Motley Fool Money - Geek Out!

Episode Date: December 2, 2023

The rules of business are changing. And those rules are being written by some … unlikely characters. Andrew McAfee is a Principal Research Scientist at the MIT Sloan School of Management and author of a number of books, including The Geek Way. Mary Long caught up with McAfee to discuss how culture shapes companies – and brings about impressive returns along the way. They discuss: The power of “geekiness” How Satya Nadella turned Microsoft around And why Amazon *wants* to see billion-dollar failures. Tickers discussed: AMZN, MSFT, AAPL, GOOG, META Host: Mary Long Guest: Andrew McAfee Producer: Ricky Mulvey Engineers: Dan Boyd, Rick Engdahl Learn more about your ad choices. Visit megaphone.fm/adchoices

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anyone who owns Amazon stock would prefer for it not to have billion dollar failures. But our prime goal is are they creating value? Should we value them more highly over time? Yes, Bezos's point is a part of that. Is this willingness to take risks and do things that are not going to pan out? And the scale at which you do that, at which you take those risks, needs to grow with the scale of the company. Amazon's a massive company now.

So Bezos said, if we're not incubating, multi-billion-dollar failures, we are not, we're not being risk-seeking enough. We're not trying hard enough to deeply innovate. I'm Mary Long, and that's Andy McAfee, a principal research scientist at the MIT Sloan School of Management. He's also the author of multiple books, including, most recently, The Geekway, the radical mindset that drives extraordinary results. I caught up with McAfee to talk about why investors should pay attention to geeky companies.

We discuss how Saty and Adela saved Microsoft from sclerosis. Why communicating less may actually be a good thing, and how Amazon's ownership culture led to the start of an entire industry, now worth hundreds of billions of dollars. You described the path to geekdom in the book as being fourfold. It's embodied by deeply valuing science, ownership, speed, and openness. How can investors, so outsiders to these companies, how can they spot those qualities in companies that they're interested?

in. It's such a great question because it's hard, right? Because I'm talking about a company's culture and our ways to assess and detect a company's culture are weak. And these four things that you described, science, ownership, speed, and openness, those are norms. Those are behaviors that the people around you expect out of you. We don't have a norm detector. I invent a hypothetical one in the book. We don't have norm detectors. As an investor, It's very hard to know what the ground truth is in a company about its culture and about its norms. Like you know, reading the annual report is a deeply lousy way to do that because that's written by a very different group of people. Luckily, we are finally getting better tools to understand what a company's culture is actually like.

In one of the chapters of the book where I'm making my argument, I rely heavily on this really fascinating body of research called the Culture 500 research, where a couple of colleagues of mine at MIT, Don and Charlie Saul, two brothers, said, wait a minute, we have a lot of people talking online about their company's cultures. In a free text, say whatever you want kind of a way. Think about glass door reviews. And they said, what we can do is use machine learning. We can train a machine learning system to extract what the person is talking about in their review of the company where they work.

and are they talking about it in favorable or unfavorable terms? Now, this isn't perfect, but nothing's perfect. This is a really cool way to systematically and consistently assess companies' cultures. When you do that, the kinds of companies that I'm talking about and that I studied, companies in what we call the tech space, although I hate that label, clustered in on the West Coast, primarily in Northern California, they jump off the page in terms of what people, say about their agility, their innovation, and their execution ability. And we used to kind of think

you could pick maybe two out of those three. But according to the people who work at these kinds of companies, these companies are doing all three. So we're getting better ways to assess culture. And those more objective assessments line up, I believe, with where a huge amount of the value creation has been happening. Oh, yeah. And that value creation, I think, is illustrated, this might sound like an easy example, but in Amazon, which you cite as a premier example, of ownership culture. And that, despite the fact that it's one of the largest companies in the world and could in another world be plagued by bureaucracy, right? So Bezos has a commitment to ownership culture and that leads not only to the development of a new business unit for the company,

but effectively to the creation of the cloud computing industry. Can you tell us that story of how that kind of came to be? It's such a wild story and I didn't know it before I started researching the book. Mary, I'm with you. Amazon. has a profound culture of ownership. I think it's the first of their leadership principles that they articulate. And Bezos, and now I think Andy Jesse, are working very hard not to let bureaucracy creep in because that's what happens by default.

It kind of comes in like barnacles on the hull of the ship or kudzu on a tree. They fight against that super hard. But what I didn't know was that early in its history, Amazon was by design a super top-heavy bureaucracy. This was Bezos's first vision for how to do innovation. You submitted your proposed innovation to this set of committees that would pass judgment on it. And if it passed all the reviews, they would give you the resources that you need.

If you didn't make that cut, maybe you escaped having to provide resources to somebody else, or maybe you didn't get your request filled and you had to go provide resources to somebody else in addition to hitting all of your own targets. This was misery. People hated it at Amazon. And Bezos, to his great credit, did about a 180-degree shift and said, nope, if we want innovation, we cannot manage it in this way. What we're learning is how to kill innovation. So that sparked this movement in Amazon to have a very modular, very, very decoupled organization with very autonomous independent units. And as you point out, building a technology stack that could enable that was, was uncertain at the time. Didn't know if you could do that in a sizable company. They did. It led directly to AWS and to the birth of the cloud, this very modular systems oriented architecture. And then they also had to decouple organizationally. And they found that the teams that worked hardest, this is where two pizza teams came from, the teams that worked hardest on reducing their

dependencies with the rest of the organization early on were the ones that had the best results later. And what you wind up with is this kind of directed swarm of companies. Think about a drone swarm, all going after the target together. Amazon strikes me that way. And there's a really good technology analyst. I'm sure a lot of your listeners follow Benedict Evans. He's fantastic. And he got this great paragraph that I quote in the geek way. He said, Amazon is a machine for building more Amazon's. And I think that's a, that's if you can pull that off, that's really, really powerful. Because then you're just like plugging more stuff in and letting the good stuff grow. You mentioned that 180-degree shift from like the way that things were at Amazon and then realizing that that was stifling innovation and pivoting to something new.

Microsoft is another great example you give in the book of a company that is one that kind of swings back and forth on this pendulum of geekiness that starts out really excelling in a lot of those categories that you mentioned and then is just wrecked by sclerosis and then manages to come back from that. How does that happen? Not without a huge amount of leadership. So I think what Satya Nadella has accomplished at Microsoft is up there, neck and neck. I don't know if it's a header behind. It's at least neck and neck with what Steve Jobs did when he came back to Apple took very different paths. But in terms of a corporate turnaround and unlocking crazy amounts of value, I can't think of anybody else that belongs in that league with Nadella and Microsoft. because if some of your listeners are old enough to remember,

the first decade of this century, Microsoft was dead in the water, right? They were a large, profitable company. Their stock price was absolutely flat. They were and also ran in the industry. And when you looked inside, there's very good reporting about Microsoft in these days. They were a massive sclerotic bureaucracy that killed good ideas for a living. And the infighting and the politics was crazy. So Nadella inherits that when he becomes,

CEO in 2014. And what he's done in not even a decade is pivot this gigantic company. And I had the chance to interview him for the book. And as I was listening to him, he's kicking off all the things that are in this geek playbook, embracing decision making based on evidence. That's science. Being more agile. Embracing agile methods for managing big projects. That's speed. Devolving authority, getting roadblocks out of the way, removing the need to ask permission from all kinds of gatekeepers inside the company. That's ownership. And then finally, and this might be the most clever thing of all, working to make a place where vulnerability, we're not being right or not knowing the answer, or not always having the perfect response at the tip of your tongue in a meeting,

where that's actually okay. That is the opposite of the kind of defensiveness that exists at most companies. And that was the rule of the day at Microsoft early on. So as I was listening to Nadella and furiously trying to take notes. I kept on saying to myself, yep, you know, this is, this is speed, this is ownership, this is openness. This is doing the stuff that geeks believe in. Your book got me to think about communication a bit differently because I think there's a temptation to think, oh, all communication is good. And what the geek way kind of emphasizes is, well, actually talking oftentimes gets in the way of doing. But you mentioned the agile method. There's still communication happening. And the agile method is a great example of this.

a lot of that communication is visual. It's not gatekeeping information or having a conversation just for the sake of talking. And not running it by somebody. It's delivering something to them and seeing if it works or not. It's very, very outcome-based results-based. And Mary, I'm with you. This was one of the weirdest things that realizations that I came to is always researching the book. This mania for coordination and communication and communication and

cross-functional collaboration and all this stuff, we do way too much of it. Now, some of it's a good idea, but we got way too fond of it over the course of the industrial era because it just provides more opportunities to block progress, more opportunities to slow things down, more chances to grab turf and to become important because you got to run the idea by me, either in a hard way or a soft way. There's plenty of soft bureaucracy out there. And what the geeks are doing is when they take this inherently modular approach and letting small teams do what they go do and iterate and try to accomplish big goals, an important part of that is stop as much of the coordination. And can I run this by you? Is this okay with you? They do a huge amount less of that. I talk to Sebastian Thron, who's just an alpha geek, entrepreneur, innovator, scientist. And he said, I tell my teams to stop all the communicate.

He had this great image. He said a team's working on something fantastic. Then they decide they want to run it up the management flagpole and then back down. And by the time it comes back down, it has so much added to it because everybody wants to add to it and make their own participation visible that it's almost unrecognizable. It doesn't bear any relation to what they started with. And if you spend any time in organizations, this happens all the time. And the geeks are trying to not, they can't eliminate it entirely. And it's not that communication is bad.

communication just for the sake of it and hey let's make sure we're all coordinated they do a lot less of that there's a lot of emphasis on the book as well on the importance of failure and shipping things before they're ready being unafraid to ideate and change and pivot even if that pivot means completely abandoning the original idea do you have a favorite pivot story from a company that you've studied as i was researching i learned how many really successful tech companies now started as something completely different a weird number of them started as online games of some kind. And YouTube was originally a dating site. I had no idea. I think Instagram started as a game. You hear these stories and the lore of the pivot in Silicon Valley, you know, you can overdo it and the

sitcom Silicon Valley made fun of it. But here's the thing. It's the opposite of defensiveness. It's the opposite of clinging to the status quo and saying, no, we're right. We just have to work a little bit harder. I need more resources. I need more time. My idea. is right. That's the default. That's the norm. We humans don't want to admit that we're wrong. We have a very strong status quo bias. We are inherently defensive. And I would much rather overemphasize the pivot than under-emphasize it because I think we've been under-emphasizing it kind of for all of corporate history until now. And this notion that you're going to be wrong a lot if you're trying to accomplish big things in a non-certain environment. And not that,

you know, failure is our goal, but failure is a thing that is going to happen on our way to our goal, and we're not going to punish it. In some cases, we're actually going to celebrate it, and we want to build a company that is okay, swinging for the fences, missing, pivoting, trying not to be so defensive. In addition to which, I think they're better places to work. I think non-defensive organizations are better places to work, because they're not full of people digging in their heels and protecting their turf and trying at all costs not to ever lose budget, headcount status, whatever. There's a lot of that going on.

It's not very much fun. There's another point in the book. You quote Jeff Bezos, which I believe it's from an old Amazon earnings call in which he talks about how failures ought to grow at the same scale of the company. And he said that he expects in hopes to one day see Amazon make multi-billion dollar failures. I think for investors, that's a really interesting point to focus on. How much should we look at the costs of failure, like actual losses as indicators of success. and the future and foundation.

Yeah, and one way to do that is to look at the company's track record over a decent length of time. All of us, anyone who owns Amazon stock would prefer for it not to have billion dollar failures. But our prime goal is, are they creating value? Should we value them more highly over time? Yes, Bezos's point is a part of that. Is this willingness to take risks and do things that are not going to pan out? out. And the scale at which you do that, at which you take those risks, needs to grow with the scale of the company. Amazon's a massive company now. So Bezos said, if we're not incubating

multibillion dollar failures, we are not, we're not being risk seeking enough. We're not, we're not trying hard enough to deeply innovate. And I think we have just seen a multi-billion dollar failure with Alexa up to now, which was not lighting the world on fire. And now on this error of generative AI, the money they've spent training all those Alexis skills, who, man, does that look like money that was not well spent? Now, again, all of us who own Amazon stock would prefer for that not to be the case. But what I really want is for Amazon to maintain its innovation engine. That involves failure. You hold up a hand. The book is effectively case study after case study of these companies that embody geekiness, and many of which we've

talked about just now. So Netflix, HubSpot, Google, Amazon, SpaceX, etc. What else do you think these organizations have to learn? They've got geekiness down. What's next? They have to learn how to stay healthier later into middle age. The conclusion of the book is actually one of my favorite chapters because I realized as I was interviewing all these alpha geeks, and as you know, Silicon Valley is not full of incredibly modest people, right? And a lot of the people I talked to had to accomplished very, very impressive things. They're confident in a lot of their opinions, but when I asked them, do you think that we have figured out finally how to build sustainably successful companies? They all laughed at me. And if I said, do you think the companies

in the tech space that are on top now are guaranteed to stay on top, they really looked at me with pity because it was such a dumb question. They said no. And there are a couple of reasons. One is competition is nasty. Competition can be tough, right? The example I give is if a startup announces a real commercial scale quantum computing tomorrow, oh, a whole lot of incumbents are in trouble, right? But that might not even be the biggest force. There are internal forces in organizations that ruin them. And two, that seem particularly relevant to me. Number one is an overconfident leader. And people who are successful build up a lot of confidence. We humans are innately overconfident. We are inherently overconfident because it's good for us. It improves our standing in

the group. And after you've done a few amazing things, you start to think that by definition, the things that you do are amazing. We look at Elon with Twitter right now or whatever we're supposed to call it. I think we're seeing a case study of an overconfident leader play out. Zuckerberg was so convinced in the metaverse that he spent billions and billions of dollars on it. That appears not to be money well spent. So overconfidence at the top is alive and well, and it will kill a company. I think even the deeper problem, though, is the fact that the interests of a company

are not inherently aligned with the interests of the people that make up the company. And those divergences can grow. You can get into factions. You can get into different flavors of infighting and political turf. And you can watch companies

just kind of tear themselves apart from the inside with no outside force doing that. I think that is a very, very, it's almost a permanent feature of human organizations. I don't think we've unlocked how to never have that happen anymore. Yeah, your book was striking to me because on the one hand, it's about individuals, how founders and leaders are largely responsible for shaping the culture of a company. But on the other hand, it's about companies. It's about multiple people and the people that actually make up that culture that's being fed to them.

And it comes at an interesting time because I think we're talking so much about wild minds. That's a phrase that I'm stealing from Morgan Housel, but these like, one, you know, this single individual that we were prone to thinking of as the reason for something happening, when your book kind of says, well, it's not about this single wild mind. It's about the many minds who sign on to a mission and about how as a unit we can build a space where that mission is allowed to thrive. Yeah, completely. And thank you for bringing that up. I think my community of people who study businesses has had the wrong unit of analysis, so the wrong focal point. We focus way too much on individuals. We focus on them as the engines of change, and we focus on them as the way

to make things better. If you made a bad decision, read a few books on better decision-making, become a more rational person. If there's bad behavior going on at the company, send everybody off to ethics training. We default to thinking about the individual as the unit of an analysis. and where to make where to affect change. I think that's wrong. Now, we do, people can change and we need to work on people. Groups are where the action actually is. We humans shape our behavior consciously and particularly subconsciously,

based on what's going on around us. We pick up signals. Again, with explicit, implicit signals, we adjust our behavior in all kinds of ways. You remember one of the, the iconic studies in psychology, was when they put some poor unsuspecting person in a room with people and flashed a bunch of simple pictures on a screen and said which of these two lines is longer and one was clearly longer than the other and everybody in the room goes duh it's line a and then everybody else except the poor subject as part of the experiment they started saying that the line that was clearly shorter was longer and most

people changed their opinion even though they knew that it was wrong just to get along with a group of strangers. We humans are so susceptible, shapeable, influenceable by our group environments that I think the group is where the action is, which is why the book is not about four things that you can do. It's about four group level behaviors, four norms that you really want to be part of and help inculcate and help stay strong in an organization over time. I'm not saying we should ignore the individual level. We got to think about the group.

The group is where the action is for us human beings. I want to talk a bit about your work at the MIT initiative on the digital economy. First off, is there anything that the digital economy doesn't touch in today's world? No, no. But we can't just call it the initiative on the economy, right? But the point that Eric and I made, Eric Brunyolfson and I, when we started, now Sanana Raul, who's the director of the center of May, is look, these digital technologies are having a huge impact on fill in the blank aspect of the economy, Whether it's jobs or wages or business models or social contagion like we were just talking about,

digital technologies are incredibly important. We need to study them and we need to have academic homes for that kind of work. Is there a digital technology that you're most excited about right now? I mean, super excited about generative AI. Okay, does the answer change if I say you can't say AI? Then I would say one that's not here yet. that's not commercial yet, we are going to get quantum computing in our lifetimes. And I think it's a matter of years, not decades, although opinion varies on that.

When we get that, scary things and amazing things are going to happen. The scary thing is, holy cow, we have to rethink our entire approach to digital privacy and security. And we might have to do it kind of quickly, especially if one of our geopolitical adversaries gets quantum computing first. Okay, this is scary. And we need to start preparing for that now. The amazing stuff is that we are going to be able to peer more deeply into nature and simulate it and understand it in ways that we absolutely can't do right now.

Our computers just don't have the horsepower to simulate properly very, very simple chemical reactions, for example. Richard Feyneman pointed this out, I believe in the 80s. This was actually the spark for quantum computing. It wasn't privacy and security. It was, we don't understand how photosynthesis happens. But boy, would it be cool if we could figure out photosynthesis? Imagine the energy transition just being finished that way. So I think it's incredibly cool, not least of all because it's just

so weird, right? Nothing makes sense in the world of quantum. And yet we're harnessing phenomena that we profoundly don't understand. I find that cool. As always, people on the program may have interests in the stocks they talk about. And the Motley Fool may have formal recommendations for or against. So don't buy ourselves stocks based solely on what you hear. I'm Mary Long. Thanks for listening. We'll see you tomorrow.