Strategy for New Companies [Entire Talk]

Welcome to the Entrepreneurial Thought Leader Seminar at Stanford. ETL is brought to you by BASES, the Business Association of Stanford Entrepreneurial Students, and STVP, the Entrepreneurship Center in the School of Engineering at Stanford. I am Ravi Balani, a lecturer in the Management Science and Engineering Department at Stanford and the director of Alchemist, an accelerator for enterprise startups. Today we are thrilled to have Professor Kathleen Eisenhardt as our keynote. How many people have heard of Professor Eisenhardt before today? Has anybody taken one of Professor Eisenhardt's classes? Okay, if not, you are in for a treat. Professor Eisenhardt's academic foundations were in engineering. She got a bachelor's degree in mechanical engineering from Brown and then a master's degree in computer science and then crossed over to the dark side when she got a PhD from the business school here at Stanford, from the Graduate School of Business, with a focus on strategy and organization. And that crossover foreshadowed the sandbox in which Professor Eisenhardt plays, where she's one of the leading researchers in the world right now on issues at the nexus of strategy and high-velocity tech-driven entrepreneurship and startups. Professor Eisenhardt's official title is the Asherman Professor of Strategy and Organization in Stanford School of Engineering. She's a member of STVP, which is the Stanford Engineering Entrepreneurship Center, and the Digital Economy Lab. And she's among the most widely cited entrepreneur scholars in the world, having authored over 100 articles in research and business journals and several books. Her most recent book with Don Saul is Simple Rules: How to Survive in a Complex World, and it was designated a top business book by the Wall Street Journal, Bloomberg Businessweek, and the Washington Post. An accomplished teacher of several popular undergrad and grad courses, Professor Eisenhardt enjoys bringing research insights into the classroom, and is currently studying exceptional growth ventures, as well as strategy making in new marketplaces, community versus firm innovation, and business model design. Professor Eisenhardt's on tons of lists, but including the Thinkers50 list of the most influential global thought leaders in business. And her research has won many honors, including the Global Entrepreneurship Research Award. Her practice-focused articles were the first to be featured on the Harvard Business Review On Point collection. And if that's not enough, Professor Eisenhardt also has 6 honorary doctorate degrees. So without further ado, please welcome Professor Eisenhardt.

Thank you, Ravi, for the great introduction and good afternoon, everybody, and thank you so much for spending your afternoon here, or at least part of your afternoon. Now, you're probably wondering what a professor can add that, for example, Andrew Ng didn't know or some other entrepreneur didn't know or what some VC didn't know. What does a professor know? Well, what we know that they don't know is we actually study lots of different companies. We study good ones, we study bad ones. And so compared to an entrepreneur who maybe have experience in 2, 3, 4, maybe 5 companies, I've seen 100. VCs tend to focus in industry, I don't focus. So what we have— what our advantage is, is we know lots of different companies. We know good ones, we know bad ones, and we also have the time to step back and think about what we're seeing. Because real entrepreneurs are super busy, they don't have much time to reflect. VCs, similarly very busy, they don't have time to reflect. And what our business is, is thinking about what we're seeing and thinking about it at a higher level. So that's why you're listening to a professor and why, what are, if you will, competitive advantages. My academic arc, I've been at Stanford longer than I like to think. But I started out studying top management teams. So one of my first breakout articles was on how do top management teams make fast decisions. I did a bunch of stuff on top management teams, some consulting, then I went to look at big businesses, then I took a little time, it was time to be a guru and you get to make money and be famous, so that was sort of fun. And now I'm back doing professor stuff, research, teaching, I'm actually on sabbatical this year, which is probably why none of you see me, but I'm on sabbatical, but I'm back researching, teaching, and doing the things that I became a professor to do. So what I'm going to do today is talk a bit about what I've learned over the years on strategy in new companies, and so that's where we'll start. But you can ask me about a lot of things. I know acquisitions, boards, all sorts of stuff that I'm not going to talk about today. So let's get started on the slides. There they are, okay. So that's our— that's the intro, and there's an orca. What I want to start out with is the idea of an opportunity is not a strategy. Airbnb started in about 2007, which as you probably know was a couple of guys in the city who were fairly poor at the time and rented out space on their floor for an air mattress, gave somebody— gave people a bagel and called it good. And that was the start of Airbnb. And they realized that actually there was a lot of uptake in what the Airbnb opportunity was. But it took them probably 18 months to figure out What's the product? What's the business model? Who the customer is and so on. So, they started thinking how it was really a convention business and it was for younger people. It turns out there are more people using Airbnb like me than are like you. So, they completely had it wrong. So, the point is that seeing an opportunity is not the same thing as having a strategy. Second point I want to just talk about is what is a strategy? Strategy is a set of— interdependent activities to create and capture value. So that's sort of the formal definition of strategy, but it's really how firms try to win against one another. In a particular place I'm going to be talking about today is strategy in nascent markets. Nascent markets are new markets, disrupted markets, and they're characterized by uncertainty, ambiguity, and speed. So we may not know who the customer is, we may not know what the product is, we have no idea who our rivals are going to be, we don't know what the value proposition is, So, they're characterized by either disruption or just being plain old new. So, that's the space we're talking about today, strategy in these kinds of markets. And the dilemma in these markets is on the one hand, you have to form a novel strategy by doing things. You can't just plan because the market is too uncertain. So, you can't plan, you have to do stuff. On the other hand, you also have to come up with a coherent strategy that fits together so that the product and the go-to-market and so on all fit together. So you have to both do thinking and you have to do doing. And the talk today is going to divide between thinking and doing. So thinking. First of all, what is thinking about? There are really three things that I think that I've seen over various studies and consulting gigs and so on that differentiate how people think well and poorly. The first of all is best entrepreneurs tend to see the entire playing field. So they are like point guards in basketball, they are like midfielders in soccer, they are seeing the whole field. The second thing is they typically don't take the playing field as given. It's something in fact they can shape. They can make it bigger, smaller. They may get a rectangle or a triangle. And then finally, they understand what game they're playing. In other words, they understand the underlying economics of the business. So let me give you a couple examples of that. This was a study that we did Roy McDonald and I did in fintech. And this was a set of companies we looked at that were trying to do something that was called social investing. And it wasn't really about social mission. It was more about the idea that there are amateur investors who are great and that other amateur investors could follow them and also be financially successful too. So that's how it started out. And what the better firms were able to do is they realized the whole spectrum of who they were actually playing with, who the customers were, who the suppliers were, but most importantly who the substitutes were. And in particular, the substitutes were the big banks like the Morgan Stanleys and USBs and so on. So it was the big banks. And so the better firms understood that in fact their rivalry was with those substitutes and it wasn't with other startups. Other startups didn't matter because they were small and trivial. Instead, what they were trying to do was disrupt substitute incumbents. So they really saw the big picture and they particularly saw the incumbents. The second idea is the idea of that they also shape the playing field. This was a study that I did a while back. It was on what we called the Internet stars. And if I told you who these companies were, you would know every one of them. But we were studying them back when they were still kind of nobodies. And what we— and this was 5 firms that have gone on to be great. And what we saw that they differentiated from themselves from the other firms that were starting at the same time, was that they were changing the playing field. And in particular, what they were doing was allying with large companies who they thought might enter and be rivals, and instead co-opted them, often gave them an equity stake to keep them out, to keep them as complementers, not as rivals. They also were acquiring other small startups, but not to get their assets, but to take them off the board as a rival. They were also engaging in a number of symbolic actions, for example, storytelling, founding storytelling. Of how the founder was this really frugal guy who drove across the country in a beat-up VW bus and— or there's other stories around, my girlfriend wanted something and so I created this marketplace. So it had these stories that were fairly colorful, kind of true but kind of not, but very catchy for the media. So what these entrepreneurs were doing was they were changing, they were shaping what the structure was, keeping certain rivals out, getting rid of other rivals and creating what they called a cognitive reference. They became the company that you thought of when you thought of that market. Another example of that was a study we did in mobile gaming. There was a time when people didn't actually know what mobile gaming was. And so it was an ecosystem of developers, games, handset makers, platforms, and brands. So a lot of different players all kind of milling around trying to figure out who owned the customer and what the business model was. Was. What the better entrepreneurs did was they had a vision of what the industry should look like and gave themselves a role that was important. Whereas the people who did not do well, the entrepreneurs who didn't do well, did not think about the entire vision, but in fact thought about building a great game. So it was all for the weaker players, it was all about building technology. For the better players, it was about seeing you actually had to put the pieces together and you had to give yourself a role and you could be an instrumental player in terms of of building relationships and building that architecture. For example, one of the things they would do is they were little companies, they would see a brand they wanted like Lord of the Rings and a particular carrier like AT&T, and what they would say to AT&T is they would say things like, I'm working with Lord of the Rings, and they would go to Lord of the Rings and say, I'm working with AT&T, and so they would— and they were sort of working with them, but they sort of weren't, but they were actually taking advantage of that information arbitrage. So that was— so essentially they were making themselves at the center. By contrast, the other folks were focusing on a great product, but sort of missing the bigger picture. An interesting just little side tip on that was that the entrepreneurs in Los Angeles got that— got the winning message much better than the Silicon Valley entrepreneurs. Silicon Valley entrepreneurs were very tech-focused. The people in LA understood —perhaps in the movie industry—that you have to put together the pieces and give yourself a good spot. Another idea is playing the correct game. One of the things that always surprises me is how little entrepreneurs understand the underlying economics of their business. You would think they would know, but in fact, they don't. Often they don't. I mean, some do, but many don't. So this is an example from the residential solar industry. And it's an ecosystem example. Actually, mobile gaming is an ecosystem example as well. But this is one where the parts of the system are you have to have panels, you have to have racking, you have to have installation, system design, sales, and finance. So there's a bunch of pieces you have to put together. And what we observed is that there are really three strategies you can use. You can use a system strategy, which was SolarCity, where you do everything. So it's a vertically integrated strategy of you do the financing, you do the panels, you do the sales and design, you do the installation. So you can do a system strategy, you can do a component strategy where you, for example, you do one piece and then partner with all the rest. For example, you do sales and design and then partner with other manufacturers, partner with finance. Or you can do the most exotic strategy was the bottleneck strategy where you figure out where the bottleneck is and then fill that bottleneck and then move your strategy. So one company that was doing that would start it in finance because finance was actually a big bottleneck for people, how do I finance it? They bundled together solar contracts and then sold them on Wall Street. But then when finance wasn't a bottleneck anymore, they actually moved to sales and design. So the point is they're actually in that particular— in ecosystems, there are actually 3 strategies you can follow. And I think it's the game, is it hearts or crazy eights? There's one of those games where you can shoot the moon. I forget what card game that is. You remember, Robbie? Crazy 8s, so you can shoot the moon, which is kind of the system strategy, or you can play it conservative, which is the component strategy, or you can just be innovative, which is the bottleneck strategy. So if those are the good strategies, what are the bad strategies? The bad strategies are just focusing on a component and forgetting that you have to put all the complementars together. So we have great finance, but we forgot to put the rest of it together. We have great sales and design, but we forgot to get the rest. Or it's straddling. Kind of like playing tennis, you either play at the front or you play at the net or you play at the back. Well, if you straddle and you're partly a component and partly a system, you don't get the advantages of either one. So actually there were bad strategies too. Another example— everybody good? Okay. This is the App Store. So this is strategies on digital goods like Candy Crush, Robinhood, OpenTable, New York Times. I'm not sure what you are, I'm sure you have apps that you probably use that I probably don't use. But the big thing in strategy in terms of app stores, digital goods is really the business model and more specifically the revenue model. So is it a paid model, is it a free model, or is it a freemium model are the key choices. And it turns out that if you do the free model, it's not really free. What it is, it's a third-party payer. Sometimes that's an advertiser and sometimes that's somebody else. Perfect example of a great app that does third-party pay is WebMD. And the key to having a free app and third-party pay is you're gathering something about the users that you can sell. So WebMD gives you insight in terms of what a particular person using the app, what health concern that person has. Is it heart disease? Is it the measles? Is it whatever? And then that allows the sale of target advertising. By contrast, the pay model requires you to be able to see quality signal. You've got a signal that this is a great app and you don't have to check it out, you know it's going to be good, you'll pay for it. New York Times is the classic example of a paid app. Finally, the interesting app is of course the freemium app and that's the hardest app to do because you have— it's a more complex programming problem and you also have to figure out what's free and what you pay for. So in Candy Crush, it was fairly simple. You pay for— you get the Candy Crush basic game, but then you can power up in various ways for the paid. But freemium tends to be more complex because you've got to figure out where to draw that line between free and pay. So that's the good— sort of the better apps in the App Store tend to have figured out which revenue model fits what they actually are doing. By contrast, what do not-so-good apps do? They pick the wrong one. For example, people will have an app and they'll say, well, somebody will sell it, it will be an advertising model. But they don't have enough information about the user to actually sell anything useful. So it's such a generic app that there's nothing special about the user that you can sell. Or they say things like they'll have a pay app and say, well, you know, people should pay $5 for my app because that's like a Starbucks cup of coffee and I put a lot of work into this and so you should pay. You know, like who cares about that? That doesn't work either. And then finally what you often see is entrepreneurs who are less savvy just avoid the freemium model because it's too hard. So weaker entrepreneurs tend to go to paid or free, but they don't understand it. More savvy entrepreneurs select smartly about among them and in particular willing to go into the effort of freemium. I'm going to talk about marketplaces in a little bit, but I'm going to skip it for now. And I'm going to say a little something about online MOOCs. This is another study we did. And what it means to be a complex established industry, what does that mean? That means an industry like healthcare, higher education, defense, where there are a number of big established players, some of whom have a commercial business logic but many of whom don't and may even not like profit. So, for example, in healthcare, there is a logic around care of the patient, there's a logic around scientific advancement, but profit maybe not so much. In higher education, where we were studying, there was a logic around, in particular, democratization of education, having it free, and so on, so very much of a social welfare logic. Profit, not so much. So, in these kinds of industries, there are a couple of different strategies, but one of the interesting ones is what we call a diplomacy strategy. If you got a lot of big institutional players who aren't so commercially oriented, what you have to do is build coalitions with them and build relationships. So, before you can even get going with the business model, you have to build relationships. And so, the more successful companies in this arena basically built relationships with higher education, built coalitions, had ambassadors, and so on, and then only later brought in the commercial side. Once the universities felt comfortable with the profit motive and then they started realizing their self-interest around profit as we at Stanford know, they figured out the better model. And final thing I'll talk about in terms of economics is unit economics, which is something we tend to forget about, particularly when you're talking about physical goods, but really any good that's got at least some variable costs. Even software has some variable costs around customer acquisition, or around, for example, customer support. The importance of unit economics, because if you can't make money on a basic transaction, like when I sell the pen, I can't make money, all you do when you grow is you lose more and more money. And so this is, again, this is the unit level. So you may choose to be unprofitable at the firm level, but it's really important to be profitable at the unit level and take that as a first priority that you do, particularly if there are any kind of variable costs. And there are a couple of reasons why that's true. One of the things is if you focus on variable— if you focus on unit economics, that means the revenue minus the cost is the profit. You, of course, are going to have more profitable unit economics, that's sort of obvious. But what you also do is you tend to also build a simpler business model. And a simpler business model is easier to replicate and easier to scale. The other thing that you get when you focus on unit economics, it forces you to look at more aspects of the business. For example, we were looking at online fashion and one of the companies we looked at was carrying inventory and sending clothing out to people, out to consumers. They started looking at shipping and then realized that they actually changed their business model to if you buy 5 products, if you buy 5 outfits, you get a cheaper price, saved on the shipping costs. They realized that they charged people $20 to use the site, they got better customers. So even though they lost some customers, they got customers who were more likely to buy. So as you you explore the costs and the revenue and the interrelationship of costs and revenues, you start to develop a better strategic understanding. So unit economics not only forces you to be more— not forces you, but encourages you or leads you to better unit economics. It leads you to simpler unit economics which scale better and leads you to a better strategic understanding of your business. By contrast, the entrepreneurs who simply focus on growth, they find product-market fit, and start growing, they never really understand the business well enough. And in the meantime, they start developing a culture of we're growing, it's great to grow, and they keep— but what they can never— what's very hard to go back to doing as you're scaling is to go back and fix the unit economics. And after a while, your funders get tired if they don't see that you're ever going to be profitable. If you're in a big market like Uber, they'll wait a long time. But for most startups, they want to see some profitability. So they'll encourage— VCs will encourage you for growth early on, but then they'll turn the tables on you around Series C and say, so when are you going to be profitable? So unit economics. So overall, what is the story here? The story is when you're thinking, see the entire playing field, particularly focusing on the substitutes, not your rivals. Little rivals don't matter, substitutes matter. Understand that you can change the shape of the playing field and then understand the basic economics of what you're doing. Okay, that's the thinking side. Let me just say a few things about the doing side. Doing side, focus on what's new. I'll do the what's new part. What's new is the idea you focus on the substitutes. What's new is that you see industry architecture can change. What's new is really the importance of economics, which I don't think many entrepreneurship courses— I'm sure some do it here at Stanford, but broadly in the world or in the States, people aren't facing, looking at the underlying economics. Okay, I'm on doing now. Everybody good? Yeah. Okay. Okay, so doing. This is— doing actually means learning. But what we've seen in learning is first of all, you have a repertoire of processes. You understand strategic timing and you use the right problem-solving strategy. I'll unpack that and tell you what that means in like real life. So this is a— we did a study of two-sided marketplaces. Again, we always look at good companies and bad companies. Bad is probably too harsh, but you know, less successful. Like I think I've seen in every study we've done, every consulting I've done, experimentation is a good thing to do. So experimentation just works. And I can talk more in the Q&A if you want me to tell you what good experiments look like. But a basic experimentation works. But what people don't always understand is it's actually very synergistic with trial and error. So engaging in trial and error and then experimenting and vice versa actually works really well. And so for example, in this marketplace, one of the companies in the marketplace was a company that we called by a pseudonym, Market Chef. And there, what they were doing was it was a business that connected travelers in Asia or around the world, but initially Asia, with local hosts where you could go and have a homemade meal. So you could go to Bangkok and go to somebody's house and have a homemade meal and a more local experience. So it was essentially a marketplace. What they did was start out with some ideas of what that marketplace was going to be. For example, they thought that the ideal host was going to be a rural poor woman. In fact, that was not. They realized that actually they needed somebody who had internet, which means you actually were more middle class, not poor, and that people actually wanted to go to cities and not so much rural areas. So it was actually a different demographic. They started to figure that out as they did some trial and error and then did some experiments to actually hone what the ideal host was. Similarly, they didn't really have an idea of exactly which cities they wanted, but they tried a few out. For example, they went to Phuket. I don't know if you all know Phuket in Thailand. Well, if you don't know Phuket, Phuket is a party place, particularly for Australians. So Australians partying, you can kind of get what that might be. It was not the same as the person who wants a quiet meal and a local experience. So they realized no more partier. So they did some more experimentation. No more party locations. What we really want to go to is a place like Ubud, which you may not— it's in Bali as well. But that's a very local cultural place with not a party crowd. So the idea is they combined experimentation with trial and error. Another example is back to the fintech ventures that I mentioned before. That was an interesting study because it showed that yes, you do experimentation and yes, you do trial and error, but there are other kinds of learning. Like you can learn from your rivals. You can actually copy your rivals if you want to. So that's imitation. You can also engage in passive learning, which just simply means you don't do anything, you just kind of watch what's going on. So the idea in that study and other studies we've done is that having a repertoire of learning processes, not just experimentation, not just trial and error, but having a repertoire that you're using is actually the most effective thing to do. Then finally, we did a study that was looking at pairs of— actually triples of new companies from Finland, Singapore, and the U.S. so culturally pretty different countries. And then we matched them on what industry they were going in. So it was kind of a matched sample. And we were looking at how they internationalized. And there the idea was, what we realized is that what people— the entrepreneurs who internationalized most effectively learned simple rules about how to internationalize. For example, they would learn— like one of them learned that actually they did better in former British Empire countries, so basically British-speaking, English-speaking countries. And then that proxied for a whole bunch of different things. Or they learned other rules around the kind of customer that would work for them. Or they learned when to be greenfield and when to be something, but they essentially learned simple rules about that process. By contrast, the entrepreneurs who learned random stuff like the French enjoy wine, or if you go out with Japanese, you may have to go out late at night and go to long dinners. So they learned sort of random stuff, but the ones who actually learned rules about what worked and what didn't could then scale those rules. And then there's the paper, and if you're interested in the book that Robbie mentioned on simple rules, talks about all the different kinds of simple rules. But essentially, it's not just that you're using a variety of processes like experimentation or trial and error, but the content of what you're learning. If it's a repeated process like hiring, like entering a new country, like hiring hosts, whatever it is, there are simple rules that will actually make you more effective. Finally getting a little near the end, so I'll just say a couple last things about timing. I prefaced this before, but let me go back to it, the idea that sometimes you just want to do nothing. I think we get an idea in entrepreneurship that it's go, go, go, you got to keep, Kind of keep rolling. In contrast, what this study showed, this turned out to be, it turned out to be the better models were marketplaces. But they put the marketplace out there and they didn't actually know who was going to use the market. And it was a market that was connecting investors and people who wanted to follow investors. So, let's say Robbie's an investor and I want to follow him and I realize, oh, I like Robbie's performance, I'm going to follow Robbie. So they just put the— they had the website out there in the marketplace and then they just watched it for a while and tried to figure out who was going to use it because they didn't really know who was going to use it. And it turned out that actually who used it was not amateur investors but in fact investors who were professional investors from small towns like Bend, Oregon who didn't really have the distribution and this was really great for them and then they went on and did some more things and they ended up with robo-investing. But the idea was they simply didn't do anything for a while. For a while. They just watched to see what would happen. Another idea is this idea I was talking about unit economics before. This study that we did in the online fashion, we looked at retail, we looked at 3 business models, retail, rental, and used clothing marketplaces. And what we saw was that it was actually a good idea to stop your growth, to hold back your growth to pause your growth so you could learn because it was too hard to learn while you were growing. So as you're perfecting your unit economics and your product-market fit, you needed to actually gate your website, close your customers, not advertise and so on so you could actually learn enough. So the point is, again, you don't necessarily always want to go as fast as you can, but you want to go— you want to understand that the timing can vary. So much like in sports, you don't always— if you're playing basketball, you don't always play up-tempo. Sometimes you cut the tempo back. It depends on who your opponent is. It depends on what's going on. So like in sports, you manage the timing. And then finally, problem-solving archetypes is a little bit abstract, but let me— this is— I want to tell you this because I think marketplaces are interesting. Marketplaces are companies like Airbnb, Etsy, Uber. So there's buyers, there's sellers, and then there's a transaction platform. And sometimes there's a geographic component to it. Like there is at Airbnb, for example. And what's interesting about a marketplace strategy, it's what's known as a complex novel problem, and some of you may know that from computer science, what complex novel problems are. Novel means new, complex means the pieces are interconnected. So buyers, sellers, platform, geography all have to fit together. And the way you actually build that is not doing everything all at once. Like when you have a mature marketplace, it's about balancing buyers and sellers and taking advantage of network effects. But when you have a new marketplace, it's not. It's about, first of all, typically figuring out and building a platform around the sellers, then the buyers, then the geography, and depending on the complexity of the platform, you fit it in somewhere. If it's a very complex platform like Uber, you do it first. If it's a more simple platform, let's say like a Poshmark, you might put it down after buyers and sellers. But the idea is you don't put the marketplace together all at once. You put— you learn one thing, then add the next thing, then add the next thing. And so what you learn, you learn the suppliers and then you pause and you don't grow it. Then you learn the buyers, you figure out who they are, pause it, then you figure out maybe— then you do the transaction platform and you hone that, and then you figure out what the geographic expansion algorithm is. And then you build it. But if you build it all together, there's too much going on and you can't manage it. So it's the step-by-step that I think people often say, oh, it's platforms and marketplaces, it must be network effects. It's not network effects until you build those pieces and you build those pieces one at a time. So that's what I mean by product architecture and then finally, just a little bit on drones. I think I'm about at the end here, yeah, I'm at the end. Let me just say, I think maybe I just won't say anything about this. You can ask me if you care about drones. But let's see here. So what am I saying? I'm saying doing is about a repertoire of learning processes, not just experimentation. Think about timing and think about how you're actually solving the problem. What's the sequence of problem-solving steps? And that's probably the most abstract part. So what's new? The idea is not just experimentation. The idea that timing matters. It's not— things like first mover advantage, scale economies, network effects. Often come later after you've gotten things right. And finally, the what to learn, not just learning. So that was, I think, my story, strategy in new markets, and because I like that picture. So anyway, any comments, questions, thoughts? Or did I tell you too much? I don't know, are you all good? So you mentioned that simple business plans are easy to replicate and easy to scale, I believe, and— Business models? Yeah, business models or strategies. Have you ever come across a simple business plan that's hard to replicate and easy to scale, or a complex plan that is easy to scale? It's the unit economics. It's the profits— if it's the revenue minus the cost. That being simple. I mostly seen if it's complicated, it's got a lot of pieces to it. For example, we looked at a marketplace where the simple marketplace connected buyers and sellers on the platform and the sellers would send the stuff to the buyers and they had made a deal with the post offices, there was a flat rate, so you only had a flat rate. The platform took a simple cut from the seller, and the seller was in charge of sending it. So that was a very simple unit economics. Another company that started at the same time doing the same thing, it was people cleaning out their closet and hoping other people would buy it, had this company carry the inventory themselves. So the seller sent the inventory to the firm. They were taking a transaction cut from the buyer and the seller, and they had variable shipping costs. And so, it was a much more complicated transaction which even if you could get that to work, it was hard to scale it. So, simpler core transactions tend to be easier to replicate, easier to scale.

[Speaker] Hi, Professor Eisenhardt. Thank you for your presentation. Could you please explain again the solving a complex and novel problem? I was thinking when you were saying that about when Microsoft didn't innovate on the cloud services, and then Gmail completely did that. So sometimes by not doing all, you cannot commit in a big blunder. So I was wondering what are your thoughts, and if you could revisit the concept of solving a complex and novel problem.

Yeah, OK, a complex novel problem is a problem where there are a lot of pieces and they're interconnected. And it contrasts with modular problems. And so if I talked about the DJI 3DR example, what I would have said is 3DR was a community, so it was a dispersed community of people who love drones. And the original business model was kits. So different members of the community were designing different parts of the drone like the rotor or some of the receiver or something. So they essentially modularized it because it was a kit. And the community was really good at that, and that is what's known as a simple problem. When the industry got more advanced and the quadrotor was developed and then you're getting what are known as RTFs, out-of-the-box drones, like the DJI quadrotor that some of you may know, came out of the box and it was ready to go. That was a complex novel product because you had to fit together all those different parts, it took aeronautics, mechanical, and so on, and so you couldn't, the community couldn't design that very well. Because you couldn't modularize it. It worked much better in a firm where you could actually coordinate people. So complex novel problems require integration and coordination. Simple problem, that's why you see software can be open source because it's modular, whereas hardware is typically hard to open source because it's not. And that's true of strategy. So marketplace strategy is another example. Marketplace strategies are highly integrative, and so you can't just out— you can't have this guy doing buyers and this guy doing sellers and this guy doing the platform all at the same time because it's too integrative. It doesn't work that way. You have to do one at a time. Thank you so much. I'm wondering if you guys have done any research on the successful founders' mindsets and their character attributes. Character attributes. Well, I think that idea of the big picture. The ability to see the whole industry and not just focus on the really techie cool thing. So seeing the whole industry I think is a really big one. The other one that I didn't talk about is the ability to think in time. The ability to understand the business today, understand it in 6 months, and understand where it's going. So you can go across the time frames. And if you can't do that, you have a partner who can do whatever the thing is that you can't do. So that ability to think in time, that ability to take the big picture, I think are two of the things that I think make for great entrepreneurs that may not be obvious to all of you.

Are there any personality traits with the great entrepreneurs?

No, I've never seen any particular personality traits. I mean, I've seen shy ones and pushy ones and sole founders and teams and all kinds of founders. So I don't know if there is a personality trait.

That's a good takeaway, that there is none actually.

Not a defining one, no. I think it's more some of these mental abilities that the better founders have that others don't. And that's certainly— they also actually understand the economics, which is again kind of a big picture idea. Hello, Professor.

First of all, thank you so much. This is very insightful. Um, I was curious about companies that are free for consumers, free for people, but then they make revenues through other companies. So say things like code editors, it's free for public to use, but if you're a company using the code editor, you have to pay for it. Yeah. So what are some of the challenges that you should keep in mind if you want to go into that space? One thing that What I understand is that you have to really build strong relations.

You have to really what?

You have to build strong relations, but how do you make sure that other companies adopt your product?

How do you make your— so this is a company that's where you're giving it away, but somebody's paying?

Yeah, basically for public it's free, but if you're a business you have to pay for it.

Okay, well then you have to have, I mean, I think I mean, everybody loves free, right? So the free part's easy, it's the pay part that's hard. And so you have to have some sort of value proposition for the companies that makes them willing to pay. And sometimes companies will do it, will pay for some sort of social good, but mostly they don't. So you have to be, so for example, when I was saying about the App Store and we have a free product and we think somebody's gonna want the advertising. Well, if there's nothing about the user that you're learning that lets you target the advertising, there's not a lot of value in that. So, there's got to be some sort of value unless it really is just a social mission. Not to say just a social mission, but a social mission.

Next question.

You mentioned geographic transaction algorithms for marketplace strategies.

Yeah. Could you talk more about that? Yeah. In fact, that's one of the really interesting things about Uber and Lyft. Uber had a fairly clear transaction geographic, essentially simple rules. And it was around go to cities where there's a lot of nightlife and sports, go to cities with bad weather, and there were a couple other things about what cities to go to. So for example, Chicago was a great place. Bad weather, great sports, great nightlife. Then there were other parts to the simple rules that were around always send an ambassador, have that ambassador have a lot of freedom, have that ambassador, or whoever's starting, the city manager sometimes it was called, targeting events and being sure you really swamp that event with let's say Uber cars. So for example, if you knew there was going to be a Beyoncé concert, you made sure that there were lots of Ubers right around the— outside the Beyoncé concert so people wouldn't have to wait long and they'd start getting in their mind, Uber is where we want to go. Another thing was making deals with hotel concierges. So Uber had a number of fairly simple rules about how to go— which markets to go into and then how to scale it. Lyft tended to be much more centralized and didn't have the rules, didn't have the simplicity that Uber did and didn't give their managers the flexibility. Sometimes that flexibility was a bad thing, but it allowed Uber to grow faster. Does that make sense? Yeah. Next question.

Can you comment on any trends you've noticed in the indoor and vertical farming space? —In what space? —Vertical and indoor farming.

—Vertical and indoor farming. I mean, I know it's happening, but I don't know much about it. I thought you're going to ask me about AI because I could actually say something about AI.

[Speaker:GHION.AI] You can add AI to the Venn diagram.

[Speaker] I'm going to segue from vertical agriculture to AI because that's actually been particularly on our online fashion study, that was a really It simply seemed to be true that human plus AI beats human. And in particular, the companies that were able to grow faster, which I didn't tell you, they've got the unit economics and then there was the growth part of it that I didn't tell you about, were using algorithms more effectively and had figured out how to pair people with the algorithm. So they were using algorithms and then they were using AI and they were then figuring out how do people and AI work synergistically together, which turned out to be a big sort of defensible moat for them. So AI, I think, is really changing strategy in some interesting ways.

But maybe there's a thread on— one of the themes that you brought up was on vertical integration. There's like 3 different verticals. Oh, in the ecosystem? Yeah. Was that part of the angle with which you were asking the question on vertical integration? Or can you give more context about why? Or was it just a generic question on—

I think it's a new market, isn't it? Using indoor hydroponic. Yeah. Yeah, I think I've heard about it, but I don't know what's going on, but what I said will be true.

And at what point should you start thinking about strategy if you're a founder? Should you think about it from day zero, or do you follow your passion first and then figure out the unit economics after you've done at least 10 engagements?

What do you do? You mean you— you don't really have a— your strategy early on is learning. So it's really all— The initial strategy is always about learning, and in particular learning product-market fit and learning unit economics. Most people get product-market fit, although sometimes they don't, but a lot of people forget unit economics and forget that— like one of my co-authors' brother is the founder of Klaviyo, which was the big IPO this year, and they actually worried about unit economics even though it's a software company. They had big— not big, but they had some variable costs around customer acquisition, and customer support. And so they actually thought through how are we going to do those on the unit economics. Very early on, yes. Very early on, right.

We have time for one more question. Thank you.

So earlier you mentioned how one way of driving out competition is through acquisition. So let's say Company X saw a rising competitor and they're like, OK, their product is pretty good, and they're trying to acquire them. But then the Company Y, which is here the smaller company, refuses to— sell essentially their product out because they know that they can scale up later on and basically be a big, I don't know, a big company.

So then what do you do at that point? The acquisition is, I mean, it's a little sketchy on the ethics of it, I think. But it's essentially if you're a small company buying a small company, you never get in trouble with antitrust. And so, and it's another kind of thing about acquisitions is, When entrepreneurs are selling their company, yes, they care about the money, but they're also selling their baby or their dog. And do you give your dog to the highest— let's say you have to move and you have to give up your dog. Do you give it to the highest bidder? No, you're looking for the good home, right? If it's your dog— I mean, of course you don't sell your baby, but your dog. And so entrepreneurs surprisingly foolishly think other entrepreneurs are going to be nicer than a big company. And that's just not true, but they think that. And so they think an entrepreneur is going to be a better home for their baby and sometimes it is and sometimes it's not. Thank you. Yes. Okay.

I had one founder describe an acquisition as giving up your baby for adoption and then having to babysit. But thank you, Professor Eisenhardt, that was fantastic.

Thanks everybody for coming. Thanks.