happen? For me, it's sets, sets of things in the past, sets of things in the future or imagined future. This is a whole bunch of sets of motivation, right?

Bob Moesta: So what happens is, because we're thinking about average, we're looking for the outlying cause that caused you to buy your sunglasses. Right? There's not one.

Bob Moesta: I always think of it this way. In a spreadsheet, I have a column. It's got a thousand rows in it, right? That one column, I'm going to average a thousand pieces of data in that one column. But the reality is each data point is actually dependent upon every other column in that data. So when I actually average it, I actually negate all the other things that are wrapped around it that make it isolating and make it basically wrong, because there's dependencies between the columns that actually make it there. That's why cluster is so much more powerful than segmenting and averaging.

Todd Rose: I think that one of the big challenges here is we're dealing with a fundamental assumption, right? Assumptions exist ... They're meant to get you off the ground. You're not supposed to think about them, and then you're trying to uproot a deeply held assumption, and yet, everywhere you look in your lived world, most of it's telling you, actually, averages are pretty good, right?

Todd Rose: So it takes a lot to get past that, and it's not surprising ... Short of stronger pain points for you as a person, broader counterexamples of what else is possible, it's not surprising that people struggle.

Bob Moesta: We have to give them another way of thinking, right? It's why the jobs stuff is so important.

Bob Moesta: The thing I go back to is if you watch football and you show the stats that they have, the stats are everything in the past. It has nothing to do with predictive in the future. So the notion is if you actually understand that the quarterback is in a completely new situation, seeing a completely new defense in a completely new way, but he has an 83% completion rate, it actually has nothing to do with what he's going to do next.

Todd Rose: It drives me nuts.

Bob Moesta: So this whole notion is there's a huge misuse of stats, over and over and over again. One of my daughters is a math major and she calls me. She goes, "Dad, people are confusing statistically significant with important." It's like, "If we just increase the sample size, we can make something statistically significant, which makes it now important." It's like, "No, that's not how it works." She goes, "I know, but I don't know how to tell them."

Bob Moesta: So there's all these kinds of misnomers of how people want to use stats and data and average to literally tell their story.

Todd Rose: Garbage in, garbage out.

Bob Moesta: Exactly.

Todd Rose: It doesn't matter if you have ten times the garbage.

Bob MoestaIf I increase the sample size, it doesn't actually make a bad question better.

Shaye Roseman: So how can we be sure that we're using that information responsibly and that, as we've been talking about, we're understanding the difference between the why versus just the what?

Todd Rose: Yeah, I mean, look. I think there's a couple of things with the data. There's an issue of quality, which is to say that ...

Bob Moesta: You've got to measure the right things, first of all.

Todd Rose: I think we've already talked about ...

Bob Moesta: But I think the notion is how do we come up with the right things.

Todd Rose: Right.

Bob Moesta: I think that's number one on your list, is we aren't having the discussion about what to measure. We're just not doing it. It's, "Oh, I can measure the" ... People that are literally offering up 50 things to measure, like, "Oh, that's great, and we'll just amass big data. We'll figure it out from there." My experience is that never happens.

Todd Rose: It never happens, and, by the way, what's really dangerous is we have to resist the temptation to be like, "Well, in the meantime, until we figure out something better" ... No, because what happens is that it captures, and suddenly, this thing that we all knew was kind of crummy and not a good idea now becomes the way everyone talks about things, right? It becomes the metric, and things start to drive against it. Now you're stuck with this thing that is really hard to displace.

Shaye Roseman: Do you have an example of where that's happened?

Todd Rose: Oh my goodness.

Bob Moesta: Net promoter score is my favorite.

Todd Rose: Oh my God, kill me with that one. Right? I mean, think about in education, our reliance on norm-referenced standardized assessments. By definition, norm referenced means we don't actually care what you know. We care how you compare to other people. It's referenced to the average, and we give you a score. So when parents see their kids' stuff come home and be like, "Well, you scored in this percentile," I'm like, "Yeah, it does not say what they know. It doesn't matter. You cannot act on that." If I said, "Okay, how do I help my kid get better?", It cannot tell you those things, and I don't think anyone would start the system over and say, "You know what's a good idea? Norm-referenced standardized assessments."

Todd Rose: We have other ways of doing this, right? We can do individual growth scores. We can do all kinds of stuff, but you have an incumbent advantage with this particular kind of assessment, and you have lots of people who have a vested interest in preserving it. So, for me, it's like let's have the conversation about what's worth measuring and don't feel like we have to have this rush to get crummy outcomes and metrics just to have something.

Shaye Roseman: Just because they're there?

Todd Rose: Yeah. By the way, we'll get ... and Bob's right. We'll get to the patterns pretty quickly. We'll get to the insights. It is not hard.

Bob Moesta: It doesn't take long, either.

Todd Rose: No.

Bob Moesta: I can do 10, 12 interviews and start to see patterns very, very quickly.

Shaye Roseman: So we're very lucky to have both of you to learn from. I think in our last few minutes here, I'm just curious whether you have any final words or parting advice for our listeners.

Todd Rose: Yeah, look, our society is moving towards something that's more personalized, whether we want it to go there or not, and I think the open question is what is it going to be and who is it going to benefit? You can imagine that we double down on an average-based view of people and we use our big data to actually lock in this antiquated idea that we've known is just not true. That's one way, right?

Todd Rose: We could just do it on steroids, and it's just like what a wasted opportunity, or the systems we create actually do go the way of individuality. By the way, most of these things, like Amazon and Facebook, have, or they're trying to.

Bob Moesta: They're trying.

Todd Rose: They're trying, and, suddenly, our systems know us better than we know ourselves. That asymmetry in knowledge is frightening to me. I think that is the nightmare scenario where we lose agency, we lose our ability to honestly be able to make choices on our own behalf, and, unlike the sort of standardized model where it was just brute force, you knew what was being done to you, in this world, you will thank them for it, and you'll call it personalized.

Todd Rose: So I see this as a really important moment in time, when if we can get rid of the shackles of average-based thinking and we can adopt this approach to individuality that I've been talking about, then we can actually get somewhere, where we have a society of people who honestly feel like they have a shot at living fulfilling lives. I think it's vital to the health of our democracy, and it's vital to our economy.

Bob Moesta: Yep. I agree. The way I would add is I believe that we grew up in a supply-side economy, of people making products and people trying to figure out how they fit into people's lives. I think the future holds a more demand-side economy, which is basically, as people become more and more aware of what progress they want to make and as we become smarter and smarter about ourselves and what we can do, the supply side, which is mostly where average comes from that builds average products, average systems, standardized things, the reality is that it's like the jet fighters, where they told us it was impossible to actually make the seat and the cockpit and everything adjustable. What, six, eight months later, they did it.

Bob Moesta: I think it's a two-way street here, because I think consumers actually have to get more engaged. I believe that we're actually unengaged in very important things, and the reality is that they're picking things, as opposed to choosing things. I think getting people to be more mindful about the choices that they're making ...

Bob Moesta: So, for example, I'm working with somebody on an election right now, where it's not voting. They're not picking, and they need to actually choose a new mayor. By using that as their campaign vote, of your city is struggling, it's because you are not voting, you are not choosing to be engaged, and basically making sure we have it as a demand-side issue.

Shaye Roseman: So my news feed at the end of the day, even if it's ultimately personalized, in a sense, I'm still not picking what shows up.

Bob Moesta: Yeah, this is about who gets to decide the kind of life you're going to live. Who gets to define what success is for you and how you get to achieve it? What we're talking about is empowering, on the demand side, individuals to know enough about themselves, the things that truly matter, the things that have been masked in our standardized system, and allowing them to put that into play in our democracy and in our market economies.

Bob Moesta: I think that everybody wins in that scenario. For me, the bear right now is a mindset, and we've got to surface this. We've got to get people to realize what's actually holding us back and that we have a way forward. This is not rocket science. We can do it.

Shaye Roseman: Well, hopefully our conversation today can help folks realize just that. I think that's an awesome place to leave it.

Todd Rose: Great.

Shaye Roseman: Thanks so much for being here.

Bob Moesta: Thanks, Shaye.

Todd Rose: Thank you.

Clay Christensen: Thank you for listening to us at Disruptive Voice. If you like our show and want to learn more, please visit us at our website or leave us a review on iTunes. Until next time, good luck, everybody.