Passion Struck with John R. Miles - John A. List on How to Make Good Ideas Great and Great Ideas Scale EP 276

Episode Date: April 6, 2023

I am joined by John A. List, a renowned experimental economist and bestselling author, who is the Kenneth C. Griffin Distinguished Service Professor in Economics at the University of Chicago and the Chief Economist at Walmart. We discuss his new book “The Voltage Effect: How to Make Good Ideas Great and Great Ideas Scale.” In This Episode, John A. List and I Discuss His Latest Book, The Voltage Effect. In this episode, John A. List and I discuss scaling and how the meaning behind this buzzword goes deeper than just growing your following online. Full show notes and resources can be found here: https://passionstruck.com/john-a-list-on-the-voltage-effect/  Brought to you by Green Chef. Use code passionstruck60 to get $60 off, plus free shipping!” Brought to you by Indeed. Head to https://www.indeed.com/passionstruck, where you can receive a $75 credit to attract, interview, and hire in one place. Brought to you by Fabric by Gerber Life: Got to meet fabric dot com slash passion --► For information about advertisers and promo codes, go to: https://passionstruck.com/deals/  Like this show? Please leave us a review here -- even one sentence helps! Consider including your Twitter or Instagram handle so we can thank you personally! --► Prefer to watch this interview: https://youtu.be/-yutHqpncTA  --► Subscribe to Our YouTube Channel Here: https://www.youtube.com/c/JohnRMiles Want to find your purpose in life? I provide my six simple steps to achieving it - passionstruck.com/5-simple-steps-to-find-your-passion-in-life/ Want to hear all our episodes from Top Behavior Scientists: https://open.spotify.com/playlist/7D1rzGkCDxDWliRUij8Ehz?si=7caa3db29e514272  Want to hear my best interviews from 2022? Check out episode 233 on intentional greatness and episode 234 on intentional behavior change. ===== FOLLOW ON THE SOCIALS ===== * Instagram: https://www.instagram.com/passion_struck_podcast * Facebook: https://www.facebook.com/johnrmiles.c0m  Learn more about John: https://johnrmiles.com/ 

Coming up next on the Passion Struck Podcast. Scalable ideas are all alike. Each unscalable idea is unscalable in its own way, but when it's unscalable, it will be because of one or multiple of the five vital signs. So each of these five vital signs, you need to check the box. And if you check the box of each one,

you have an idea that has the DNA of something that's scalable. You still have to execute. And that's what the second half of the book is about. It's four little behavioral economic secrets to execution. But the first half really establishes there is a science of scaling in a science of ideas. And we need to start taking that science seriously. Welcome to PassionStruct. Hi, I'm your host, John Armiles. And on the show, we decipher the secrets,

tips, and guidance of the world's most inspiring people and turn their wisdom into practical advice for you and those around you. Our mission is to help you unlock the power of intentionality so that you can become the best version of yourself. If you're new to the show, I offer advice and answer listener questions on Fridays. We have long-form interviews the rest of the week with guest-ranging from astronauts to authors, CEOs, creators, innovators, scientists, military leaders, visionaries, and athletes. Now, let's go out there and become PassionStruck.

Hello everyone and welcome back to Episode 276 of PassionStruck, which is ranked by Apple as one of the top 20 health podcasts. Thank you to each and every one of you who comes back weekly. Listen and learn, how to live better, be better, and impact the world. And if you're new to the show, thank you so much for being here, or you simply want to introduce this to a friend or family member we now have episode stardopax. These are collections of our fans' favorite episodes that we organize, and to convene you topics that give any new listener a great way to get acclimated to everything we do

here on the show. Either go to Spotify or PassionStruck.com, or buy stardopax to get started. And in case you missed it, earlier this week, I interviewed Dr. Rhonda Patrick, who I've been wanting to have on the show for a very long time. And we do a deep dive on both Sanae Use and its extensive benefits, along with her secrets for longevity. In episode, you don't wanna miss,

so go check it out in case you haven't. And if you like today's episode or any of the Passion Stark episodes, we would so love it if you could give us a five star rating and review, which goes such a long way in improving our popularity, but more importantly, bringing more people into the PassionStrike community, where we can give them weekly doses of hope, meaning, connection, and inspiration. And I also know our guests love to hear from you. They love to see those reviews so that they can understand the impact that they're making on your lives. Now, let's talk about today's episode. Whether it's a medical breakthrough, a policy change,

a productive innovation, or a social movement, translating an idea into large-scale impact depends on only one thing. Whether it can be replicated at scale, while scale has become a favorite buzzword for entrepreneurs, as well as venture capitalists in the startup world, the concept extends beyond just accumulating more users or capturing more market share, rather than an art scaling is a science. It is critical to everything that we do, whether that's expanding a small business, a nonprofit, to narrowing the National Achievement Gap, to delivering billions of doses of vaccines, to making a new technology or vaccine widely affordable, and so much more.

In my interview today, John List and I cover all of this and so much more. John is the Kenneth C. Griffin, distinguished service professor in economics at the University of Chicago. He is also the chief economist at Walmart and co-director of various research centers around the world, including the John Mitchell Lab at the Australian National University and the TMW Center at the University of Chicago. He co-authored the International Best Seller, the Y-Axis in 2013, and his author to a new book, The Voltage Effect. How to Make Good Ideas Great and Great Ideas Scale. Thank you for choosing Passion Struck

and choosing me, be your host and guide on your journey to creating an intentional life. Now, let that journey begin. I am so excited today that we have John List here to join us on Passion Struck. Welcome, John. John, thank you so much for having me. Is a big fan of your show. It's about time you invited me. I've been hearing all about you from so many of my guests. And when I was speaking to Katie Melkman, who if the audience isn't familiar with her, she's a professor at the University of Pennsylvania.

She said, you've got to get John on your show. You're going to love him. And today we're going to talk about scaling a lot. But before we get into that and get into your book, I wanted to ask you, speaking of Katie Milkman, she and Angela Duckworth, co-founded an organization called The Better Change for Good Initiative. And I was hoping for the audience, you could discuss what it is and why so many researchers, scientists,

psychologists are supporting this initiative. Yeah, so first of all, when Katie and Angela call you and ask you to be part of a group that they're part of, it's really not about yes or no. It's when do we start? Katie and Angela are big deals not only in the academy, but also in trying to change the world. And I love this idea when they explained it to me and said, here's what we're going to try

to do with the mega studies, with the interactions, with government officials, with other academics, with the business world, just exactly what I've been trying to do my whole career. Since the early 90s, I've been about use the world as my lab, and they're putting that on steroids. So I just love being part of the group. It's a great exchange of ideas. It's a good way to scale your own ideas up. So I'm very excited about this. And in general, I think we're gonna learn a lot

from this process. And I think we're gonna be able to use the social sciences for good. Well, one of the things that this initiative is really doing is it's putting a ton of focus on mega studies where multiple scientists are coming in and sharing ideas, cross-pollinating the work. And I was hoping for the audience who might not be familiar, what is the difference between what is done in lab experimentation and what is done in field experimentation and why is doing this field experimentation so important? Yeah, it's a good question. So in the lab

we typically like to make it a very sterile environment. And we try to do that for a good reason. We want it to be artificial so we can pinpoint an exact mechanism that might be at work leading from a policy to a behavior. Now, that's important as an initial wind tunnel test, but we're not sure that after we take that idea from the lab to the field. And here I'm talking about running an experiment where nobody even knows that they're taking part in an experiment. It's something what I call a natural field experiment. And now this is important because that's the real world. And that's exactly what we're trying to change. And in many cases, the lab can inform what's going to happen out in the field, but until we actually do it in the field, we just won't know. And there are some cases where it looks really great in the Petri dish. And then because of some unforeseen reason, it doesn't work as well in the large. And that's a little bit, well, my book is about,

right? Scaling from the small to the large, but anytime we're using science to do in vitro or in vivo, we always want to eventually learn about what happens to the organism in the real world when we try a certain idea or a certain policy. Yeah, well, I remember when I was working at Fortune 50s and I'll just use Lowe's as an example, when we were rolling out a new initiative, we would start with this trickle approach where you'd start it in a single store, then you'd get it to a district, then a region, and then you'd roll it out, but you're right. You go into these pilots and you think you're going to have this set of results.

And then once you start going to a larger and larger population, you start seeing it change sometimes for the better, sometimes for the worse. And I think this is something we're going to talk about today. But you have a really interesting background. And one of the things I found extremely interesting, given that Lowe's example is I would have loved to have had my position also at the Home Depot, because I think as a consumer, they see Lowe's and they see Home Depot and yes, there are differences,

but you think their approach has got to be pretty much the same, and it could be no further from the truth how different the two are. And you were the chief economist, if I have it right, at both Uber and Lyft, and I was wondering if you could share, if you're able to, some of your thoughts on, although the two companies provide a very similar service,

I imagine the same thing is true about them and that there are some deep differences between how they both approach it. Yeah, it's a great question and it's a question that nobody has ever asked me before. But you're right. So I was a chief economist at Uber for two years and I quit on a Friday in the next Monday. I became a chief economist at Lyft and I was there for two years. And I quit on a Friday in the next Monday, I became the chief economist that left. And I was there for four years, and I'd left about eight months ago to take the chief economist role at Walmart. So I'm at Walmart now. But to answer your question, buy and large. These are very similar companies in many ways. For example, data is our DNA.

That's literally a sign at Uber when I started there, but Lyft lives by the exact same mantra. If you have an idea, you want a product that you push out, or you want to change something, people naturally say, where the data, and where is your science behind what you're trying to do. So to me, that is a shared feature that is extremely important because most orgs I work with, it's more about art than science. But in these two orgs, it's science first. Okay, what are some differences?

I think there are big cultural differences, at least when I was at Uber versus Lyft, I think Uber has changed since I left. I was leaving as Darro was coming, the new CEO. And the cultural differences essentially stemmed from the mission that each of the firms have. For example, if you would ask Uber people, when I was chief economist there,

tell me about Uber pool. What they would typically say is, one piece of labor, one piece of capital, and three or four revenue streams. Okay, nothing wrong with that. Now, if you would ask the people at Lyft, tell us about Lyft Line, they would say, gosh, it's a great way to get lower cost transportation

to the underserved. So there are just two very different ways to think about how to approach a specific product. And neither of them are right or wrong, it's just this is our culture and then it goes down from there from the exact team downwards and then you can imagine how the discussions are based on the mission of North Star. Now all of that said I don't doubt if Uber has moved considerably toward lift in the past, four or five years. Well, it's interesting. I happened to read the business cases as both were going through funding because I was part of the private equity world.

And I think what a lot of consumers don't realize is their long term business model is built on automation and automated drivers. So the lift and Uber we see today, 10 years from now, is going to be completely different and mostly automated. But I'll just bring up the difference between lows and Home Depot, the way that Home Depot is always gone to market is they have put their business model around the contractor. And that's how they made a lot of the decisions about how they organized the stores, etc. Lows on the other hand geared everything towards the female consumer,

which is why they made it brighter, bigger ills, back in the day. Lows, when I was there, 2005, 2010, we were doing an initiative called the seamless customer experience where we were trying to create an experience for the consumer that the same thing that you had online, you had whether you called the call center or you went in the store and it's interesting because Home Depot is embarked on the same thing now. It's called One Home Depot and I think they're spending $67 billion to try to achieve it. But it is interesting how they each web and flow over time.

Well, you had a really interesting study that I saw when you were at Uber, and you looked at, if I have the numbers right, 1.5 million riders, and you were examining the science of apologies as it related to disappointed Uber customers. I just wanted to ask because to me that's really fascinating. What did you find and did anything really surprise you from your research? Yeah, good question. So the background of that work is that I received a bad trip on Uber. And I got home that evening and I called Travis Kalanick and I let him know what I thought about his Uber app. And I told him, I am so disgusted that I'm going to become a left loyalist. And he started laughing and I said, but seriously, Travis, the worst part

about my bad experience is that I never received an apology for a mover. And he said, well, John, we haven't gotten to that yet. And I said, we have now. So I had to start by, first of all, determining the business case for bad trips. And what that means is you have to figure out how much revenue are we losing?

How much profit are we losing because of bad trips? Now here you can't really do an experiment and give people some bad trips and other people all good trips because of course you don't want to give a bad service on purpose. So what I did is my team started looking at statistical twins.

And what I mean by that is two people who are otherwise identical, one gets a good trip, one gets a bad trip. You know, whether the bad trip is they picked you up, a half hour late, or they delivered you 45 minutes late, whatever. We found that revenues lost were about 5% to 10% across cities in the United States because of bad trips. Okay, that's the business case. Now, I have to try to rectify that. So we developed a program based on you get a bad trip and we found early on that the apology

has to occur within an hour of the bad trip. Okay. Now the apology also besides being within an hour of the bad trip, it also has to include a five dollar off coupon. So what we found is an apology tacked on with a $5 off your next trip. We can get back about a third of that bad trip effect that we were experiencing. So apologies ends up being a pretty important way in which you can undo bad stuff. Now Now you could easily say, well, John, just don't have bad trips, just have better drivers. That's easier said than done when you're doing

tens and tens of millions of trips a week, right? But you're still going to have computers malfunctioning and taking a wrong turn, etc, etc. Now I do want to come back to automation because I agree with you, this industry makes it in the end. It scales in the end because of automation. But never be tricked by who the winners are in automation. It's not clear that the winners will be Uber and Lyft. The winners usually are the people who hold the unique asset. In this case, it might be the unique technologies that are making everything go. I'm not sure if the platform itself in the grid is really that unique.

So then I would look for the true winner to be someone like WAMO, who is years ahead of the game in the technology of autonomous. I think it's easier for them to put together a grid of consumers than it will be for Uber and left to develop that technology that they have. So you can say, well, who's going to get all the rents or the profits? It's probably going to be the holder of the unique asset or the unique technology.

Yes, well, I see a world in the future, whereas similar to Airbnb, where you're leasing out your residents or a rental, you're going to do the same thing with your cars. And Uber and Lyft may have their own fleet, but there may also be this day where you signify I'm not using this car because I'm going to be at work for eight hours. You can just use it and put it into your pool. But I do think speaking of Airbnb, your research on apologizing is probably something that they could implement as well because I imagine for them the stakes are even higher if you have a bad stay. Oh, yes, of course. Think that every organization can learn from that.

Apologies and how to think about in an economically efficient way, how to undo bad things that happen, whether it's B2B or B2C, it's all the same. We have to figure out how to undo bad events that just naturally happen through the course of the business year, business month, what have you. Okay. And one final question before we jump into the book. And that is you mentioned that you're

now the chief economist at Walmart. Congratulations. Big job. But if you're a listener and you hear big job. But if you're a listener and you hear John's chief economist at Walmart, what does that job entail? So what I am trying to do is build a team of economists at Walmart that will have an influence on every important economic decision that Walmart makes. Okay, what does that mean? They have 2.3 million employees around the world. They have a store in America within 10 miles of 90 percent of American households. They're getting into E-commerce and trying to have a footprint to take on Amazon and doing last mile delivery. They have 4700 stores that have a lot of employees and a lot of

pricing decisions to make. There's a Walmart Plus program now that is attempting to compete with Prime. compete with prime. I've just said four or five things, just scratching the surface, that all beg for critical thinking skills into add economics to the discussion. And I think that's exactly my chore in building a team is I want to make well-informed decisions. I want to give good advice to the CEO and other decision makers who have to make tough decisions every day. And I think having a strong data-based economic analysis of the important issues that this Fortune One company faces. Look at their footprint. The GDP of Walmart is something like just a little bit more in the size of Belgium's GDP. So I like this because small changes can lead

to big outcomes, not only for Walmart, but can also help change the world. And I think about my work with Virgin Atlantic Airways, where we taught them using behavioral economics and field experiments, how if their pilots just changed three simple things. They could save millions and millions of dollars and millions of carbon emissions. That's great stuff because once you figure out something in the small, and if it scales to the fleet, you have a real chance to make big change. And you really only make big change at scale. Yes, so I'm glad you brought up these small changes because one of the key concepts and behavioral economics has been the Nudge. And it was interesting I had Jesse Wisdom. I'm not sure if you know who she is, but

she's now one of the founders of a company called Humu, but Instead of going the academic path, she decided to join Google once she got her PhD and it's interesting because they had her use her Research to analyze why so many of Google's employees were getting unhealthy. And what they ended up finding was that in all these cafeterias where they gave everyone free food, they were putting all the sugary drinks and all the desserts right up front.

And so she had them change the entire layout of the cafeterias, had them start putting M&Ms's that used to be in clear bottles in the different break rooms into bottles where you couldn't see what was in it. Something like three, four years, I don't know how they measured it, but it was amazing. It was like she had reduced, it was something like 1.8 trillion calories and had the effect of people losing over a million and a half pounds of weight. So I just give that as an example to show the power of the work that you guys are doing. And that's on a big subset. But you can also apply this

to your own life and still have those huge results by taking small incremental steps and choices every day. John, I think that's a great point that a lot of times we'd like to talk about headline results, like a trillion pounds or tens of thousands of carbon are offset, etc., etc. But it's important to point out that all or most of these approaches we can take back to our own life. And when we do, and we stick to it,

because a lot of times what happens is humans try it for a few weeks and then it's done. Now I'm going to go to the gym and then I try it for a few weeks and it's done. Or I'm going to try a new diet and it works for a week or two and then it's done. I'm going to go to the gym and then I tried for a few weeks and it's done, or I'm going to try a new diet and it works for a week or two and then it's done. Just because you don't see changes quickly, that does not mean it's failing to work. And these behavioral interventions that we're talking about are proven scientifically. There's real science behind them. And I think it's really important for the listeners to always know that even though it's incremental, you might not see it day to day, but you will see it perhaps month to month or year to year. If a friend doesn't see you for six months and then all of a sudden sees you and says, oh my gosh, you've changed a lot,

you might not have even seen that change because you see yourself every day in the mirror. But if you take a longer viewpoint and see yourself every six months or three months or 12 months, what have you, that's where you see real change. Yeah, Benjamin Hardy has a book out on this concept called The Gap and the Gain. I'm not sure if you've had a chance to read it, but I found it fascinating because in it, he provides scientific research that shows most of us measure ourselves against the gap, which is we're comparing ourselves to others that we see as opposed to comparing ourselves to the gain, which is as you were just describing, where were we six months ago, where were we a year ago, and how have we evolved since then? And if we start measuring ourselves

against the gain and seeing the progress that we're making, it kind of underpins making more of that progress. So I love that concept that he put out. Yeah, absolutely. Well, we're going to start talking about your book, The Voltage Effect, and I'll make sure in our YouTube video we have a picture of it, etc. So the audience won't see it. But before I get in that, as I was doing the research on this, I found that you have something called the Voltage Research Project at the University of Chicago, where you're a professor. What is that project? Yeah, exactly. That's nice that you brought this up.

This is a program whereby I am trying to promote more diversity in economics. And you can say, well, what does that mean? Really economics right now is dominated by white men. And that's typically who holds the PhDs and who's teaching across the world, really. And we need to change that. We need to add first of all women, minorities, etc etc. So I set up a voltage scholars program whereby I had several dozen high schoolers come in for a week and these are high schoolers from underserved communities

who were sophomores in high school. And I really wanted to let them know this is what economics is. I wanted to teach them about economics, but also show them how to think critically, how to think about colleges going forward and to show them what's possible. I'm a first-gen kid. I think the next generation of economists needs to be much more diverse

from the than the previous few generations and that's not only because of equity. It's the right thing to do and it's fair, but also because I think the major innovations tomorrow will come from the diversity that we enhance today. And what I mean by that is I started doing field experiments in the early 90s in large part because I was a baseball card dealer. I went to conventions and I bought, I sold, I traded in the late 80s and I was learning at the same time about this wonderful world of economics in the classroom. And then I was trying to take that economics from the classroom to the baseball card shows. And I was testing economic theory. And this ends up introducing field experiments in a big way in economics, in large part,

because I'm coming from this very different world than all of the other economists. Now that's my comparative advantage. And this ends up being an important illustration of we should be doing field experiments now, and we can learn a lot from them. Who knows when field experiments would have been introduced if that hadn't been through a baseball card dealer. So there are these stories all over but we never give them a chance to play out because these

types of students never get a chance to go into the top econ programs and then get econ PhDs because they're forgotten. They're in communities where the school in is lapsed. They don't have the right infrastructure for them. And then they're never even exposed to this wonderful world that they should be in and participating in. It's only fair, it's only efficient. Well, since you brought up the Major League Baseball, I'll ask you one follow-on question about this project, and that is, I saw you did research on spatial proximity by examining the Major League Baseball draft. What was that all about? The listener may not even know what spatial proximity means. Oh, absolutely. So look, this is a paper titled nothing pro pinks like pro pink witty. Try to say that ten times. That's hard. That's hard to say. Okay. So how does this all start?

So the Chicago White Sox reached out to me and asked me for help. So they wanted help in developing a draft model for them and developing how do we evaluate talent. So I put together a machine learning model with my son and with the help of a few others. My son's a junior at Harvard study and econ in computer science. So we put together this draft model. Okay, that's good. White socks can use it now. And the draft model is super good at predicting who they should be drafting. Then we started to notice that there was a bias in how some teams were drafting. And the bias was where their director of scouting lived. They were more likely to choose players

who played around that director of Scouting. So what if you're a director of Scouting lives in Tampa, for example, you're much more likely to draft people around Tampa and Florida than if your director of Scouting lives in Phoenix, Arizona, for example. And we found that bias, which is called propinquity bias. So propinquity means you prefer people and things around you. Like your best friend might not share political views, but they might share the same floor as you in your apartment.

So these types of things happen with friendship networks in another settings, but we weren't sure if it was going to happen in the baseball draft, because that's high stakes, right? Really high stakes, but we find it does. And we find that teams give up multiple wins per year by not drafting the right players because of pro-pinklyty bias. by not drafting the right players because of pro-pinklyty bias. Wow. How interesting is that? I'm amazed. You could look at the Tampa Bay rays.

They're on the bottom third of all payrolls, and yet they're in this division where they're having it compete against the Yankees and the Red Sox every year. But yet you could say over the past decade, they've been one of the five most successful teams in baseball. And I don't know how they do their draft picks, but they have done just an amazing job of finding raw talent that they're able to develop in their minor leagues that has allowed them to compete for a fraction of the price tag that these other teams are playing. So there's definitely something here that you're talking about. So thank you for sharing that. To me, it's kind of fascinating. It's fun, right? Hey, economics is life and life is economics.

This is true. Well, since you brought up the Chicago White Sox, you obviously don't come from North Chicago, I would guess, because having grown up myself in Palatine, there is a complete divide between the city on those two teams. But speaking of the South side, I understand in 2007, 2008 timeframe, you were asked to do some experimentations in Chicago Heights examining how you could leverage behavioral economics to improve educational performance. What did you learn from that experience about scaling? Because I think it leads right into why

you wrote this book. Yeah, that's exactly right, John. So a first comment on the Cubs. I love the Cubs in terms of Eleanor Ricketts, the granddaughter of the owner, Tom. She's an undergrad here at the University of Chicago. So they understand how to make good choices. So that's a good thing, but that's where the love ends for me. And then of course, it's all with the white socks.

But so Chicago Heights, this is a community that the modern economy has left behind. This is a community that was once proud. And now 95% of households are on food stamps. This is a community that has broken families and many broken dreams. So they called me, you're right, in 2007, and asked me for my help.

And when a community like Chicago Heights calls you with a plea for help, it's not really about yes or no. If you're a humane human, it's where do we start? And where we decided to start was we built a pre-K. And that's a school for three, four, and five-year-olds. Because when you look at these underserved communities, the disparities start at birth and they continue through time.

So we wanted to start as early as we could by setting up a free pre-K or Chicago Heights. And our goals were really threefold. One, we wanted to help the community. Two, we wanted to write academic papers in which we learned about the education production function or skill formation at an early age. And in three, I wanted to create a curriculum that I could scale to the rest of the world and the rest of the underserved communities in particular. So we opened up in 2010. And by the time 2014 rolled around, we had thousands of kids who signed up,

we served all kinds of kids. We started to get great results. And the results were literally we were moving kids from like the 25th percentile on cognitive test scores all the way up to like the 60th percentile within six months. Well, we're moving them from the South side of Chicago to the North side of Chicago within six months. So we were helping kids. We were writing academic papers. Great. We're trying to teach the rest of the world what we were learning. But when I went to scale it, that's when I got to slap in the face.

So the slap in the face came basically and look professor list, it looks great in the Petri dish in Chicago Heights, but don't expect it to happen at scale. That's what they told me. Yeah, it's disheartening. And what did you do from that point forward? Yeah, so from that point forward, I started to do research on scaling. And I started to learn about the science of scaling. It's interesting because if you've ever read the

Bible, a phrase comes up occasionally that it basically says the pearls before the swine. And what they mean by that, it to me in academic terms is the pearls are you have a great idea. And then the swine is you have to scale it. And as a society, we have placed much less import or emphasis on scaling. So I started to learn about how people viewed scaling. It was things like move fast and break things, fake it till you make it, throw spaghetti against the wall, whatever sticks you cook it. Government officials were telling me this. VC people were telling me this. New firms were telling me this. And I started thinking, this is art.

This is simply art. We need to add science to these decisions. So that's when I started to write academic papers on the science of scaling. And we've written a dozen or so of these papers. Now it comes to the point of does anyone read them? Probably right in the academic paper. Maybe two people read it, right? The editor and one of the three referees who were supposed to read it. Those are your

two readers. So I decided to take stock and say, look, we have some great stuff in these academic papers. Let's unlock some of these secrets and write a popular book. That's why, literally, I decided to write the voltage effect because I wanted to translate all of the secrets that we had in those academic journal publications. So the rest of the world like you, you're not going to read the academic paper, but you're going to read the voltage effect. So at least we have a chance to change the world with our science.

Well, I think that's fascinating. And I earlier this week had a chance to talk to another one of your peers. You probably know Jay and Bayvind from NYU. And you talk about research papers not being read. Well, he and his team did one where they came up with 18 behavioral predictions around COVID. And it did catch a lot of attention so much so that another professor and his team said that they would like to peer review it once it was published. So he said he was just sitting there not knowing how this is going to pan out,

worried that they got it all wrong and it turns out that 16 out of their 18 predictions proved accurate. And the other two basically were null either way. So it didn't affect it. So that's incredible. That's incredible. That is incredible. I can't imagine being in that position, though, and having someone peer review your work. So I'm gonna go into the doctor's office and having to wait several days to see

if you have the disease that they think you might have, right? You have the symptoms and needles. Well, we're just talking about scaling and you were giving a lot of the definitions that I think we hear in San Francisco and in the startup community. But I think you define scaling a little bit more broadly than that. Can you kind of tell the audience why scaling just isn't about scaling startup company? No, absolutely.

Think about the Chicago Heights early childhood center that I led down in Chicago Heights. So I think about scaling first of all in two different ways. One is, does your idea horizontally scale? So what I mean by that is it worked in Chicago Heights. Does it work in Tampa? Does it work in DC? Does it work in New York? Does it work in Tampa? Does it work in D.C.? Does it work in New York? Does it work in Atlanta? See, what I'm moving here is I'm moving both across an input market. So I need to hire new teachers from a different place. Plus I have new outputs or new students. Okay, so that's how I want you to think about horizontal scaling. The other type of scaling that's important is vertical scaling. So what we found in Chicago Heights is that we needed to have good teachers. If we didn't have good teachers, the program wasn't going to work. We had to hire 30 good teachers. Now if I wanted

to vertically scale that, what I mean is let's say I want 10,000 Early childhood programs around Chicago. Guess what? That means I have to hire a lot of teachers, right? I only hired 30 for my one now. I have to hire 30 times 10,000 It's an entirely different value proposition to find that many good teachers You just won't so that shows you that if you want to vertically scale a highly different value proposition to find that many good teachers. You just won't. So that shows you that if you want to vertically scale and teachers are important, my program will not vertically scale because I will not be able to find that key input at scale. And that's what we get wrong a lot.

A lot of times we think it's just about the people, right? It's just about horizontally scaling. If they're different people, maybe it will or won't work. That's chapter two It's know your audience, but chapter three in the book is just as important when you're and the Petri dish Understand what are your non-negotiables and then understand, can you hire those at scale? In the same quality, the same quantity at the same price is what you did in the Petri dish. If you can, good. Your idea has the DNA of something that can work if you execute, but if you can't, you need to go back to the Petri dish and change it around to make sure that you're

using inputs that are available at scale. So now, the voltage effect is really all about when you scale something up in this vertical and horizontal way. Do you have the evidence from the P3Desh to give you confidence that the thing will actually scale? Okay. And I think it's important that you define that. And I wanted the audience to also understand

you've just given them an idea of what the voltage effect is. What is a voltage drop? Yeah, so voltage drop is when it looks great in the Petri dish, but when you scale it, the benefits just go way down per person. Like for example, when I did it in Chicago Heights, I was moving a kid from the 20th percentile all the way to the 60th. Well, a voltage drop would be if you scaled that, you'd go from the 20th percentile, maybe to the 21st.

And that's a huge voltage drop because the benefits that we thought were going to happen are much, much lower than what actually we had in the Petri dish. And these voltage drops are predictable. That's what the book tries to make clear. They're predictable based on the five vital signs. And if you don't have those five vital signs, we've talked about a few of them already, then it's predictably unscalable.

Whereas other ideas are predictably scalable. Yeah, so that begs the question, why is scalability not a silver bullet problem, but a weakest link problem? Yeah, great question. So when I talk to all of the policymakers, they viewed it as a silver bullet problem. And what they meant by that is it doesn't have the one great feature like Michael Jordan or LeBron James or Tiger Woods. They were viewing the problem as does it have that best characteristic or best feature? That's exactly wrong. The real issue around scaling is a weakest link problem or something that you might want to think of as an Anna Karinana problem. So if you go back to your days of reading Tolstoy, the very first line in Tolstoy was about

happy families, but I'm going to riff on that and put Tolstoy into scalable ideas. So here's the idea behind this notion. Scalable ideas are all alike. Each unskailable idea is unskailable in its own way, but when it's unskable, it will be because of one or multiple of the five vital signs. So each of these five vital signs you need to check the box. And if you check the box of each one, you have an idea that has the DNA of something that's scalable. You still have to execute, and that's what the second half of the book is about. It's four little behavioral economic secrets to execution, but the first half really establishes there is a science of scaling in a science of ideas

and we need to start taking that science seriously. Yeah, so I think my follow on question of that would be what are the five specific and universal causes of the voltage effect? Yeah, so the first one is false positives. You simply have a false positive in your initial study. So what does that mean? Think about when you went to get your COVID test. There's a chance that when you're positive, that was actually just a false positive. It was just

a bad reading. Now the manner in which we argue that let's try to control the false positive rate. In chapter one, I talk about how we've duped ourselves into assuming it's a lower false positive rate than it really is. Like, when I looked at government data, 50 to 70% of programs, the government scales are simply false positives. They never had a chance. They never had voltage to begin with. So, if I'll say number one's false positives. Two is know your audience. Know who is your audience? Understand how to measure.

Who is your audience? And I kind of take on McDonald's and other people who use focus groups because that's a flawed approach. And I talk about a better approach to doing kind of extensive market types of measurement. Vital sign number three is understand the situation. If you need good teachers as I talked about before, make sure you can get good teachers at scale. Vital sign number four is every idea has spillovers. So in the book I talk about four types ofillovers. One is just the behavioral effects.

Like when you put through a new incentive, they might modify their behaviors in unexpected ways. In the example I talk about is back in 1968, the federal government put seatbelts in every new vehicle. Guess what that did? It made people safer, but it also made them drive more aggressively, which unwinded some of the seatbelt effect. Okay, so that's one kind of spillover. Another kind of what happens at Facebook. When Facebook was small, it really wasn't that valuable

to its users, but as it grew, there's something called network externalities, and as some ideas grow, they become more valuable for each person who's part of the service or the network. Those are ideas that you should look for because they have high voltage at scale. And that's linked in, it's Facebook, and I talk about several examples. That's vital sign number four. And then vital sign number five, of course, is the supply side of scaling. So this is interesting because most businesses will start thinking about their ideas on the supply side. But most governments will focus on the benefit side.

And it's kind of an interesting dichotomy. I think it's because governments don't have any competition and because they their monopolist, whereas a firm, they want to make sure they can get to really low cost. So it keeps out competitors. And as you lower your cost, you can bring in new consumers. Because as you expand, of course,

you're going down the demand curve. And then these are people who value the good less than the early adopters, but you still want them as part of your market. So those are the five vital signs. Thank you for explaining those and I was going to ask you that question about social media so I'm glad you brought it up. The interesting thing to me though is as Facebook has gotten you could say more successful, more prominent, more valued. To me, the negative consequences have come out as well in the form of their profitability is driven based on how individuals use their technology.

And they understand through their algorithms what creates more viral moments. And so their algorithms tend to pick up that type of content and propagate it. But I recently interviewed Professor Douglas Rushkopf, and he has a new book called Survival of the Richest. And in there, I think he made a good point. It's a very title. Well, it's an interesting read because he gets called out to the middle of the desert to meet with four or five billionaires. And they said it was going to be a technology question, and it did turn out to be a technology

question. But it was really about how do they implement technology around the bunkers that they're going to go into when the world comes to an end. But more importantly, how can they use technology to control the staff who they won't be able to control with money at that point in time because it won't be worth. But we just talked a lot about how you just named a whole bunch of them. Whether it's, I think, LinkedIn probably less than some of the others, but whether it's been Twitter or Facebook or Instagram or whatever, how much individualism they have driven and how much it's driving us more towards an individualistic

centric world as opposed to a world-centric view, which is really damaging when you think about the billions of people now absorbed in these technologies. But anyway, I digress. No, that's a good point. So Robert Putnam wrote a book years ago. I think it's titled Bolin Alone. And the idea was these types of technologies will cause us to bowl alone. These have important societal ramifications that we need to understand, and we need to both appreciate,

but also help to attenuate and make sure that these new technologies, whether it's a personalization or an AI, doing right by all of society, just lining people's pockets. And this goes from privacy to societal norms, to societal fabric. It is a whole and these are all important issues. I'm glad that you raised those, John. Well, thank you for that. Do you reference restaurants in the book? And I thought this is a

clearer example that the audience will understand. You brought up McDonald's before and we see these large scaling companies like McDonald's, Burger King. But then you look around your neighborhood and hundreds of these small restaurants that never scale. Why is that? Great question. Chapter three is titled,

is it the chef or is it the ingredients? I looked at a lot of restaurants. You're right. So a lot of restaurants have you write. So a lot of restaurants have one restaurant and they kill it. They make a million dollars at EBITDA. And then they want a scale. They say, well, if we had 10 or 20 different restaurants, we could make 10 or 20 million in EBITDA per year, plus we would have economies of scale. So they give it a go. I'm here to tell you that unique humans do not scale. The original success of the restaurant was due to a unique chef. It will never scale. If it was due to ingredients that are available at scale at a good price, then you have a chance. Now,

unique humans don't scale yet. We try to teach people. A unique human says, I'm going to teach you to be unique. It fills every time. The only chance you have is if you systematize what the unique human does. And I'm glad you brought up Uber and left, because think about Uber and left. They've grown a lot. If they would have needed Jeff Gordon or Danica Patrick or Michael Schumacher as drivers, they would have never scaled this big.

Wouldn't have had a chance. But they could have scaled even bigger, or let's say to their size, if they could automate it. And that's exactly what you were talking about before. It's trying to automate the largest marginal cost that they have. The marginal cost of the driver is 75% 80% once you include commissions and insurance costs. So what are they trying to do? They're trying to automate it.

So that's what gives you a shot. But chapter three is really about, don't try to scale with inputs that you know can't scale. And a unique human is one of those inputs that can never scale. Well, I'm glad you brought up the whole services side. It was an area I was gonna bring up with you anyhow, but I know even

with passion struck, a lot of people have come to me and said, you should become a services firm where you're providing these services to everyone. I'm like, you don't understand how difficult it is to scale a services firm. And I spent a number of years as a practice leader at Arthur Anderson. And the way Arthur Anderson was able to scale is, and I'm sure you're familiar with it in St. Charles, they had a center even when they split with Anderson consulting that they both held onto because it didn't matter where you joined the firm.

First thing you were sent to was St. Charles to ingrain you in the methodologies that Arthur Anderson used. And we had, on the consulting side, this methodology called method one, that if you were working on any large-scale systems implementation, we all had to use the same methodology because by doing so, we were all following the same process, but it also could be quality controlled by other people who were looking at it

because they were following the same manner. And I think that's how these large firms, whether it's them, or McKenzie, or PwC consulting, who have you end up having to do it, but it is not easy to build and roll out those methodologies, ton of money. That's right. That's a great point. Well, speaking of Arthur Anderson, I eventually quit the firm. And quitting is another topic that you go into. So I just wanted to go there before we wrapped up.

Because the question I want to ask is, if quitting is repungent, why would labeling it as pivoting changed the social norms about it. Yeah, great question. So the back half of the book talks about what I call four little behavioral economic secrets to make your life better. And it introduces incentives, marginal thinking, culture, and what you just brought up quitting. So the fact is we don't quit enough and we don't quit enough because on the one hand society has taught us that quitting is repugnant. Just flat out repugnant.

Go to Google and type in inspirational quotes, quitting, and you will find enough posters to fill every museum in the world. That's how repugnant we think quitting is. Now the other reason why we don't quit enough is because we neglect our opportunity cost of time. Now that's a lot of economics so you might wonder what does this all mean? I did a big survey on recent people who had quit their jobs. And reason number one is I lost the meaning of work. Okay. Reason number two, I didn't get the pay raise, I thought I deserved. Okay. Reason number three, I didn't get the promotion, I thought I deserved. All the way down to reason number 10, I didn't like my cubicle. Every reason John was because my current job got soiled. Nobody ever said my opportunity set got better.

My opportunities are my jobs were better. That's because we don't think like that. We need to constantly think about our opportunities. And when the opportunity is really good, and it's sure, you quit and you pivot. Now, it's clear from the science we don't quit enough. So I argue that if we just called it pivoting, then our parents and grandparents and friends wouldn't be dismissive of us. Because when people people hear quitting they think you're going to sit on the college and watch TV all day. But really it's not that it's pivoting from something that is okay to something

that is great. And we should have grit, but this guided grit does nobody any good. We need to have grit, but make appropriate choices on where to spend that grit. We have a big study, Steve Levin and I designed it where we have people flip coins and then quit if it comes up heads and don't quit if it comes up tails and then in six, nine, 12 months we go back and say how happy are you? People are a lot happier when they quit. So this kind of tells you there's a lot of anxiety and angst around quitting because society has tricked us. We really should, when we're agonizing over something, figure out what your opportunity said is. If there are good opportunities in there, quit and take it, pivot. We need to do that more

often to lead better lives. Well, there's something in there that you just said that I wanna just pick up on. And when I read grit years ago, it got me thinking about what Angela was talking about at West Point because I went to the Naval Academy. And she talked about that it was grit that got the cadets through West Point. And that was part of it, but from

my standpoint, what got me through was the intentional choices I was making to apply that grit in the right manner, which is exactly what you said, which is really the backbone of Ashenstruck is it's combining that grit with intentionality and how you're pursuing your life or any initiative you're trying to get done. Well, I had one other question I wanted to ask you on how to apply this. I recently had Seth Godin on the podcast. He has a new collaboration book out right now about climate change. And as he looks at this, he's finding that there are four horsemen that are causing the climate disaster that we're all facing. But he is evangelizing that in order to fix this,

we as individuals aren't going to be able to do it, it's going to take systems change. And when I think about systems change, because these are things such as changing what companies are evaluated at from shareholder value to how they're influencing the climate, for instance. It's going to take a lot to scale some of these ideas if we want them to implement them. So how does this concept of scaling that you have in the book relate to how we could approach climate change? Yeah, that's a good question. And I have several examples around climate change

in the book, but let's just think of it this way. Behavioral change is hard. So we've been at behavioral change for a long time using nudges. So one approach using a nudge, if I want to conserve water, would be to kind of nudge people using either social norms or financial incentives to take shorter showers, for example. Okay, that will work a little bit, but it will tend to weigh in over time.

What will work better is if I incentiv it will tend to weigh in over time. What will work better is if I incentivize them to put in a low-flow shower head. Because that's a technology now that they don't have to continue to moderate. Sure, they might take a little bit longer shower, but it won't undo all the good stuff. And then when they move from their home, that technology stays, and it's there for the next person who lives there. That's a system change and it's not a behavioral modification. And I think that theory is exactly right. The situational features of our environment and changing those in a cost effective, efficient way is much easier than behavioral modification in the long run.

So I do think that the systems approach makes sense. It can guide behavior in very important ways, but see we haven't taken that seriously. We've thought more about get people to change. That takes generations. Look what happened with smoking or the war against drugs or what have you. These are still fights that go on and on. But systems changes can stick in a can stick for generation to generation. So I do agree and I think you'll find that the features of the low flow shower had idea. You change the technology. Now you have a low flow usage of water for years to come and you don't have to rely on people modifying their behaviors Okay, well we touched on just a tiny bit of the overall book and I like to do the tiny bit approach because I want people to read your book

But if a listener is there or reader picks up the book What would you hope that they take away from it? Yeah, I can take away two things. One, a new way to think about their lives. So in a way, it's a self-help book, but it's also a book to understand if you want to be an entrepreneur, or if you want to be a policymaker, or if you're raising money for a local charity, if you're starting up your own business, there's therefore you. But most importantly, it's a new way to think about the world around us. It's a new way to think about how to make change and how to make the world a better place. And I think after you read it, you're going to have a different view about ideas, about policy making, and about how to chart the proper course in your own life.

Okay. And John, if someone wants to know more about you, what is the best path for them to do that? Yeah, so either on Twitter, I'm Econ for everyone, on LinkedIn, I post a fair amount on LinkedIn. And if you just type in John List and Google, unfortunately a mass murderer will come up. So no relation in its terrible story, but he's the first guy who was caught

in America's most wanted. Oh my goodness. Because in the late 80s, so if you type in John List, economics and Google, now you'll see a ton of work on charitable giving, you'll see a ton of work with firms, you'll see a ton of work on, I bet most of the listeners have been a subject in one of my field experiments without knowing it.

Now, it's not creepy in the sense that I can't pinpoint their name to a behavior. It's not creepy like that, but I can say, what are the best ways to get people out to vote? And I can say, what are the best ways to get somebody committed to your charitable cause? I can say, what are the best ways to get somebody committed to your charitable cause? I can say, what are the reasons why intercity schools fail? So I think these are all questions that we constantly grapple with and that science can really

help. Well, thank you for that. And I really appreciate you taking the time to share this valuable message with our audience. Thank you so much again. John, thanks so much for having me and I can't wait to come back. Well, you've got an open platform to come back to because I'm sure this isn't going to be your last book as you have another best-selling book already behind you. Thank you so much.

I thoroughly enjoyed that interview with John List. I wanted to thank John, the Better Change for Good Initiative and Penguin Random House, for the honor and privilege of having them appear today on the show. Links to all things John will be in the show notes at passionstruck.com. Please use our website links if you purchase any of the books from the guests that we feature on the show. All proceeds go to supporting the show. Videos are on YouTube at both PassionStruck Clips and John Aramiles. Advertiser deals and discount codes are in one convenient place at passionstruck.com slash deals. I'm on LinkedIn and you can also find me on Twitter and Instagram at John R. Miles

where I provide daily doses of inspiration that go well beyond this podcast, but also support it. Please check it out. You're about to hear a preview of the PassionStruck podcast that I did with Isah Watson, who is a scientist, founder and CEO of Squad, and an expert in social media and connection. We discuss her debut book, Life Beyond Likes, logging off your screen and into your life.

If you are waking up in the morning and the first thing you do is check your social media or the last thing you do before your head hits the pillow at night, is check your social media, that's an addiction. The average millennial has nine social media accounts and people are spending between three and a half and four hours on social media each day. So when you add an eight hours of sleep and eight hours of work, people are spending a third of their waking hours on social media. So where does that lead time for genuine connection, spending time with your family, cooking, cleaning, all the things that you have to do every day.

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