Today I’m chatting with former-analyst-turned-design-educator Jeremy Utley of the Stanford d.school and co-author of Ideaflow. Jeremy reveals the psychology behind great innovation, and the importance of creating psychological safety for a team to generate what they may view as bad ideas. Jeremy speaks to the critical collision of unrelated frames of reference when problem-solving, as well as why creativity is actually more of a numbers game than awaiting that singular stroke of genius. Listen as Jeremy gives real-world examples of how to practice and measure (!) your innovation efforts and apply them to data products.

Highlights/ Skip to:

• Jeremy explains the methodology of thinking he’s adopted after moving from highly analytical roles to the role he’s in now (01:38)
• The approach Jeremy takes to the existential challenge of balancing innovation with efficiency (03:54)
• Brian shares a story of a creative breakthrough he had recently and Jeremy uses that to highlight how innovation often comes in a way contrary to normalcy and professionalism (09:37)
• Why Jeremy feels innovation and creativity demand multiple attempts at finding solutions (16:13)
• How to take a innovation-forward approach like the ones Jeremy has described when working on internal tool development (19:33)
• Jeremy’s advice for accelerating working through bad ideas to get to the good ideas (25:18)
• The approach Jeremy takes to generate a large volume of ideas, rather than focusing only on “good” ideas, including a real-life example (31:54)
• Jeremy’s beliefs on the importance of creating psychological safety to promote innovation and creative problem-solving (35:11)

Quotes from Today’s Episode

• “I’m in spreadsheets every day to this day, but I recognize that there’s a time and place when that’s the tool that’s needed, and then specifically, there’s a time and a place where that’s not going to help me and the answer is not going to be found in the spreadsheet.” – Jeremy Utley (03:13)
• “There’s the question of, ‘Are we doing it right?’ And then there’s a different question, which is, ‘Are we doing the right “it”?’ And I think a lot of us tend to fixate on, ‘Are we doing it right?’ And we have an ability to perfectly optimize that what should not be done.” – Jeremy Utley (05:05)
• “I think a vendetta that I have is against this wrong placement of—this exaltation of efficiency is the end-all, be-all. Innovation is not efficient. And the question is not how can I be efficient. It’s what is effective. And effectiveness, oftentimes when it comes to innovation and breaking through, doesn’t feel efficient.” – Jeremy Utley (09:17)
• “The way the brain works, we actually understand it. The way breakthroughs work we actually understand them. The difficulty is it challenges our definitions of efficiency and professionalism and all of these things.” – Jeremy Utley (15:13)
• “What’s the a priori probability that any solution is the right solution? Or any idea is a good idea? It’s exceptionally low. You have to be exceptionally arrogant to think that most of your ideas are good. They’re not. That’s fine, we don’t mind because then what’s efficient is actually to generate a lot.” – Jeremy Utley (26:20)
• “If you don’t learn that nothing happens when the ball hits the floor, you can never learn how to juggle. And to me, it’s a really good metaphor. The teams that don’t learn nothing happens when they have a bad idea. Literally, the world does not end. They don’t get fired. They don’t get ridiculed. Now, if they do get fired or ridiculed, that’s a leadership problem.” – Jeremy Utley (35:59)
• [The following] is an essential question for a team leader to ask. Do people on my team have the freedom, at least with me, to share what they truly fear could be an incredibly stupid idea?” – Jeremy Utley (41:52)

Links

• Ideaflow: https://www.amazon.com/Ideaflow-Only-Business-Metric-Matters-ebook/dp/B09R6M3292
• Ideaflow website: https://ideaflow.design
• Personal webpage: https://jeremyutley.design
• LinkedIn: https://www.linkedin.com/in/jeremyutley/
• Twitter: https://twitter.com/jeremyutley/
• Brian’s musical arrangement of Gershwin’s “Prelude for Piano IIfeaturing the Siamese Cat Song” performed by Mr. Ho’s Orchestrotica - listen on Spotify

Transcript

Brian: Welcome back to Experiencing Data. This is Brian T. O’Neill. And today I have Jeremy Utley on the line from the Stanford d.school and also the co-author of Ideaflow. We’re going to talk innovation. How are you?

Jeremy: Excellent. How are you doing?

Brian: I’m great. I’m excited to jump into this, especially because apparently you love spreadsheets and—

Jeremy: You know, [crosstalk 00:01:02]—

Brian: A lot of my audience loves [laugh]—

Jeremy: I’m in recovery, you know? I was a finance guy by training and so I love a good pivot table. The challenge is that very few things worth measuring can be measured. So, I’ll leave it at that for the time being.

Brian: Oh, that’ll be good to get into that. Yeah. You have a background in management consulting, right, and then you were an investment analyst. So, for all the analytics nerds listening to the show, this is someone working in the innovation space at the Stanford d.school, which stands for design for some of our audience that doesn’t know that.

So, I think talking about how you’ve made that transition is going to be really interesting. And my first question is, there’s a time and a place for analytical thinking, but when you’re an analyst or a data science and you kind of live in the world of the facts, did you have to carve out space in your head to think differently about this, or mode switch to maybe get out of the analytical thinking sometimes in order to do the type of work that you’re doing now? Talk to me a little bit how you think about that.

Jeremy: Yeah, I think it’s really a matter of knowing when what is appropriate. And one of the big advances I think of the design school’s, you know, design thinking methodology is bringing a little bit of explicitness to what mode is going to help us in this moment. And broadly, Amy Edmondson talks a lot about this with psychological safety is you have to have shared language. One of the simplest ways to think about shared language in a collaborative dynamic is, are we converging right now? Are we trying to make decisions? Or are we diverging, we’re trying to generate options?

Very, very simply, even being explicit about which of those two things we’re doing helps enormously, right? When we’re converging, when we’re trying to evaluate or judge, Wally, who sees that in the fourth column, the numbers aren’t adding up, it’s a phenomenally valuable contribution, right? If Wally brings that same mindset to a brainstorm session, we shouldn’t be surprised if we don’t get very far brainstorming because that same critical mindset which is so valuable when we’re converging and when we’re making decisions, is actually going to limit our ability to diverge well. And so, having a little bit of language around, what’s our goal here? Generating or evaluating?

And it’s simple things like that. And so, for me, it’s not that I value spreadsheets. Yes, I mean [unintelligible 00:03:12] I’m in spreadsheets every day to this day, but I recognize that there’s a time and place when that’s the tool that’s needed, and then specifically, there’s a time and a place where that’s not going to help me and the answer is not going to be found in the spreadsheet. And I think that my encounter with the d.school, actually, it didn’t weaken my resolve or enjoyment of getting in the numbers in the spreadsheet, but it gave me another—sometimes the answer isn’t, keep working on the pivot table or keep working in Crystal Ball.

Sometimes the answer is looking up and asking, “Who can I talk to? Where can I go? What can I try?” All stuff that’s got to happen outside of this spreadsheet. So, it gave me I would say, complementary instinct that makes my ability in the spreadsheet that much more of a superpower, actually.

Brian: How do you help people feel comfortable that maybe do come more from the analytical mindset? And when we’re talking about the divergent thinking and we’re talking about trying to come up with a quantity of ideas about ways we might tackle the problem at hand, my feeling from experience working sometimes [laugh] with certain individuals is that there’s a real uncomfortable rub or the feeling of complete waste of time. This is a total waste of time, and it’s like, it’s very fuzzy and hand-wavy, and it’s baloney, basically. Like, you could see it on their face. It’s just, “Let’s get it done.”

Like, how do we make that more comfortable so it doesn’t feel like it’s just a silly game of tossing out random ideas, this is, like, what creative people do, wear the black turtleneck. Just how do we make that comfortable for maybe people that don’t feel like that’s a good use of time?

Jeremy: You’re getting at the heart of the challenge, which I would say is broadly a professional challenge, which is we’re obsessed with efficiency, we’re obsessed with productivity, and we’re obsessed with feeling like we’re making progress with every incremental unit of time. There’s a correspondingly incremental improvement in progress, right? And the thing is, there’s the question of, “Are we doing it right?” And then there’s a different question, which is, “Are we doing the right it?” And I think a lot of us tend to fixate on, “Are we doing it right?” And we have an ability to perfectly optimize that what should not be done. [laugh].

And you go, “Okay, well…” and I think that everybody’s probably had the experience of there’s an easy fix, right? We identify a problem, we identify a solution, it’s an easy patch, it’s an easy fix. Except in the long-term, what we realize is it wasn’t actually the right solution. And just because we could do it doesn’t mean we should have done it. And furthermore, we weren’t even solving the right problem, right?

And so, if you think just from a pure efficiency perspective, what felt efficient in the moment turns out to cause a ton more work later on. And then it’s a question of, do you want to give your future self a gift or do you want to give your future self, like, a knock, knock, a bag of doo-doo on the porch, so to speak, like, you know—what is it—Billy Madison style? And sometimes that’s what we do to ourselves. Like, we implement the quick fix, only to give ourselves a ton more work later on because not only was it not the right solution, we weren’t even solving the right problem.

But it does get to the challenge of efficiency. One of my heroes, intellectual heroes, a guy named Amos Tversky. He was the sparring partner of Danny Kahneman, who a lot of people will know. And Tversky and Kahneman rewrote the laws of economic theory as we know. Before Tversky and Kahneman, economic theory assumed that people were rational actors, right?

By the way, that’s not pleasing to the spreadsheet junkies among us to think otherwise, but the truth is, we know we’re not rational actors. We don’t make decisions rationally. Our rational brain, as my colleague at Stanford likes to say—Baba Shiv—says our rational brain is exceptional at rationalizing decisions we’ve made elsewhere [laugh]

Brian: [laugh].

Jeremy: So, that’s where reasoning comes in, right? To rationalize that which we’ve already decided. But Danny Kahneman and Amos Tversky, they devised a series of wildly inventive experiments. If you think about their work output as experimental design, as experiments that yielded incredibly unexpected and counterintuitive data, what they were doing, their work product was really designing these wildly inventive experiments. And somebody asked Tversky once, “How did you guys do it? How did you design such incredibly inventive experiments?”

And here’s what Tversky said. He said, “The secret to doing good research is to always be a little underemployed. You waste years by not being able to waste hours.” And he was referring to the fact that he and Kahneman would take these rambling, ambling walks around Hebrew University’s campus there in Jerusalem, where they were up-and-coming stars, and people in their department look out the window from their dusty textbooks going, “Those whippersnappers aren’t working.” And what they were doing is rewriting the fundamental laws of economic theory. But it didn’t look like work. It looked like play.

Albert Einstein when he stuck on a really difficult physics problem, what his wife and his son both noted in their memoirs is he would pick up his violin. And he was a big fan of Bach concertos. And they would hear the violin clatter to the floor at times and he scramble to his desk going, “I’ve got it?” You know, frantically writing something down, right? Is the violin a distraction or a weapon?

And that I would say is at the heart. Is the walk, the rambling, ambling walk with a colleague not working or a different way of working? And those are kind of illustrative. Claude Shannon, father of information theory—literally the guy who discovered that information can be encoded in zeros and ones—wrote the most influential thesis paper in the history of the world. When he was stuck, you know what he did at Bell Labs? He would get on his unicycle and juggle. You cannot make this stuff up, okay? It’s like, stranger than fiction.

And the point is, we admire E=MC^2. We admire information theory. We admire confirmation bias as these phenomenal conceptual work outputs. And we discount the violin and the weird, kind of, unicycle juggling and the coffee break, and we don’t see the connection between those two things. And for me, I think a vendetta that I have is against this wrong placement of—this exaltation of efficiency is the end-all, be-all. Innovation is not efficient. And the question is not how can I be efficient. It’s what is effective. And effectiveness, oftentimes when it comes to innovation and breaking through, doesn’t feel efficient.

Brian: It’s funny you mention that. I think that changing the environment is a great way—I mean, I guess a personal story on this. Like, I’m also a composer and I remember I was arranging Gershwin’s piano preludes for my quintet and I was kind of stuck on—there was three preludes, I was stuck on the second one and I didn’t want to just basically take the piano parts, arrange them for the quintet and record them. We needed to put our mark on it somehow and I was kind of just stuck on it. And I was randomly—I was on vacation in Belgium—I think it was, I can’t remember—but we were on a beach and it turns out it was the international sandcastle competition was going on. And so, this giant tent—

Jeremy: This is too good. I have no idea what’s about to happen but I’m totally enthralled. This is great.

Brian: [laugh]. Yeah, it’s so there’s this giant tent protecting all these massive, you know, sand sculptures. And the theme was Disney. And so, I’m walking through and it takes you through all the movies and stuff, and these some of these things are 20 feet tall, you know, these giant castles and, like, scenes from the Little Mermaid and all of this. And I was walking out on the other side of it, and they have the little, like, rock speakers, you know, along the path, which, you know, the fake gardens, speakers, and music from Lady and the Tramp was playing, and it was this the Siamese cat song.

And so, I immediately had this idea. It’s like, well, these piano pieces that Gershwin wrote were originally written as recital closers, or encore pieces or something like this, and I’m like, “What if we imagined, like, a catfight? Two cats fighting inside of a grand piano, like during a recital? Like, what would that sound like?” Because we’re also jazz musicians and thinking about improvisation, and so that kind of got written into the tune is that you’re supposed to imagine, like, your—it’s because it’s very slow, the second prelude is [singing] it’s, like, super slow.

All of a sudden, there’s, like, it starts to break down and it turns into this, it sounds like free jazz from the ’60s. And that’s the catfight. And it wouldn’t [laugh] not have come and had I not just been randomly—I had the space in my mind, I wasn’t planning on doing anything. And I really rely on that free space and free-thinking time for new stuff to come to me. And if I’m working all the time, designing stuff, if you’re always doing all the time, it’s hard for me to open up the space to do that. And I don’t know if that’s just chance or how other people work. I mean, I’ve read that other people also feel like you need that boredom time for the other part of your brain to take over a little bit and like, [laugh] occupy a space.

Jeremy: So, the thing is, I would submit to you, anyone who’s broken through has a story like that they feel the need to apologize for. “This is kind of weird, but here’s how it happened.” Right? If you’re a nerd like me, I mostly, largely abandoned spreadsheets for the study of invention and discovery and innovation, and what I found is the weird stuff is not the exception, it’s the rule.

And yet, as a rule in our lives, we don’t want to do the weird stuff. And getting back to your question about idea generation, embrace where we go, “This feels weird.” And you know what I say? “Exactly.” It is weird, right?

And you go, “I just want it to be normal.” It’s not normal. Innovation is not normal, right? And David Ogilvy, who I admire, he’s the father of modern advertising. He said, most businessmen—and you could say, MBAs, you could say, software developers, you know, many people fall into this category—most businessmen are incapable of original thinking because they cannot escape the tyranny of reason.

And there are these moments where almost off guard as it were, where reason is not the dominant paradigm. And the Siamese cats catch you off guard and become the cats fighting in the grand piano. And it’s the unreasonable thing that’s the breakthrough. And yet we go, “Okay, well, now let’s get in the con—everybody file in the conference room and we’re just going to have very reasonable, straight-up-the-middle, good ideas. And you know what? Preferably before lunch. Somebody set a stopwatch.” Right?

We go, okay. Is it any wonder that, as we say in the book, no breakthrough starts with a shrug? And yet most of our efforts are, it’s just, like, “I don’t—you know, okay. Whatever.” Right? One of my other favorite quotes is Arthur Koestler, the Hungarian philosopher, he’s got a fantastic book, if you just have, like, a month off, read it. It’s called—after you read my book—it’s called The Act of Creation. It’s a fantastic book—seven or 800 pages long. I had Covid before the vaccine, so I had plenty of time on my hands, so I read it.

Brian: [laugh].

Jeremy: But anyway—yeah, I don’t recommend that. But one of the things that he says, he defines creativity this way—and he’s studied it across domains and centuries—he said, “Creativity is the collision of apparently unrelated frames of reference.” And that’s a beautiful definition. The operative phrase there being collision, of course, but the other being that which is apparently unrelated. And what we don’t like in our hyper-productive, hyper-efficiency-oriented view of problem-solving is we have no space for that which is apparently unrelated. What’s the relevance? What bearing does it have on the problem?

If you’re sitting in your den trying to resolve this quandary you’ve got with the sonnet or the piece that you’re working on, you’d never say, “You know what I need? I’m going to go visit a sand sculpture Disney exhibit, and listen to some crappy you know, Disney music on tinny speakers.” You know? If you said that to your friends or your wife, they’d be like, “Are you taking drugs? Like what are you talking about?”

And yet, it’s that which was apparently unrelated that ushered in the breakthrough. When you recognize that and when you study it and you see this kind of pattern recurring across history and across domains, as I have, that’s actually what led to the book is, people—there’s some mysticism here that we—it’s not mystical and there’s some mythology here, it’s not mythological. The way the brain works, we actually understand it. The way breakthroughs work we actually understand them. The difficulty is it challenges our definitions of efficiency and professionalism and all of these things.

And yet we wonder, in our highly efficient and highly professional environments, why aren’t we breaking through more? Our perspective is, well, that’s part of the point. We actually have to redefine what work looks like if we want to be ushering in breakthroughs more routinely in this era.

Brian: I feel like this gets lip service, though, a fair amount, especially in large organizations, executive manage, “We want this thinking and we need this,” you know [laugh], yet they don’t carve out the space and the time to allow for that, and the, “Waste,” quote-unquote that goes with it. I actually want to ask you about maybe how to navigate that particular fear. You know, say you’re a VP or your a director, and you know that your team needs to be doing this kind of work. And the org says it wants to, but it’s also running its efficiencies [laugh] and how much will it cost? And when will we see something for this investment? And what’s the value [laugh]? How do we negotiate that?

But before we do that, I wanted to jump back to this definition of creativity and ask you, do you have discrete definitions for creativity versus innovation, and how we think about those two things? Are they interchangeable or are they different?

Jeremy: No. No, no, no, I mean, probably my favorite definition of creativity comes from a seventh grader in Ohio, not Arthur Koestler, despite my love for Koestler. But this—and I wish I knew her name. I don’t know her name, even, but she wrote it on a Post-it note, and a friend of a friend took a picture of it, and it got forwarded to me almost, like, by telephone. Her definition of creativity is, “Doing more than the first thing that you think of.”

I think that’s a phenomenal definition, one because it has no reference to the arts, which is great because creativity is way too overly associated with the arts, which drives me crazy. Creativity is basically the art of solving problems, right? It’s doing more than the first thing you think of, and the reason that is so profound to me is it speaks to this cognitive bias that plagues us all, which is called the Einstellung effect, first demonstrated by Abraham Lutens in 1942, subsequently validated by people like Karl Duncker and researchers at Oxford. And basically what they demonstrate is, when we identify a solution to a problem, two things happen. The first is, we cease the search, despite the fact that there’s no evidence that the first solution that comes to mind is the best. In fact, there’s evidence to the contrary.

The second interesting thing is, if prompted to look for better ideas, we’re blinded to better ideas. We become fixated. And even experts will say—they’ve studied expert chess players, for example, and using eye-tracking software, they identify a move, and the proctor will say there’s a better move available to you. An expert will say they’re looking for it, but what eye-tracking software shows is they just keep going back to the move they’ve already identified. And this, I call it the anti-Einstein effect, not the Einstellung effect because our tendency to fixate on early solutions is what keeps us from breaking through.

So, this definition that creativity is doing more than the first thing you think of is a phenomenal—it’s a profound definition far beyond the years of a seventh grader because it speaks to what’s difficult for all of us, which is—Arie Kruglanski was a Russian psychologist, I think, who identified that one of the most psychologically distressing phenomena we experience is admitting we don’t know. So, we’re always seeking what he calls cognitive closure. And one of the easiest ways to arrive at cognitive closure is to say, you know, we have a brainstorm and then the first passable idea, we all go, “Phew, let’s just do that. Somebody slipped the Gordian knot, right? We’re good. Can we all—” you know, “Because my kid’s school just called. I got to go pick her up early. I think we’re good here, right?”

Because nobody wants to leave something unresolved. And so, to me, that’s the definition of creativity: doing more than the first thing you think of. Now, creativity is essential to innovation. It’d—I mean, one of my colleagues at Stanford, Bob Sutton, innovation is creativity plus implementation. So, there’s a lot more that has to be done for something to yield innovation, but ultimately, every innovation starts as an idea; starts as a solution, which starts as an idea.

And when you understand what ideas are—you know, we haven’t talked about that; perhaps we could—but what is an idea? How do they come? How do you court them? Do you have to be the victim of a breakthrough? Can you perpetrate a breakthrough? When you start to understand what’s happening in your brain, then you can actually start to bend the odds in your favor of breaking through and innovating more. Not that they’re synonymous, but one is necessary to the other.

Brian: When we first met and we were talking about this, I told you that a good half of my audience primarily works on internal data products, internal decision support applications, and tooling and machine-learning models, and AI for optimizing enterprise, right? So, internal tools, we’ll just call it for short. Can you talk to me a little bit about small innovation? We’re not building the next iPad over here; we’re helping the sales team figure out who’s the best people to call or—I use this example a lot because we all can kind of reflect on it—but how can we use this for internal tool development? How can we think about approaching things in a new way, using some of the toolset and thinking approaches that you advocate for?

Jeremy: This is one of my favorite topics, by the way. I think you already know that, Brian, but internal tool development I feel is an area that should be celebrated as a cutting edge of innovation that rarely gets acknowledged or gets the spotlight as innovation. For me, the canonical example here is AWS, which started as an internal innovation that because of Jeff Bezos’ unique mandate in the market, and the market's expectations of Amazon going into radically unexpected directions, they were able to commercialize. But AWS is a phenomenal internal innovation that was able—that now drives, you know, 90-plus percent of Amazon’s market cap. These kinds of products are phenomenal innovations and they come from a deep understanding of a real problem or a real pain point, right?

We talk about, since the 1960s at Stanford, Professor Bob McKim, the legendary progenitor of the design program at Stanford, advocated that students keep bug lists. Mind you, this is long before computer programming entered the common parlance. He wasn’t talking about errors in code. He’s talking about a list of things that bother you. What bugs you? Keep a bug list. Because he knew that things that bother you are phenomenal seeds of innovation.

Well, organizations I think one of the most unrealized assets an organization possesses is what annoys its people. Using AI or ML to improve the sales leads. If you solve that problem, you know who else needs that? Every other sales organization in the world. And not many companies have the mandate to solve other people’s problems, but when you see, when you become highly attuned to problems to be solved—and that’s why empathy gets foregrounded in design thinking.

Ideaflow isn’t a design thinking book per se, but one of the methods when we talk about becoming input-obsessed, so creative people or problem solvers, you know, creativity is a function of input more than it is an output. Most people think of the iPhone as the creative thing or the innovation, right? We think about creativity and innovation is actually a function of input, meaning what are the inputs to your thinking? To use your example of the sandcastle maze, it’s an input. The creative outcome was a function of the input.

Well, one of the fantastic inputs to innovation in organizations is connecting with individuals and understanding their problems, their internal ticketing systems that do that, all that stuff. It’s highly operationalized and implemented this point, but the means of understanding problems to be solved are incredible. The one thing I would say—and you probably know this much better than I do—I don’t believe that surveys, or voting, or things like that are necessarily the way to know what’s—the way to develop conviction as to whether something should be built. One of the things that we really espouse in Ideaflow, dedicate a couple chapters to it is early and scrappy experimentation, meaning big data isn’t what matters in the early stages, good data is what matters. So, let’s use analog because I live in the external tools world most of the time.

If I’m a—I was a management consultant, as you mentioned, I’ve been a puppy-dog-eyed, clipboard-toting in the mall food court many times walking around saying, “Excuse me, Mister. Hate to interrupt your dinner, but can I ask you, if you like my boss’s idea?” You know, what does he say? Put, “Me down for a yes, buddy. Good job, buddy. Keep it up.” Right?

Doesn’t mean it’s a good idea. But I talked to 10,000 people in the mall food court over the course of the month and I come to my a boss, and I go, “Boss, 10,000 people said they like your idea.” What should my boss say? “This data is highly suspect.” But what does he say? “Great. Let’s do it.”

And so, there are methods of data creation that are highly unreliable. Conversely, there are methods of data creation that are probably scrappier and cheaper and faster that are highly reliable. And the question is, how do we create small but reliable datasets, not large, unreliable datasets? And what I would say about—and here’s where my knowledge ends and I would maybe put it to you to say, “I don’t know how to—” what bearing this has, the question to me is what I see in a lot of internal tools, you know, discussions, forums, et cetera, is, like, voting stuff and road mapping and there’s all sorts of tools that I’m not sure they’re highly reliable for experimental mechanisms. And I wonder what internal tools folks could do if they were versed in scrappy experimentation, call it chapters four, five, and six of Ideaflow not to plug the book.

But if they were versed in scrappy experimentation where data isn’t someone’s feedback, but someone’s decision—think about how you A/B test a colorway or a button or a dial on a customer-facing app, split traffic across two different things, right? Why not do that with an internal feature? Maybe people already doing that. That’s a way more highly reliable data point than the internal Yammer, like, 50 people thumbs up to a feature request. As David Ogilvy—not to quote him again, but he said, “Consumers don’t think what they say, they don’t do what they think, and they don’t feel what they say.” And I think the same is probably true for internal stakeholders, too. What people say, what people do are very different. And the heart of scrappy experimentation is finding clever ways to discover what people do, not what they say.

Brian: I just gave a keynote for a big data conference and one of the ideas that I try to communicate in my own work as a designer trying to help the data product leadership community is this idea of sketching and prototyping, not necessarily the kind of—so designers use sketching as a way of doing low-fidelity work to get learning cycles accelerating, right? So, we’re getting feedback early, you’re avoiding the sunk-cost bias and loving the first thing that you fall in love with. You want to make it easy to throw it away and that’s part of the thing. So, my challenge for the audience is, what’s the sketching equivalent of developing an API? What’s the sketching equivalent of designing a machine-learning model? Is there some low-fidelity way that you can do that work to shortcut it to figure out whether or not someone would actually use it? And what the measurement of success is, can you accelerate that?

Jeremy: That’s right. No, speed is the name of the game. What I find this is where I think it’s counterintuitive to a lot of people. At Stanford, we have t-shirts to say, “Talk Nerdy to Me.” So, let’s talk Bayesian statistics for a moment, a priori probabilities.

What’s the a priori probability that any solution is the right solution? Or any idea is a good idea? It’s exceptionally low. You have to be exceptionally arrogant to think that most of your ideas are good. They’re not.

That’s fine, we don’t mind because then what’s efficient is actually to generate a lot. By the way, a lot becomes efficient when you know your a priori probability is low. Take is a—what I find interesting is teams that embrace rapid experimentation as the means of learning, you know what they learn really quickly? We need a way more robust ideation practice. Because when we start deploying experiments where we were at before, it took us ten days to learn this was a bad idea, as Mark Randolph says in his book, That Will Never Work about Netflix, it used to take us two weeks to learn we had a bad idea. And then we learned in a week, we had a bad idea. And then it took us a day, right?

If you’re accelerating the pace at which you learn your ideas aren’t good, which is the first step to innovation, not to realize you have a good idea but to realize which ideas aren’t good. If you’re accelerating that, if you aren’t also ramping up the backlog of other ideas to test, really quickly you run—it, it’s like, wow, we have this ability to experiment. Our problem is we don’t have any more ideas to test. And so, to me, it’s this amazing realization of the complementarity, a robust experimentation practice demands a rigorous ideation practice as well.

Brian: Do you need certain skill sets to do this work? If you’re like, “Okay, I’m sold. Like, let’s try this.” Is upskilling a team of people that don’t do this work the best way to get going? Is it bringing in talent? Is it working with designers? Like how do you recommend an organization that maybe is coming more from that analytical space and analytical thinking, like a data team or a data science team, how would they get started with this and not bail on it too quickly [laugh], like, because it doesn’t work, you know?

Jeremy: It’s a critical question. I think, ultimately, you have to think in terms of capability, not event, right? Most people when they think about innovation are the epiphany, the lightbulb moment, everything’s moment based, right? The hackathon, the sprint, the workshop, the light bulb moment. What I would challenge folks to do is think in terms of capacity, ability, practice.

It’s radically different when you think in terms of practice, right? When you think about your pianist, or your composer, if you stop doing your scales, your skills degrade quickly, right? If you’re a swimmer, if you stop swimming laps, you lose your edge. What is someone’s innovation practice? For most people, it’s nothing. I don’t have a practice. What are you talking about? Innovation practice?

Which is a problem, right? So, if you think about a capacity or an ability, you would never say you’re healthy if you’re eating junk food all the time. “I had a salad last week.” But people say they’re innovators because they participated in last quarter’s hackathon, or they updated their LinkedIn, they got a badge. It’s like, well, that not how you approach any other capacity. You are constantly nourishing it.

And we talked earlier about how executive teams and leadership teams are hyping innovation. It’s critical, and yet it’s so undernourished as a capacity. They don’t afford any space or any time. That delta is actually a real problem. The hype and the emphasis it reaches as, like, as a buzzword, the neglect it experiences as a capability.

So, the question I think you’re ultimately asking is, how do we develop the capability in our team? And it’s create small practice opportunities and recognize that practice is itself valuable. Charles Limb is a MIT researcher, he does MRI scans of the brain. And you’ll appreciate this. He studied jazz musicians and he studied hip hop artists.

You know what he found as he studied jazz musicians who were entering kind of true improvisational jazz, where they left the kind of—and he would do things where he would have them do learned pieces and then depart, et cetera. What he found as he did fMRI scans of the brain—same for freestyle hip hop artists—there was a precipitous decline in blood flow in the area of the brain responsible for judgment. They basically turned off the self-censor. So, here’s a question. Where’s the space or time where teams are encouraged to turn off judgment?

It’s a very simple thing, right? It’s not—and by the way, it just, if I’m a runner, if somebody says they’re a runner, you don’t think well, you run 12 hours a day. How do you have time for anything else? No. I go and run, like, 20 minutes a day and I’m a runner, you know? It’s something I do, right?

Okay. What I’m not advocating is willy-nilly, free-form, total abandonment of all scientific laws and principles all the time. What I’m saying is, is there ten minutes a day? You guys, I know our instinct is to judge. Let’s try to answer that if an fMRI scan where the blood flow just stops to that region if you carve out these times.

You know, we talked about in the book about having individually what we call a daily idea quota, where the basic principle there is simply, instead of looking for the idea, you look for lots. Can be to anything, right? What should the subject line of this email be? How do I open this presentation? How do I deliver this piece of feedback? How do I write this line of code? How do I engage this internal stakeholder? It doesn’t matter.

My default orientation is to look for the answer, but very few of the problems we’re trying to solve have one right answer. Most of them have hundreds of possible answers. And yet again, we tend to fixate. So, by deliberately flipping, once a day again, it’s just like touching your toes. It’s not, you don’t have to do yoga all the time to stay flexible.

Most people wonder, “Man, why do I keep pulling a hamstring when I go to the company sprint?” Well, you never stretch. Are those Cheetos stains on your shirt? You know, no wonder you pulled a hamstring. You’ve been eating Cheetos, you haven’t stretched right?

These are simple things you can do where every day you go, you know, instead of looking for the right answer, even if I know I need to get to the right answer, I’m going to try to come up with ten. I wrote a little chatbot. I mean, like, you would laugh at it because it’s so rudimentary but like, a little kind of interface just to help me do it because I know every day I want to practice this. I kid you not, the other night—true story, personal story, hashtag#VH1storytellers here—my kids broke a 114-year-old window in my house, okay? Our house is built in 1908.

And the bathroom window, after the 1,000th time they slammed the door and we asked them not to, window shatters. And I’ve got a—there’s a pickle as a father. What should the consequence of this be? It’s like it’s irreplaceable. You know, they’ve clearly disobeyed for a thousand times.

What do I do? And you know what I did? I did an idea quota. And you go, what does that have to do with innovation? It has everything to do with it. I need to stretch, I need to flex. This is a problem that has no right answer. There’s no objectively right answer to how to respond.

I joked, I told this to—I actually did a keynote in Napa last week and I mentioned this story and one of the executives there goes, “There would have been two holes in the window, one that they made and the other one where I threw them through the window [laugh] afterwards.” He said, “You were way more cool-headed. You treated it as an innovation opportunity? I just would have thrown my kid through the window.” But you know what was amazing, Brian? The 10th idea that I pushed myself to come up with was actually legitimately a breakthrough. I kid you not. I mean, I’m still surprised by [laugh] it, right? But the point is—

Brian: You want to tell us what it was? Now, I want to know.

Jeremy: Yeah. I mean, for me, it was a breakthrough. Everything’s relative, right? But you know, you get through, like, the first five or six are, like, spank them, ground them, take away their devices, all that kind of usual suspects of consequences. Tenth idea—I have four daughters—two bigger, two littler.

Have the two bigger girls prepare a lesson to teach the little ones why our household rules are not arbitrary. How interesting to have to take ownership over the rules. And in the moment, they’ve realized, whoa, we’ve slammed the doors a lot and then my parents keep saying to not slam them and look what happened. There’s glass every—it was a total disaster. There was glass everywhere. It’s like, people crying, people scared, you know.

And I never—educational opportunity? It was—it’s not the first or the third or the fifth or the seventh thing that came to my mind, right? But because I had a quota and that’s the, you know, Edward de Bono talks about the value of having a quota is you don’t latch on to good ideas because your goal isn’t good. Your goal is a number. And I had a number in mind.

So anyway, all that to say I still practice this stuff too. But there’s simple mechanisms as a leader or even as an—and you have to take individual responsibility for it just like your physical health, you have to take personal responsibility for it. And as a leader, I think you should attend to your team’s creative health. But it doesn’t mean that you got to go to, like, Zen Buddhist centers and go on silent retreats and, like, hire painters. It just means are there times where we all are thoughtfully turning off the censor, as a fundamental starting point, orienting around volume or, you know, quantity rather than quality just for a little bit of the time?

Not that we’re going to implement insanity, but we just want to play with this. What happens when we reduce the self-censor? What happens when we reduce the instinct to censor one another? That’s really valuable. My friend John Cassidy, he’s written a bunch of these guides The Klutz Guide to Juggling, for example, you may have seen it. It’s a great gift. Holiday gift guide. This can be our holiday gift podcast. The Klutz Guide to Juggling is a great book right? It comes with three, you know, really nice juggling balls. The whole first chapter, I don’t know if you’ve—have you read it?

Brian: I have not, no.

Jeremy: Okay. A lot of people I talked to have. It’s—I didn’t know it was so popular.

Brian: Oh, is this like the how to catch? Or you practice catching not throwing or something or it—

Jeremy: You throw the ball and you don’t catch it. You let anything [crosstalk 00:35:41]—

Brian: Or you don’t catch it. Yeah. I think I’ve heard about it, but I have not read it.

Jeremy: [crosstalk 00:35:43] over and over and. Like, you turn the page, do it again. Do it again. Turn the page, do it again. And I said Cass—I saw him, actually, the other day to restaurant, cafe locally—I said Cass, why the whole dropping rout—I get it. Balls got to drop. He said, “No, no, no, you don’t understand.”

If you don’t learn nothing happens when the ball hits the floor, you can never learn how to juggle. And to me, it’s a really good metaphor. The teams that don’t learn nothing happens when they have a bad idea. Literally, the world does not end. They don’t get fired. They don’t get ridiculed. Now, if they do get fired or ridiculed, that’s a leadership problem.

But if they never had the experience of the ball hits the ground, you go, “Oh, wow. Nothing happened. Well, I guess I could throw out another bad idea.” Steve Jobs would sit down with Johnny Ive—Sir Johnny Ive—every day. In Johnny Ive’s memorial address at Steve Jobs tribute, he said Steve would sit down and every day he’d say, “Hey, Johnny want to hear a dopey idea.”

And Johnny said most of the time, they were pretty dopey. In fact, sometimes they were truly terrible. But every once in a while, “They’d take the air out of the room and leave us breathless in wonder,” right? And the point is, where’s the space for dopey ideas? Every once in a while, they trigger something amazing.

When people go, “I only need really great ideas,” they’ll only have mediocre ideas. Because ideas are, like all natural phenomena, they fall in a normal distribution, right? And variation is, you know, you get to choose the variation. You don’t get to choose that’s a one-side—it’s not a one-sided distribution. And what most people do is they go, “I want to incredibly limited distribution,” which means they get a bunch of average. If you want to expand the tails of your distribution, dopey is the price of disruption. Dopey is the price of delightful.

In most teams though, you get punished for Dopey. And that’s something that if you really want to create space for divergent, collaborative idea generation, you got to make the space for the dopey, again, not because you’re implementing the dopey stuff, but because you recognize it the dopey stuff that actually leads to the delightful stuff.

Brian: I’m going to summarize something. You know, one of the core tenets here is a volume and quantity of ideas, not necessarily good ideas. That’s maybe one of the metrics if you want to try to measure what’s going on is simply understanding, if you run a team, when my team comes to me with quote, the solution, show me how many things you didn’t try, so I know at least did we go through the gauntlet of trying multiple things before we settled on an implementation. But that also requires ownership of the problem, right? Not ownership of someone asked me to make this thing for them. I don’t know why, but I’m going to make it.

To me, you’ve already cut off—there’s no reason to do innovation or to generate ideas because you’re in responsive mode. There’s no sense of ownership of the problem. So, a prerequisite to me is that the team feels like they actually own the problem space and not necessarily the solution or instruction given to them, which is go make a machine-learning model that will predict x, without knowing why and who it’s for and why that person needs it. And what would be the hurdles to them wanting to use it? Instead, it’s figuring that part out, then coming up with a bunch of ideas of which one of them maybe as a machine-learning model and maybe it is not.

Jeremy: Yes.

Brian: Am I tracking right with the way you’re—the, the—

Jeremy: It’s brilliant. It’s brilliant. That’s absolutely right. I would say—and I hadn’t thought about this way until you said that, but I’ll summarize your summary, which is, volume is evidence of ownership, which is actually really, really interesting. I was talking to—I had the chance I met Astro Teller, the head of Google X, the moonshot factory, and I was talking with Astro about this idea of volume.

He said—and it relates to what you’re saying about leaders—he said, “I always say show me five. I don’t want to see one idea, I want to see five.” And I said, “How does that—why do you do that?” He said, “Because I know that volume is actually the important thing to be measuring in the early stages. So, anytime a team comes with one idea, I say, ‘where’s your other four?’” he said, “Now, teams at X have gotten smart to my tactic and so they bring dummy ideas.” And I said, “And what’s the impact of that?” He said, “They don’t realize half the time, one of their dummy ideas is better than their good idea.” [laugh]. But it’s only the exercise of actually—he said what’s funny is trying to come up with dummy ideas sometimes leads to better ideas than the one they were going to present.

Brian: You’re almost trying to shortcut the process, by coming—“Well, we have to give five even though we’re sold on this one, so let’s just come up with four [laugh] other ones.” And it’s like your attempt to game the system fails [laugh].

Jeremy: If you start to require volume, then you start to engender ownership, you start to engender a lot of those things. So, there’s simple things you can do. I mean, another great question I would say that every leader should ask themselves is, when’s the last time a teammate shared a stupid idea with you? And most leaders, by the way, there’s two responses to this. One is, “Never,” which is I say, “You’re honest. Thank you for your honesty. Now, you have work to do.” The other answer is, “All the time.” In which case, I’d say, “You’re a jerk. You have work to do.”

The truth is, I wasn’t asking, “When’s the last time someone shared an idea that you as the leader thought was stupid?” I’m asking, “When’s the last time someone shared an idea with you that they thought was stupid.” That’s an indication of how much safety is on the team. I learned that actually from my dad. He’s a corporate litigator and he had the privilege of arguing a case before the Supreme Court a few years ago.

And I was talking to him about how his team broke through. And he said, the moment of breakthrough—we were actually talking separately about skunkworks at Lockheed Martin, these are the kinds of conversations nerds have with their fathers—we’re talking about skunkworks and how the stealth bomber was originally called the hopeless diamond because nobody thought it could fly. Because the kid who designed it with a 1,000th of the radar signature of the next best aircraft ever was a 30-year-old ki—you know he wasn’t older than the slide rules most of the aeronautics guys had. And I was talking about the value of a fresh perspective. And I was asking my dad, “Have you seen that in your work?”

And he said, “Yeah. The breakthrough in our case before the Supreme Court came,” he said, “There’s this kid in our firm, hadn’t been there two years, didn’t even know where the filing cabinets were.” And he said, “One day, he came in my office and he shut the door.” And he said, “Mr. Utley, either I’m about to say the dumbest thing a lawyer has ever said or I think I just figured out how we’re going to win this case.”

And my dad said, “That bonehead who doesn’t even know where the copy machine is figured out a way for us to win the case before the Supreme Court of the United States.” And my question to my dad was, “Dad, you’ve been there 30 years. How in the world did you create an environment where a young attorney could say, ‘I might be saying the stupidest thing that any lawyers ever said?’” That is an essential question for a team leader to ask. Do people on my team have the freedom, at least with me, to share what they truly fear could be an incredibly stupid idea?

Brian: I think that’s a great place to leave it. I love the stories here. I love that you’ve given some visual examples we can refer to here. So, the book is called Ideaflow. Where can my listeners follow you and more of your thinking on this? Do you publish anywhere? LinkedIn, Beyond the Book, et cetera? How can they get in touch?

Jeremy: Yeah. So, I’d say there’s two, kind of, big things. One is just book stuff. The ideaflow.design is our website. jeremyutley.design is my personal website. I blog there every day. I repost a lot to LinkedIn, Twitter, all that stuff, so I’m easy to find.

The other thing I would say is, if you’re an internal tools person and you think you’ve made some really cool that you think should see the light of day, my venture capital fund is always looking for interesting internal tools that actually should be externalized. We’re actually working with different teams in, you know, radically different contexts, whether it’s restaurants or synthetics or we had a call with an insulin company this morning, about taking internal, kind of, back office stuff, stuff that most organizations don’t call innovation, but actually spinning it out and capitalizing it like a startup. And we’re always looking for folks to partner with, so if you feel like you’ve done something cool, it’d be super cool to hear from you. And I’m trying to learn more about the internal tool space, so I feel like Brian, I need to almost have you on my podcasts just to interview you—

Brian: [laugh].

Jeremy: —about internal tools because there’s a ton I want to learn. And I really appreciate the chance to get share some of the ideas from the book with your audience.

Brian: Sure. It’s been great to talk to you and I look forward to linking up some of those URLs you shared in the book there. Ideaflow, again, as the book check it out. Been great to have you Jeremy. Thank you so much for coming on Experiencing Data.

Jeremy: My pleasure, be good.