Invest Like the Best with Patrick O'Shaughnessy - Tony Xu - A Human and Math Problem - [Founder’s Field Guide, EP. 28]

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Starting point is 00:01:25 to post a job for free. Terms and conditions apply. Hello and welcome everyone. I'm Patrick O'Shaughnessy, and this is Founders Field Guide. Founders Field Guide is a series of conversations with founders, CEOs, and operators building great businesses. I believe we are all builders in our own way, and this series is dedicated to stories and lessons from builders of all types. Founders Field Guide is part of the Colossus family of podcasts, and you can access all of our podcasts, including edited transcripts, show notes, and resources to keep learning at Join Collecent. Thank you, Patrick O'Shaughnessy is the CEO of O'Shaughnessy Asset Management. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect

Starting point is 00:02:09 the opinion of O'Shaunacy asset management. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of O'Shaunosie asset management may maintain positions in the securities discussed in this podcast. My guest today is Tony Shue, co-founder and CEO of DoorDash. Tony started DoorDash seven and a half years ago, and today it's one of the largest food delivery and logistics platforms globally, with operations in the U.S., Canada, and Australia. In our conversation, we discussed the initial problem that DoorDash set out to solve, DoorDash's counterintuitive approach to building their product, and the surprising benefits of capital constraints in DoorDash's early days.

Starting point is 00:02:50 DoorDash's business model is equal parts logistics nightmare and human coordination problem, or, as Tony put it, a human and a math problem. After talking to Tony, I feel his personality makes him a great candidate to solve all of these interesting issues. Please enjoy my conversation with Tony Shue. So, Tony, where to begin? Such an incredible business story since 2012 when you started DoorDash. Let's just start at the beginning. I love the founding insights or aha moments early on in a company's history that make you know you're going to chase after something. What is the first of those moments that you experienced in the DoorDash journey? Our founding store didn't really start with delivery. It didn't even start with food. It really started with a desire to help local business owners.

Starting point is 00:03:33 People like my mom. I grew up in a really classic immigrant family story where my family came to this country from China, came to the U.S. from China when I was five. My dad was getting his graduate degree and my mom was working three jobs a day to put food on the table. She worked for all local businesses, three of them, 12 hours a day for pretty much 12 years. I was able to moonlight as a dishwasher alongside her inside of a local Chinese restaurant. For me, that's kind of how I got motivated in the first instance to help brick and mortar businesses. And for my co-founders,

Starting point is 00:04:04 there were similar stories and pursuits. And that's really what got the co-founding team together. I think for us, the founding motivation really started with a customer segment before we actually identified any problem. And then in 2013, as the team got together and we started speaking with business owners, whether they were people like my mom and sold food

Starting point is 00:04:23 or others that sold flowers or furniture or other retail items, we discover that actually there are a lot of problems to solve. None of them are ready to compete in today's digital or convenience economy because everything was thought of in the framework and paradigm of their four walls. If you think about customer acquisition, it was about where were they located or what phone number in the phone book or on Google they were. If you thought about customer service, it happened inside the store, there and then if you got the wrong item made inside of a restaurant or you couldn't find something

Starting point is 00:04:58 inside of a retail store, all of that was solved by waiters, waitresses, clerks. Everything was done inside the four walls. But we all knew that business was happening more and more, not always inside those four walls. Everything needed to be reinvented. But look, for a small group of four people working outside of my apartment, there was no ability to solve all of those problems. We kind of have to pick and choose. So we chose the customer segment, these brick and mortar businesses. We wanted to transform them. Went through a journey of identifying different problems. We actually touched upon a couple of different problems before we ultimately landed on the problem of delivery. Really around delivery, what happened was we spoke with a local macaroon store

Starting point is 00:05:40 in Palo Alto. The store manager, Chloe, showed us a book of orders that had a bunch of customer information, even their payment details, but she had to turn all of them away because they were all delivery orders. And she was a one-person shop. She couldn't fulfill the orders as obviously she was doing a bunch of other things, just running the store. And so that was kind of the first moment in which we discovered, wait a minute, this seems bizarre. This is 2013. Something as simple as delivery should exist, yet outside of New York City, really nowhere did it exist, at least in America. That was really how we started. It really started with a founding motivation, very authentic to each of the founder's backgrounds and journeys through life. And then we identified

Starting point is 00:06:29 the problem in talking with physical business owners. I'm absolutely obsessed with this modern class of businesses that allows a creative focus for entrepreneurs and takes away the logistics or sometimes even business focus of those same entrepreneurs. It seems like you unlock a certain amount of and quality of creativity when you enable smaller businesses to do the ancillary stuff that they can't figure out themselves. And it seems like early on in that journey, network density is really important. So I know the business started as palo Alto delivery.com. So obviously that's a pretty narrow focus. What did you learn early and across the journey about the importance of network density when building something like this?

Starting point is 00:07:15 Well, certainly we didn't think too much about scalability in the early days, especially naming the service or the product. But look, I mean, when it comes to something like last mile delivery, one of the most important things is creating no density. Less about population density. I think this was one of the early insights we discovered, which was that we were fulfilling deliveries actually faster in places where the population density was much lower,

Starting point is 00:07:42 like a Palo Alto or other types of suburbs versus, say, a San Francisco, which is a much more dense city by population. But when you start getting into delivery, you start realizing, wow, there's actually a lot going on. You have to think about where all the stores are located. You have to think about how easy it is to park. You have to think about which doorway you might want to enter through

Starting point is 00:08:04 because sometimes there are alleys and sometimes there are front entrances. Sometimes one is easier to get into. versus the other. You have to think about where are all of the stores relative to where are all of the customers. Most cities in America actually follow a very nice hubbenspoke model. There's a main street in a downtown area, and there tends to be homes nearby or offices nearby that surround it. Now, a place like New York City, that's basically the ultimate no density where you have those main streets in every neighborhood, whereas for the rest of America, it's a bit more spread out. And so the early discovery for us was really thinking through what does node density look like?

Starting point is 00:08:45 Because the nodes in our system, you have stores, you have consumers. You also have where dashers, the drivers on our platform, need to be positioned. It was about creating the most node density, less so about the population density, such that we can construct the most efficient routes, such that we can create the most comprehensive and accurate catalog of what was happening in the physical world so that we can actually fulfill all of the activities necessary. It sounds like both a data and math problem on the one hand and a sales problem on the other hand. You've got to convince three different kinds of constituents in a market, dashers, consumers, and merchants, all that this is a good thing to be doing.

Starting point is 00:09:30 How did you think about solving a math and a sales problem side by side? Yeah, we've always had a saying in the company since day one, that DoorDash really is a marriage between a math problem and a human problem. We actually started by solving the human side. When I back up, and actually, when we were just starting the company, we spoke to a lot of our professors, whether it's at Stanford or Berkeley, where we studied, around actually the math behind this. Really, this type of problem have been solved before, because I think a lot of people think of the traveling salesman problem or the multi-vehicle routing problem. But in those instances, a lot of the demand and supply can be forecasted with very great accuracy or some distribution of what's to come. In our system,

Starting point is 00:10:14 well, you can't control when people get hungry or when they want to order food. You can't force Asher to accept any order. You can't require a merchant to make things faster or slower or have more things in inventory or less. All of those things are unknowns in our system. This was from a math perspective, really an unsolved problem. We actually started, therefore, by trying to understand the human problem, because in our business, it's really not the bits that we have to understand. We almost have to first collect all of the information about the atoms first. So we can create structured information about the physical world and then apply some math.

Starting point is 00:10:55 So for us, that meant doing deliveries, all of the co-founders, all of the employees in the company for the first two years in the company's life, did deliveries pretty much every single day. We would code, talk to customers, restaurant owners, and dashers. We would do deliveries in between pretty much every day, customer service included. And that was really how we learned. What were the human activities? Who were these people? What motivated them to do what they did as part of our ecosystem? and then how do we actually understand their behavior such that we can create information to solve their problems such that we can solve problems for them. What's an example of a problem set that you encountered, maybe even you, when you were doing

Starting point is 00:11:38 the deliveries early on for a restaurant owner? You mentioned the unfilled delivery orders of the macaroni maker, but give us a sense for some of these other problems that were manifest. There were a lot of problems. I think one of the early things, and this came from growing up in a restaurant, I knew that restaurants could always turn food faster than they could turn tables. No one's right now during the pandemic eating inside a restaurant. But soon, you and I will have lunch and dinner or a meal together somewhere. Physically, that restaurant owner, they're not going to kick us out out of our conversation

Starting point is 00:12:07 or our meal together, but they can certainly make more food and the excess capacity they have in that kitchen. From a business perspective, we always have the hypothesis. And this was verified as we spoke with all the restaurants that one of the problems they had was, how do I make more sales, out of my fixed costs. If you think of a restaurant more as a manufacturing plant, they have a lot of fixed costs. Rents, obviously, labor, I think sometimes is misunderstood. It's actually largely fixed. Some semi-variability when it comes to seasonality and things like this, but it's mostly fixed. So the only variable part is really the food, some of the packaging costs. And so they were always trying to think, how do I make more stuff out of my plant and make the most out of my interactions with

Starting point is 00:12:50 customers? So that was certainly one of the things we learned. I think other things that that we learned was really just how they're different customers within the side of a restaurant. You have the owners, which I think a lot of people think about, and I think a lot about their founding stories as a fellow founder, but there is this store general manager who's literally running the store day in, day out. There is the staff. That staff is divided into two. You have the back of the house where I used to work as a dishwasher. I wasn't qualified to be a chef or a helper in the back, but then there's also the front of the house, people who are serving the customers or people who are managing maybe some of the takeout operations. And there's even a whole set

Starting point is 00:13:29 that you don't even see that doesn't even work inside the restaurant, but they work with the restaurant, such as the accounting team or the team that designs the technology, payment systems, kitchen display systems, bookkeeping systems, et cetera. There are a lot of customers inside of a restaurant. The other thing you learn from a logistics point of view when it comes to restaurants is you notice that there's variability in the operations of a restaurant. Sometimes a restaurant is able to manage a different amount of orders per unit time depending on which staff is in that restaurant. Other times, restaurants have dual kitchen capacities where they have second make lines and you think about how fast that is. Sometimes restaurants have alleyways in which they may make for better

Starting point is 00:14:14 operations for something like delivery. Sometimes restaurants are located on the sixth floor of a shopping mall, in which case you have to think about, well, how do you actually get someone to go from that restaurant to meet a driver for delivery? So there are a lot of also logistical challenges as you do the deliveries that you notice about a restaurant. So that's the human component. You're in these places learning the constituents and the stakeholders. They're all different. How do you then build a team that can map that into data and on to basically make it legible to software for you to then work with? What did that early team look like? I'm curious, the intensity of the math problem. I think you read math dissertations for fun. So this is a perfect fodder for you. Just talk us through that math problem early on and ongoing.

Starting point is 00:14:59 You used to read math dissertations for fun, but with a couple of kids running around in the household, it's been a little bit trickier. In the beginning, really the team was two parts. You can think of it as engineering and operations. All the engineers did deliveries too. It wasn't like it was just the folks not writing code that were doing deliveries. Everyone did deliveries. together, really to learn some of these problems. How do you, for example, decompose a delivery into five to ten steps? And then within five to ten steps, how do you decompose that into its lowest level of detail? That was the early team. We always believed you had to get both right. This wasn't a business where sometimes in places like Silicon Valley, when we observe some of the consumer technology companies that have come in some of the earlier decades, there was kind of like one critical focus. Some companies were known as product-driven companies. Others were known as engineering-driven companies. Maybe some were known as even sales-driven companies. At DoorDash,

Starting point is 00:15:59 we kind of have to be great at all of these things. You can't say we write great code, but we don't pick up the phone if somebody were to call us about an issue or that we don't actually meet a restaurateur where they are in terms of looking at their business, looking at their P&L, and helping them actually grow sales and profits. It's a combination, of these things. And so early on, it was engineers. And then I think on the operations side, we called them Road Scholars Meeting Navy Seals. It's people who were Swiss Army knives who, I think, demanded excellence of themselves in some field. It didn't have to be professional prior to DoorDash. Almost nobody had any experience in logistics or restaurants.

Starting point is 00:16:38 They really came at the problem as a result from first principles of mapping all of the activities, creating structured information and then actually doing an appliance and technology with it. But when we last talked with this fascinating mini topic that I think is an interesting sidebar right now, which is when faced with huge potential markets and really fascinating potential problems, that sometimes it makes sense strategically to just break those problems down into something much simpler. I think the context of our discussion was around level five autonomous vehicles. Can you talk us through this kind of mental model for how to approach, yes, an exciting, big problem, but make it practical?

Starting point is 00:17:16 We have a saying internally at the company to dream big, but to start small. And that's because I think it's really important to know where you're going. That's the dream big part. But it's also really important to get going. And it's really hard to get going on a big problem when you're an under-resourced team or maybe you don't even yet have the capabilities or the knowledge of what problems you're going to encounter. I mean, that was the story of DoorDash.

Starting point is 00:17:41 When we started, the goal was to transform every brick and border business, building them a marketplace to give them demand and also to build them a platform in which we can give them tools to create their own digital businesses. But that was way too big of a problem statement for the four of us to get started on. And so we narrowed that problem down to delivery. We narrowed delivery down to restaurants only, not all types of stores. And then we narrowed that down to one locale called Palo Alto. which is where we started. Even within Palo Alto, we narrowed that down to one street on Palo Alto, which at that time was University Avenue. There were a couple of main streets with restaurants, but at the time we focused on University Avenue. And so the point being that the vision was

Starting point is 00:18:25 always to work on a much bigger problem, but taking the first step and which first step to take, I think is really important because it does have some path dependence depending on which position you took. How do you think about variance in all of this? If you're thinking, about the future and you're dreaming big, some dreams have higher or lower variance. How does that play into how you think about running a business and planning in general? I'm still trying to develop our own mental models on them. I'm constantly learning about different models to handle variance. The first thing that we tend to do when we look at problems that have high variance is we try to reduce the scope of the problem. Usually variance is something that builds on

Starting point is 00:19:11 multiple risks. If you talk about something like climate change, it's not one thing. I wish it were because we could solve it much more quickly or even our current COVID pandemic. It's not just one thing about understanding the disease, but also everything from vaccine distribution and masks and containment. There's a lot of things that add to variance. The first thing that we try to do when it comes to variances, we try to simplify the problem and reduce the variance in some sense. And maybe in the early days, we don't know what that means. We just have to almost look at the major components. Take, for example, when we started DoorDash, there was huge variance on understanding

Starting point is 00:19:51 whether or not you can actually build a sustainable business facilitating all of these moving parts of consumers, merchants, and dashers, for instance. Okay, so what did we do? What we did was for each audience, we kind of took a hypothesis, what we thought, it would take to almost manufacture an outcome that we wanted. So for consumers, we thought that they would be willing to pay for convenience. We set a price on that. Merchants, that they would be willing to pay for incremental business. We set a price on that. And that dashers would be willing to earn in this flexible way. And we set a price on that. We didn't know. It wasn't like there were rules

Starting point is 00:20:32 of engagement here, but we try to manufacture that outcome early on. The whole point is just to get going. so that we can collect information about understanding which parts did we get wrong. It's actually to look for the disconverning evidence. That's actually why we start with the hypothesis. And then what you can do is if you can reduce variance on each one of your hypotheses, then what I would argue is, A, you can get going faster because you're solving simpler problems by reducing the scope of variance. And B, you start understanding the interplay.

Starting point is 00:21:03 Because a lot of times big problems where it's become really hard to solve and sometimes why it requires, at least in our opinion, interdisciplinary kinds of ways that looking at them, is because you have interplane dynamics. In our marketplace, for example, every order touches consumers, merchants, and dashers. Okay, well, we of course have interplane dynamics, and there are sometimes even externalities, such as inclement weather. And all of these things do happen every day. Traffic happens every day.

Starting point is 00:21:34 Sometimes staffing shortages happen every day at store. or inventory outages happen every day. These are all things that contribute to greater and greater variance. The point is to reduce the scope, therefore you can understand where the variance is being caused, but most importantly, it means you can get gone. What about time? Their scope is one dimension in complex systems, high variance situations. More time seems like could be a gift or a curse.

Starting point is 00:22:03 How do you think about time as a variable in planning for where to go? next in the business. Startups and technology, it almost feels like time is always against you. You can never do something right faster or sooner. And that's why again, back to the point of getting going, I think is one of the most important points. But with respect to something like time, especially when the variance leads to possibly irreversible outcomes or consequences or consequences that just have large magnitude, maybe not let irreversible per se, but very high magnitude, That's when actually you almost have to put a mental block on the get going, and then you have to start taking more time up front to think through the sequencing of what it is that you want to do. Because maybe you don't have to make a certain decision today.

Starting point is 00:22:54 And by the way, if you made that decision today, it could really cost you. Like I said, a very, very high consequence. When there is the time component, one of the things we try to think about is at which point do we need to make certain decisions. Is there a good example in the company's history of a high consequence decision that you intentionally slowed the action process down for that you think was the right decision to slow it down? One of the most important decisions made me very early, as early as month one of the company's life, was we actually spent very little time building the consumer product.

Starting point is 00:23:32 Actually, our very first product as a consumer product was actually our DASHR app. Back to this notion of how do you actually build a system of last mile delivery where you can bring everything inside of a neighborhood to consumers in minutes, not hours, or days, we actually decided to not work on maybe what seems to be most obvious, which is a consumer product in which you can find all of the things or buy all of the things from all the restaurants near you. Instead, we said, that can wait. We built a website so that you could actually order. in the very, very V1 of the company's life, the product was a phone number that rang Google

Starting point is 00:24:11 voice that rang the cell phones of the founders. And that's because the core thesis we were testing was if we delivered from places that never offered delivery before, would you care? And how would we actually deliver upon a good enough experience such that you would care enough to come back? We focused instead, and really for probably a couple of years when I look back on it, on spending, when I think about the allocation of time for our engineering team, 90 plus percent was dedicated in the earliest years to dashers and to merchants. And this is all building things that consumers could not see, a dasher app that a consumer cannot see, a logistics dispatch system that nobody could see, an exception handling system,

Starting point is 00:24:56 point of sale integrations, kitchen display integrations on the merchant site, a merchant portal, a merchant tablet and other order protocol systems such that they can actually receive orders and communicate to us back and forth. Those are things in hindsight were very expensive decisions. I mean, a couple of years time, right? A very precious, small number of engineering hours that we actually had were dedicated instead to that. But that's because we thought the core hypothesis to test in this whole system was, if we could

Starting point is 00:25:28 bring it to you, would you actually care? It's not like delivery is this new thing. If you think about it from first principles, well, maybe the reason why delivery isn't outside of New York City is because no one cares. Consider the alternative where we spent two years instead building the consumer product, but maybe we didn't spend as much time on other components, such as the dispatch system or the merchant products, and maybe we couldn't deliver from the places you wanted, or we couldn't deliver accurately or on time.

Starting point is 00:25:57 If you think about the two paths in terms of the emphasis on which product approach we took, you might reach very different conclusions about the likelihood of success of this business, which over time created lots of value. I think you have to have some points of view. So our point of view, it started with having a point of view that it was really about making sure that the product wasn't necessarily the UI of the consumer app, but much more so can we bring you what you want in the time that you expect, and in the condition that you would expect. And if we can do that, then we could buy ourselves

Starting point is 00:26:33 time to work on other things. And along the way, we're collecting information. It wasn't like it was just, okay, we must just stick with this hypothesis for two, three years. And then let's see what happens at the end of it. Along the way, we're collecting information every single day. It's a really interesting story because the classic view of a two-sided marketplace would be often that demand is much harder to get. If you aggregate the, the demand, suppliers will tend to show up. Suppliers like selling stuff. They like business.

Starting point is 00:27:02 They like lead gen. But in this case, really, you're working on behind the scenes harder work. It seems like it's clearly much harder to build everything you just described than a front-end consumer UI. When you did get to the consumer side and started building that UI, what did you learn then about generating demand that belonged with this great new infrastructure you had built for dashers and for merchants? I think there were a couple of different inflection points.

Starting point is 00:27:29 The first was just the realization that consumers came for really the content that we were showing them. The amazing local Mediterranean hummus shop, the amazing cake store, your favorite fast food place, whatever it was, that was probably the first recognition that the content was what people were coming to look for, more so than any other consideration. I mean, obviously, consumers have to vote with their wallets on many dimensions. What can I get delivered? How fast can I get it delivered? How expensive or affordable their services? In the case that something went wrong, how good was customer service? Obviously, they're judging us along many dimensions, but the very first one, we thought, was the content.

Starting point is 00:28:15 How did you think early on, given that this is such a network-driven business? You're building tools to serve a big network that's complicated. And to be successful, obviously, you have to kind of own a liquid network. How do you match that in the early days of company building against what I'll call unit economics? The gross profit that DoorDash makes on a per delivery basis or a per dasher workday or whatever the right unit is, it seems like those two things might be at odds and that you had to make strategic choices early on and maybe ongoing between network health and unit economics. How did you deliberate between those two things? I might slightly change the premise where I don't know your unit economics in a marketplace

Starting point is 00:29:01 and your network health have to disagree. I think what might disagree is your overall company profitability and maybe your network health. I think what's important in that process, though, is to make sure that your unit economics always work. And that was true for DoorDash. And one of the things that really helped with this was a constraint, which was our budget. We had very little money in the early days. Doras struggled, raise a seed round, and when we got started.

Starting point is 00:29:27 So we had very constrained wallets. And as a result, I think we started noticing that something seems to be working because our bank accounts are not going down, even though we have a very small bank account. Part of that, I kind of say this tongue in cheek, but was this maniacal focus on always making sure that our unit economics for orders worked. In fact, when I look back over the seven and a half years that we've been building, DoorDash, it was critical to do that because in the first five, five and a half years of the company's life, we were very undercapitalized compared to any of our peers, maybe one one hundreds

Starting point is 00:30:03 of some of our peers. And that capital efficiency, I think, started, yes, because of the constrained budgets. It also started, though, because we figured out very early on because we partially had to, that we had to make the unit economics work. So I think unit economics and network health, you can actually tie. And it's understanding the relationship of how many units you would need before you could achieve maybe overall company profitability. That's an investment decision. You mentioned this interesting point about struggling to raise a seed round. I think it was my friend Daniel Gross who first asked the provocative question. Can you name an iconic huge company that did not have trouble raising a seed round? Or where the price of the seed round was in hindsight,

Starting point is 00:30:48 clearly wrong. I mean, obviously, I guess that's definitionally true. But why do you think that was? This seems to me, with the benefit of hindsight, enormous market, the biggest possible market, and endless places to go. What do you think was behind the difficulty raising financing in the first couple of legs of the business? And Dornis just had challenges along the way of raising capital. But I think usually what it is is there's a lack of information to make decisions on. I think that's kind of the high-level bit. As a result, you kind of have to have convictions on really hypotheses where there isn't a lot of data and you kind of have to make the bet before the data is there. And so when I think about what data was not there, maybe, as

Starting point is 00:31:30 investors were evaluating the possibility to invest in DoorDash, well, one, do people really want this? Or is this just a service for the wealthy or a certain segment of the population in places like New York City, for example? Second, can you even solve the logistics problem in any sustainable, profitable way because, again, when I told you when we started and spoke with some professors about this logistics problem from a technology perspective, I bet investors did similar homework and discover that this is a problem where it hasn't really been solved before. And then I think third, just how would the markets actually grow because there probably will be a few of these networks or several of these networks who's going to be able to compete in the

Starting point is 00:32:17 most effective way. I think those were all probably questions that investors had, but you're going to have to ask them. As we fast forward through to today, what's fascinating about DoorDash is the percentage of the problem that's been solved. So we think about this like, oh, great, you did it, successful public company, et cetera. My guess is you would argue that we're a relatively small percentage of the way into solving this bigger problem. How do you think about that? How far into this do you think we are, not just DoorDash, but just generally speaking, legibility and logistics? problem for physical stuff in the world. Is it still as early as it seems it might be?

Starting point is 00:32:52 It depends on how you define the problem, but I think no matter the problem definition, and I'll talk about, I think, nuances of the definition here, but the progress bar is very low. We're very, very, very early. I mean, even when you take something like just the very first core problem that we are solving at DoorDash of just bring all of the restaurants in your neighborhood to you, that industry is still single digit, maybe just. clearing 10% of overall industry restaurant sales, even with some of the tailwinds from the

Starting point is 00:33:24 pandemic. And you compare that to something like ticketing, which is now 40, 50% online or commerce. E-commerce is 20, 25% online. Bring all of the food to you is still in its earliest innings. And obviously, food is a massive category given how often we consume. when you start looking at the problem from bring all of local commerce online, that I'm not even sure we even show a blip on the progress bar right now. I mean, we still don't know information like, again, we're in a pandemic, but if you can think back or remember back a year ago pre-pendemic or look forward post-pendemic, we still don't know where the last parking space available is in a certain city. We don't know how fast people make food, how long it takes to make a salad versus baking. making a deep dish pizza? Where are the apples left in aisle six? These are problems that are really important to solve. I think one of the greatest business model transformations that is

Starting point is 00:34:23 happening. And frankly, one of the biggest business opportunities that's occurring right now is all of local commerce is coming online. I mean, look at what happened during the pandemic. Every brick and mortar store, if there's any silver lining, participated in e-commerce, and they actually took share for the first time in e-commerce. Because the collective of some was so massive. I think that should be reason for optimism why when you do digitize and allow all of local commerce to be cataloged and brought online, then many, many new business opportunities will emerge. What do you think are the most important differences between the local commerce story and the massive distribution center Amazon type commerce? What's important for us to know

Starting point is 00:35:12 about how those worlds differ, because obviously they're very different things and 20-minute delivery is possible in one. It's not in the other. How do you think about the important differences between those two? In an overly simplistic or reductionist view, it's a world of centralization versus decentralization. At the end of the day, the customers want the widest selection. They want the highest quality. They want the lowest prices. And that's going to be true in either world, whichever world. I think when you think about it, while in the centralization world, you can have ownership over the catalog. You can put as many things into it as you want or as few things you want into it. But you're right, because of the lack of proximity, it's farther away. Because maybe it's

Starting point is 00:35:55 part of an ecosystem already. It isn't as inviting to local merchants. Now, when you look at the decentralization play, you can bring things certainly quicker and cheaper because of the proximity to your point, but maybe you can't bring everything. you have other things you use a city for, not just storage or inventory for commerce and content. I think the two worlds are starting to meld where I think that every store on the street recognizes they're really selling you two families of products. They're selling you experiences that we all crave, especially now because we've been stuck at home for a year, and they're selling you convenience. And they're trying to figure out how to do that. Do I do that out of my current square footage?

Starting point is 00:36:37 Do I look for adjacent spurt footage? And I think that's something that is a very, very exciting evolution that will be coming. When it comes to something that is introduced to the business like the monthly, I think it's $10 dash pass, that consumers can buy that sort of unlocks. It's like an inner ring to the game. If you're a more frequent door dash user, I'm sure it makes sense, almost like Amazon Prime for sure be a member of this thing. How did something like that get conceptualized? And what have you learned about the way that something like that changes? user behavior versus just giving them something nice. That was a project that took almost a year

Starting point is 00:37:14 in testing the DashPass because with subscription programs, I think to your point, lots of things change. Consumer engagement may change. Your economics may change also because obviously consumers are paying for the benefits of usage and really it becomes more of a fixed cost of that consumer where they want to use it as often as possible to kind of recoup the fixed cost of membership. And so those kinds of activities, you have to be very careful as you're building a business where you have variable logistics costs, but only fixed revenues coming in from something like a membership program. So that took a lot of testing. But the idea really came from watching our consumers because consumers tell you a lot, not certainly

Starting point is 00:37:54 when you talk to them, of course, I do customer service every day. They say a lot. But they also tell you a lot based on what they do, what they search for, what they're buying, how they're buying, how often they're buying. and that teaches you a lot about perhaps how we can create new products that might delight them and serve them better. But really a product like DashPass was one that's a good example, actually, another good example of one that has very high magnitude of possible outcomes. How you think about rolling out a product like that in our opinion is quite important.

Starting point is 00:38:27 And what are the different inputs and levers to actually create a program that actually makes sense? And then how do you continuously deliver value from it thereafter? You mentioned this idea of learning from customers. This has become maybe like the most popular trope. Be a customer obsessed company. Talk to them, watch them, learn from them. And when you start reading about DoorDash, you quickly stumble on this important idea of servant leadership, which I definitely want to talk about in a bit more detail.

Starting point is 00:38:52 I think one of the components of servant leadership, you've already mentioned some of it. You do deliveries. You're talking to stakeholders in the ecosystem, not just once or twice, but a lot. And engineers are doing it, blah, blah, blah. Is there a diminishing return curve to that kind of discovery? What have you learned about that? I'm sure it's valuable to do a few times. Is it valuable to do 100 times?

Starting point is 00:39:13 Or do you stop learning after relatively few experiences on the front lines? One of the things I've learned is that customer expectations always go up. And just like convenience is one that almost moves only in one direction. It tends to go in the direction of greater convenience or, Gravity tends to go in the direction of landing on the ground. I think customer expectations always go up. I think it's one of these things where you're not blindly trying to build for the customer. That's not the point.

Starting point is 00:39:45 I think great products come from taking a point of view like DoorDash did seven and a half years ago, for example, of starting with the Dasher and the merchant product and then building our way towards the consumer. But you have to sanity check along the way. And the good news with customers, especially in a high frequency product like ours, you get that information very fast, especially if you want the negative signal. And as a result, we learn quite a bit. And it's not just learning to react necessarily to what new products we've shipped. It's also doing a bit of what you're doing, which is listening and learning about possible new things that maybe are still in exploration phase. So far, I don't know if we've been.

Starting point is 00:40:29 ever actually measured, I guess, the return on, I suppose, time spent in this case. But because I believe that expectations always go up, it's one of the things that's most important for us to continue to do. What is your broader philosophy on leadership? And how much has that changed across the seven and a half years? It's changed a lot, I'm sure. In the beginning, I'm not sure that there was necessarily a philosophy. In fact, we waited as a company, as a founding team, probably for two and a half years maybe before we wrote down a set of leadership principles that described our culture. And that's because I think culture, it's 80% who you are and 20% who you aspire to be. And I think the same can be said about leadership because it's very,

Starting point is 00:41:15 very hard, I think sometimes just to read maybe a book or listen to a talk about leadership and then try to map yourself to that perspective. If that's not who you are, you're almost always fighting against human nature in some sense. Instead, maybe an easier way to, I guess, find your own voice or your own way of leading might be observing the person in the mirror and finding out what is your strength that you do already and then build a leadership set of principles around it. For example, around our culture, we talked earlier about customer obsession. But we didn't come up with the word customer obsession. Instead, we wrote down stories of what had already happened in the first two years of DoorDash's life. And then we derived the customer

Starting point is 00:42:00 obsession principle, not competitor focused idea where, for example, among three of the company's life, we had a massive outage on September 28th, 2013. I still remember it because of the fact that we were laid on every order by at least 45 minutes. And I remember it took the founding team maybe 30 seconds to make a pretty high magnitude decision, which was to refund every single order, which was a double-digit percentage of our bank account. You've got to remember, we couldn't raise our seed rents. We were days away from cash out. And we also stayed up to bake cookies,

Starting point is 00:42:33 delivered them by 5 a.m. the next morning to all of those customers. Or I think of stories where there were a lot of deliveries in the early days that actually made me nervous because they were going to the hospital. And I thought maybe something horrendously had gone wrong. But instead, actually, they were going specifically to the maternity ward. as moms didn't necessarily want, I guess, hospital food over and again after delivery. They wanted to get their favorite meal. And when we found out about some of these moms, we literally drove alongside the dashers

Starting point is 00:43:02 with balloons, chocolates, and other stuff, animals, and brought them something special. Those are the things I thought about, and we rode down, and those are the things that the team remembers that authentically describes customer obsession. We didn't necessarily write down the words customer obsession, and then I guess try to fit stories against it. It was almost the other way around. And that's how I think of leadership. For example, I like being in the details with our teams in our product reviews and our business reviews. And so one of our principles is to operate at the lowest level of detail. But in many ways, they came from something that I naturally did. Now, I think one of the things that's important as a

Starting point is 00:43:38 company evolves, as it grows, is you have to check whether or not those things, those beliefs, principles that you authentically live up to every day actually matter to the company because companies evolve and they grow and you have to add things sometimes or subtract things sometimes because they may no longer fit that life stage of the company. For example, we added a principle in 2017 around making room at the table. And this was our commitment in 2017 as a three-year-old company to make sure early on that we would build both a management team as well as a company, as diverse as our customer base. That came with commitments to recruiting, to other dimensions of the company. So that's an example where we didn't have it from the beginning. There were no stories

Starting point is 00:44:26 that we could derive. Actually, it was the absence of stories, but it was something that we wanted to get better. It was part of that 20% that we wanted to add that was not in the building, that was not in the water, that we wanted to make in the water. I think that's how I think about leadership. It's evolving, but it starts with you. And I think is very strong. willingness to observe and know thyself, both the good things and the not so good things. Because I think that's how you can show up every day consistently. It's such a beautiful idea. It reminds me of Carlos Brito, who's the CEO of Anheuser-Busch, InBev, talks about how you give equity, actual equity, as a reward for ownership,

Starting point is 00:45:08 not to create ownership. Ownership is a thing that comes before equity. your actual strengths and behavior come before the principles, not the other way around. It sounds so obvious when you say it out loud, but I think almost everyone does it the other way. Like, what do we want our principles to be? Like, what sounds good? What was in the book we read most recently or something like this? And this seems to come from a position of strength in a much more clear and obvious way. That's quite wonderful. How do you do that at scale?

Starting point is 00:45:36 You or you, DoorDash is a lot of people. How do you create that incentive aligned culture of ownership as the company gets really big, just in a number of people working there? As a company starts, I guess evolving, if you will, from a product into an organization, obviously the CEO's job really becomes systems design. And when you think of systems design, you need objectives, you need constraints, you need mechanisms to kind of influence. One of the first things that's really important is you have to write things down.

Starting point is 00:46:08 It's a mechanism that is true, not just for how you describe your culture or your leadership principles, but also it's how we do things at DoorDash. Every meeting starts with a document. This has been true for the last five years. Written communication scales much, much better than just conversation that you and I are having. Second, you have to think about who are you bringing into the building? Because it's a lot easier, I found, to get it right on the way in, in terms of matching with that value set or those sets of leadership principles, than to try to somehow force it on someone because, again, you don't want to fight human nature.

Starting point is 00:46:42 You want to embrace human nature. And it's a lot easier to embrace these principles if you already are practicing them. So you look for them. And then the third is you want to find ways to reinforce them as well as to minimize the absence of the practice. But the reinforcement is really, really important. And there's lots of ways in which you can do that. What has been the most surprising thing aside from everything you just laid out? that you've learned about company building, just generally speaking, maybe relative to your early

Starting point is 00:47:10 expectations? Well, the initial thing that comes to my mind is just how it's never ending. It's very different from maybe success in other genres that I've participated in before. For example, sports. I grew up playing basketball as a way to learn in English. In basketball, there's a certain time clock. Game ends. There's a game over. There's a, Who scored more points during that duration? I think this is true in terms of the pedagogy in which so many of us were educated, where there's some definition of, quote-unquote, goodness. You get an A in a class.

Starting point is 00:47:51 You attend a certain school. You major in a certain field. Secure some internship or some job somewhere or some graduate degree. And there's this belief that something ends, that there is this commencement, and then there is the graduation. company building, I feel like it's almost very unnatural because you have to be very long-term oriented because ideally the best success is the company never ends. There is no definition of start-stop. I think that's probably the very first thing that it's taking me a while to realize

Starting point is 00:48:23 and also to therefore to work with everybody inside the building at DoorDash to appreciate the journey that we're on, not some start-stop final destination. kind of thing. I think the second adds to one of the comments we talked about earlier about playing your strengths that it's so much easier company building or appreciating the journey, if you will, if you can play to your superpower and learn other things along the way. That makes the journey a lot more fun. And when the journey is with other people, it makes it a lot more impactful and rewarding no matter the score or the outcome. And that chasing excellence, certainly beats chasing the scoreboard.

Starting point is 00:49:06 It's ironic because actually if you chase excellence, maybe the scoreboard will actually be something in your favor. But I don't think of that. I more think about how are you going to do 1% better today? How are we going to invent the next thing to delight our audiences? The final thing I would say is just I've learned quite a bit around company building around what are some of these attributes of excellence? What are the attributes of chasing excellence?

Starting point is 00:49:29 And how that's been true, no matter what position in the company you play, the best people tend to have the following attributes. One, they can go high, low, and they can really go to the lowest level of detail. Two, they have a very strong bias for action. They have that get going movement indoctrinated inside their bones. Three, they're great recruiters because they recognize that it takes a team to win. Four, they try to intentionally get one percent better every day. There's this humility that no matter what standard or benchmark they've set for themselves or cleared

Starting point is 00:50:07 that there's always something that we can do better. Five, they have great followership. That's actually my definition of leadership. It's not how many people report into you or how many people listen to you. It's how many people want to follow you. And in fact, we have many individual contributors at the company who have great followership and they're immense leaders in their own right. And then finally, they can hold two opposing ideas at the same time. Their ability to constantly want to disconfirm their own bias. I absolutely love that list. When you step back and think about the problem space that we spend a lot of time talking about, it has this other feature that I'd like to sort of close with, which is this idea of emergence. So in other especially network-based

Starting point is 00:50:51 technology businesses, where you often find are unexpected and unpredictable, interesting, positive outcomes that result from you reducing friction for merchants. I'd love to hear you riff on that little bit. You talked about dreaming big earlier. What is the big dream now? As you look forward for DoorDash's next decade, next seven years after the first seven and a half, how is that dream evolved and what sort of emergence do you think that your activities might create in the world? I guess a few points. The first thing I would say is we're still so early in just organizing this city. If you think about our goal of growing and empowering local economies, which produce the vast majority of GDP in this country and globally, we're so early.

Starting point is 00:51:37 Now, the network grows in its value and its creation of value as we move from category one to category two, as we start thinking about building out a platform for these businesses so that they own the customer relationships, that they have all of the same products we have from customer acquisition to customer service so that they can replicate the same business building activities that we do so that they can be successful. And when I think about that network and what that can become in the next X years, I think it'll create more and more business opportunities. I mean, there's no reason why people can't. In fact, some of this is happening, you know, start a restaurant from their own kitchens or to open a retail store from their living rooms.

Starting point is 00:52:23 We saw some of this during the pandemic. I think there is no stopping creativity. But the distribution of access, the distribution of knowledge, the distribution of capital, the distribution of some of these enabling functions, if you will, that is limiting, and that is right now a constraint. And I think that if we can provide that, I think the activity within, just right in front of you, the city that has been housing you and give sustenance to you and your family will continue to be very, very successful.

Starting point is 00:52:55 It's actually, I mean, if you looked at some of the statistics, the percentage contribution of GDP and job growth from the physical businesses on the streets have remained relatively the same in this country through a lot of turmoil in the last 80 years that it's been measured through ups and downs in the economy, obviously changes with technology adoption. But regardless of the decade, that percentage is still the majority for every new revolution that comes. That's what gives me optimism that the cities are very resilient. And it's a complicated set of things that make that true. Our job is to help these cities create the next and enable the next set of business model transformations and capabilities such that more creation can continue, such that these cities will continue being the biggest producers of jobs and GDP creation. Do you think that your presence in the world will change the nature of where people live?

Starting point is 00:53:49 Because hearing you talk about this, I mean, it basically sounds like you're creating a cohesive operating system for businesses where local movement of goods, if that describes your business or the one that you want to build, Dordash would be the place you go build on top of that. It is the platform on top of what you build in the same way that if you want to sell stuff online,

Starting point is 00:54:08 maybe you're a Shopify is the place where you go. That seems like it could really change dynamics of how people exist where they live and where they start businesses. Do you think that that's too much of a stretch or that will kind of stick to patterns of living that we've seen in the last 50 years? I've always believed that,

Starting point is 00:54:25 even though things take time, people everywhere are more similar than we are different. There's nothing special. You know, what I've learned in the last seven and a half years, I love New York City. I love being there and I can't wait to get back. There was nothing special in hindsight about the New Yorker who can get delivery. What was special was the access to the convenience. It's not like where I grew up in the Midwest that my friends and family there didn't want convenience or that they didn't eat three times a day or that they also had little kids and they

Starting point is 00:54:52 weren't able to cook every meal and things like that. And they were also just looking for time-saving solutions. They were. They just didn't have access to the same products and services that somebody maybe living in New York City did. And so absolutely, I think that's what fosters progress. And that's not just true about DoorDash and local commerce and the opportunity for local commerce. I mean, that's true for entrepreneurship. I mean, we're seeing this globally now that you don't have to be based in maybe the Bay Area or a particular part of the world to start a company. In fact, they're great companies being started now in many places around the world because of some of the democratization of knowledge, of talent, of capital, and of company building practices. And I think that should also be

Starting point is 00:55:35 true for local commerce. What has you most excited about the future, just period? The pandemic was another great exhibit of just showing the best of humanity. I know that there were bad times and moments that we saw, in fact, during this pandemic. But, We also saw some of the best things. We saw dashers, for example, create cards to make grandparents feel better because they no longer could see grandchildren by taking photos of some of their grandchildren and actually putting them on cards. I mean, who would think of these things?

Starting point is 00:56:11 And the point I'm trying to make is I'm very optimistic just about human progress. And this is not just about commerce. I mean, climate change is one of the greatest problems that we as a collective humanity, will have to solve. There's immense progress in a lot of areas. Now, I know we have to do it fast. There's immense progress. Look at some of what's happening with biology. My background was in math, studying mathematical biology, not just in identifying when diseases will actually come. So much in preventative health and just better understanding of the body as well as better understanding how to produce treatments. I mean, look at some of the speed in which some of the

Starting point is 00:56:50 vaccines have been created during this pandemic. I'm very, very optimistic about humanity. I love it. What an incredible place to turn to my closing question. I ask everyone the same thing. What is the kindest thing that anyone's ever done for you? It's a tough one. There's so many times in my life where there's such a cemetery, I suppose, where someone is literally unconditionally giving me something that may never see any payback. It brings me back to the story and the sacrifice that my parents made. When they came to this country, also that my grandmother made, I was raised by my grandmother for the first 12 years of my life.

Starting point is 00:57:25 I didn't really see my parents that often, mainly because they were just trying to create sustenance so that I can actually never have to differ my dreams. My dad worked 40 hours a week while getting his graduate school degree. My mom worked three jobs a day, as I mentioned, for 12 years. And very, very thankful to all of the sacrifices that they made. I'm a relatively speaking new parent these days. When I just think about keeping my kids alive, forget about like creating opportunities for them. I think about just the selfless nature that that entails.

Starting point is 00:57:59 And then when I add on some of the circumstances that my parents and grandma had to overcome and frankly, the dream that they had to defer, that's the kind of thing that someone has done for me. God, what an amazing answer. And it makes me think about when I had my kids going to my parents soon they're after and just being like, holy shit, thank you. I had no idea. 100%. I've just absolutely loved our conversation, Tony.

Starting point is 00:58:23 I'm so appreciative of the time and all the insight. Love the business that you have built in our building and all the just awesome lessons that you've shared with us. This episode was brought to you by Vanta. In this five-part mini-series, I sit down with Vanta CEO, Christina Cachopo, to hear about the origins of Vanta, how Vanta is automating security,

Starting point is 00:58:43 and when companies should look to partner with Vanta. In this week's episode, Christina and I discuss how Vanta approaches SOC2 compliance with a modern software mentality and what it's like to partner with Vanta. So talk through how you began to approach this problem as a software company yourself. So I love companies that go from some arcane point in time human-based process to something almost more streaming and more software-based. So just talk us through kind of the initial product and how it attacked this need for the market in a unique way. So the first thing we noticed was Most companies didn't actually, or the security practices across companies should actually be really similar. Even if someone's, I don't know, a developer tool or developer productivity and someone else building an email client, they should both be keeping customer data secure.

Starting point is 00:59:28 Both companies, employees should, for example, have two factor on their email accounts. So I think the first thing we did, looking at this as software people, is say, why is it so bespoke? We actually have a good understanding of security best practices. Let's just use those. second part was then just looking at, okay, an auditor is going to come in. I'm going to think of them as a smart and skeptical person, and I need to prove to them that I do everything I do. And so then it was just a game of how can we produce that data? And this was where the technical piece came in of I can pull a screenshot from AWS and tell them my databases are encrypted. That's what we used to do. I can also write a few lines of code and pull information from AWS every 10 minutes to see if the databases are encrypted. So just sat down, thought about what we would need to prove these practices were in place and then wrote a bunch of code against that. So let's say I'm a CTO, which is I'm assuming kind of the point of interaction between Vanta and another software firm. What does it feel like for the CTO to engage with you

Starting point is 01:00:27 for the first time? And how does the timeline look different? So what are the steps to getting up and running with Vanta? And if one of my goals, we're going to talk beyond SOC2 in a second, but let's say my initial goal is SOC2 compliance. What kind of timeframe and workload am I talking about? We make setup really easy on purpose. We sort of know that we're working with startup CTOs that have approximately a million other things to do. So getting set up is just getting a handful of API connections so we can get the data we're looking for. And then once we have that data, we could make what we call a gap assessment, just a list of all the things you need to do and a dashboard that you or someone on your team could work off of. Then it's just a game of finish off all the tasks.

Starting point is 01:01:06 get your dashboard green, and then you're ready for your audit period. So it takes differing amounts of time, depending on how the company wants to prioritize it, but we've had founders do it in a weekend, literally. It probably wasn't their most fun weekend, but definitely possible. Better than a year and a half. Exactly. Once this initial on-ramp is complete, and let's say they're even through their first audit, which is made simpler by Vantta, what does the ongoing relationship look like with a customer

Starting point is 01:01:32 and talk about the difference between a point-time audit and sort of an ongoing, integration with Vanta and why that's helpful? It's a two-fold answer here. So one, these auditors come from the accounting background, so they understand recurring revenue. And so these audits are annual events. And so you need to redo them once a year. Regardless, this isn't just the software people came and tried to put a subscription

Starting point is 01:01:52 model on top. This is kind of a subscription model much before. But the other piece is Vanta is continuously monitoring your startup security in the background. And we think that's both important in general. It helps you as a founder know you're in good shape. if you're not doing anything, that would make you embarrassed later. And then when we think about just what we're,

Starting point is 01:02:09 Vanta's trying to do in the world, we really want to move everyone to this sense of continuous monitoring and continuously verifying a company's security, not just relying on an audit every March, but really having this holistic continuous picture. So there's almost like a, let's say, this official angle. That's the SOC2 stamp of approval, which often buyers require a view to work with you and you need that.

Starting point is 01:02:32 But there's also this, it's almost like an insurance product, that the most damaging thing would be if something really bad went wrong and the odds of some security problem going wrong are reduced with this continuous monitoring. Is that sort of a fair summary of the twin benefits? Yeah, it is. And we talk about the security pieces, sort of just making sure you've locked all the doors and windows of your house. The idea is that it's this baseline, again, you're not being a dofif, you're doing the reasonable things. No one's going to walk through the front door and, you know, take your TV. There's certainly other security products in the market that maybe are more intense, but much more narrow. And so the Vanta idea is actually security is just you're only as

Starting point is 01:03:10 good as your weakest link. And so let's just kind of raise everything up a bit until you have that confidence. Maybe just give us an overview. What are the major pieces of a security pie? If I'm thinking about what security means for a software business, you've mentioned a couple terms here and there. What are the major doors and windows, I guess is what I'm asking, that need to be locked down and closed. So there's a lot. So for a software company, key piece is in fact your cloud and infrastructure. Really broadly, did you set up AWS or whatever you think? Did you set it up reasonably? And setting it up reasonably breaks down into about 50 things, but did you do that? You have the employees at your company and the accounts they have access to. So what tools and why and what permissions

Starting point is 01:03:50 and hey, does everyone need access to all of the customer data historically, you know, probably not, especially as you grow. Employee laptops end up being important because, again, they have saved passwords. They're just the key, literally and figuratively, to so much customer data. Those are kind of the big ones we think about. If you enjoy this episode, check out join colossus.com. There you'll find every episode of this podcast complete with transcripts, show notes, and resources to keep learning. You can also sign up for our newsletter, Colossus Weekly, where we condense episodes to the big ideas, quotations, and more, as well as share the best content we find on the internet every week.

Invest Like the Best with Patrick O'Shaughnessy - Tony Xu - A Human and Math Problem - [Founder’s Field Guide, EP. 28]

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