 Live from the Congress Center in London, England, it's The Cube at MIT and the Digital Economy, the second machine age. Brought to you by headline sponsor MIT. Welcome back to London, everybody. This is The Cube. I'm Dave Vellante with Stu Miniman. Marshall Van Alstien is here as a visiting professor at MIT Sloan School of Management and is speaking today at IDE on network effects and platforms. Marshall, welcome to The Cube. Thanks for coming on. So set up your talk today. What are you going to talk about today to the audience? Well, there are a couple of things we're going to try to visit. One of them is going to be the changing nature of business models in the economy and what's happening in the changing structure of industry. One claim that we'll make is that platform business models beat product business models almost every time, but it's the product business models that we've been teaching about and learning about and studying about so far. Another thing that we're going to try to visit is why things are changing in the economy. What are the causes of that? And then the third thing will be, well, what are some of the implications that we can go into with the changes in the economy and why the business model for change? So let's start with platform. People want to know, okay, what do you mean by platform? What's the difference between a platform and a product? Well, great question. So you might think of a product as defined by its feature set and what that product does. We like to think of products being defined by features but platforms being defined by communities. What's the ecosystem built around that? Is there a developer ecosystem around that? Are there contributors? Are there user-generated content around that? The platform brings in third-party value add and third-party perspective that takes place outside the walls of the firm, that distinguishes what you might make internally versus what you might be found and contributed by the context and the ecosystem or the environment. So a product might have an API but a platform must have an API. Is that a fair? It absolutely has to. Matter of fact, you've hit on a wonderful area. Matter of fact, one of the things we've been looking at talking about in this talk but is that APIs are almost becoming the new form of intellectual property. You have this as a way to grant access to new forms of value within the ecosystem and have others to contribute to that value. APIs is a fantastic way of bringing in the external members of the community. So talk about your research in this area and share some of the findings. So one of the things that we talk about is the rise of network effects. How it is that communities can add that value or how it is that a product becomes more and more valuable as other people use it. Network effects can fundamentally change the nature of the business model. Anticipate the results. One of the things we're going to claim is that you focus, your attention moves from the shifting inside the organization to outside the organization as you bring in third party value. Network effects changes things like the pricing, for example. Can we explain the economics of free? How do you monetize an old good that is priced at free? With network effects, we can actually develop new metrics and measures of the ecosystem contributions of the third parties to do that. Another element of that is the growth that you might experience outside the organization. What is it that others contribute that cause adoption and viral spreading of that particular product? Another is the change in the corporate strategy that takes place, the old boundaries of the firm shift over time. I'll give you a perfect example. They teach four to five forces in business schools. Where you've got competition, you've got buyers, you've got suppliers. Today, you could ride on Uber today and then drive for Uber tomorrow. You can rent with Airbnb today and host with them tomorrow. These boundaries are completely blurred. The markets are completely spread out across different ecosystems. We need to figure out how to manage those different boundaries. So how do you quantify that network effect? Is it the residual creation of value? Is it revenue that's created as a result of that? Is it more intangible? How do you actually quantify that? So what we look at, there are a couple of different, there are two things at least that we want to look at in the measurement of the network effects. One, what's the core value created and given interaction? So if you're engaging on YouTube, what's the value you get from YouTube videos or the value of a particular ride? Then you want to look at the spillover value that's created for others. So in a YouTube video, what additional recommendations can we make to stew from a video that you might watch? Or what additional patterns from a Google search you might be able to give me from your particular behavior? This creates data feedback loops that make the product more valuable over time so you can make better and better recommendations or better and better product management over time. It's the measurement of that spillover and feedback loop that actually helps account for what the true metric should be. So I think about ways. And ways obviously gets more valuable as there are more waysers in my network. So does that mean that more people will use ways get value out of ways? I'm still unclear on how we actually translate that into money. Wonderful question. Okay, let's back up and take a look at what happened over the evolution of some of these mapping economies. If you look at Navtech was purchased for how many millions of dollars to actually it, it was a horrible acquisition. It was a great example of keeping the value locked up inside. Ways brilliantly crowdsourced that. Not only did you get the street navigation, but you get real time data. So if there's a traffic accident or if there's a policeman stopping traffic and doing a radar detection, that data is picked up immediately in ways and then propagated not from that one individual but to the ecosystem as a whole. There's that spillover value that causes ways to be much more valuable. Ways zoomed past the value of Navtech so it was acquired for a large sum of money and you get the complementarity between the existing mapping system and the value of the data contributed by the ecosystem partners. Fantastic example. So valuation obviously is a key metric that you track. You were talking about Uber before and the difference between how the VCs valued Uber versus was it academics or? Versus the traditional mechanisms. Yeah, yeah, okay. So one of the things I argue that happens is that almost every single one of the things that we teach in business schools changes when you get network effects into the picture. So whether it's marketing and pricing, whether it's logistics and supply chains or finance. We've got examples in each of these. Finance is a fantastic example. Only June of last year, there was a fantastic debate in finance between a famous finance professor at New York University who had actually won prizes for whose research had long-term influence and had written textbooks in finance on what was the value of Uber and he raised a very simple, wonderful question. Why on earth are venture capitalists putting $1.2 billion into a company that only had a few hundred million in revenue? How could you possibly justify that? Well, he used the classic tools of finance. He estimated the total size of the market. He then did a discounted series of cash flows and then estimated the proprietary barriers to entry, the patents that you might have. Who else could enter that? And he came up with what was a very plausible estimate for Uber of $5.9 billion. But he did one thing that was very graceful. He said, look, these venture capitalists are crazy, but at least hear my numbers, here's my spreadsheet. Anyone who disagrees with me, you're welcome to go run your own numbers. Bill Gurley, one of the investors in Uber took up that challenge, brilliant analysis. So he took it and then he used network effects to show it and he used this fantastic diagram from the CEO of Yammer, this former CEO, I believe, of PayPal. And he showed more riders attract more drivers, more drivers attract more riders and you get this feedback effect and you get arbitrary scale. Uber of now, of course, being the largest taxi company in the world, although it owns no taxis, and you've got network effects going. He said, once you do that, you're not just thinking of pricing the existing market, you're changing the market. In this case, you're not just looking at taxis, you're also looking at then encroaching on the rental car market. You're looking at encroaching on the second car market. You're encroaching on the logistics market. You've changed the whole market size. And he said, oh, by the way, the data on San Francisco alone show that the taxi market is three times the size, so if you take 5.9 and our estimate 17 billion, you're already there. Guess what? By today, Uber's already worth 40 billion, so once you've accounted for the network effects, you get a huge difference. The argument again is network effects change all kinds of different things that we traditionally learn in businesses, operations, finance, pricing, marketing, all of these things invert when we add the network effects. So we spend a lot of time in enterprise tech and one of the things I look at is the open source markets and companies are not only using open source, but they're now contributing it to open source. And I think the network effect could probably be played there because it's always, you know, if I work for, you know, big public company, how can I justify rather than my guy sitting working on my application, he's contributing code which might eventually come back and help me. You know, look at that piece of it, you know, how do we justify, you know, being a participant in that whole digital economy? So I think that is a perfect example of open innovation where you can actually capture it in the right way. Although I've suddenly repositioned that. So I actually think you need some of the open source contributions on a broader scale. You imagine one of the ways that Android passed Apple iOS in terms of market share was to be more open. There were multiple Android stores, there are now larger numbers of developers. I think Android now has something like 80% market share relative to Apple iOS which has subsequently less. But don't go too far. If you go too open, you can lose control of the ecosystem. As an example, Linux is a difficult one because I think with properties of that specific license, you can't actually charge what you're doing because the customers also gain the rights to it. You need a proprietary complement, not just services, but a proprietary complement that might also scale. Also, if you go too open, you can lose control. Android is now competing with an open source version of itself, right? So, there's an interesting balance. I think in China, for example, the open source version of Android is now doing as well as the Google-controlled version of Android. So, I think openness is a very wonderful way to grow the ecosystem and capture third-party value, but you always need a proprietary complement that you can still control and manage in IP in order that you still have a business model. It's a very interesting and delicate balancing act. So, products have cycles, cycles come and go, platforms, as you point out, have this ecosystem, and I'm struck by in reading the second machine age, and I'm sure we're going to hear some about this today, this winner-take-all economy, but you just gave an excellent example of iOS and Android where it's two winners take most. Maybe the third guy gets wonderful crumbs. Can you help us squint through that sort of dynamic of, is it a winner-take-all economy? Is it a zero-sum game? That's a great question. I would argue that in general, we probably are facing new examples of winner-take-all effects. Let me see if I can highlight a couple examples that both historically and currently. The reasons you get winner-take-all markets tend to be things like, for example, supply-side economies of scale. In an earlier era, the industrial giants might have been Carnegie Steel, huge supply-side economies of scale. In electricity, there were two main firms, it was Westinghouse and Edison. Again, huge economies of scale. In auto manufacture, it was Alfred Sloan and Henry Ford. Again, huge production economies of scale. Economists have another name for network effect, which is a demand economy of scale. It's actually value that grows as more people use it. I'm arguing, one of the points of the talk is that we are seeing a new era of giant monopolies. And in this case, it's on the opposite side of the equation. It's on the demand-side economy of scale as opposed to the supply-side economy of scale. Take a look, for example, at the dominant firms today. There was a wonderful quote that went around on the internet, I think, a couple of weeks ago. The largest media company in the world is Facebook, and it produces no content. The largest retail in the world is Alibaba, and it doesn't own any inventory. The largest taxi company is Uber, and they don't own a taxi. The largest hotel company in the world is Airbnb, and they don't own any real estate. Well, how is that? It's all on that outside demand economy of scale. It's all that production that's being done outside the firm. In each of these cases, I think what's happening is a replay of the industrial giant monopolies, but on the other side of the equation. It's on the demand-side economy of scale, the network effect, as opposed to the supply-side economy of scale, the low-cost production. Whereas the car makers made all the money in the old days, car dealers did okay, but the car makers were really where it was all at. Now you're saying that in the demand-side, it seems that their organization's riding on top of this digital fabric, they're enabling this network effect to occur. They don't have to own all the components, whether it's the cloud or the security layer or whatever. I mean, there's money to be made there, but the new business models are leveraging that digital fabric in new ways. They're leveraging it in fabulous ways. It used to be considered inflation technology. It used to be the case that IT would manage the back office. That gave us the ERP systems. Then they started managing the front office, and that gave us the CRM systems. Argued that inflation technology in these networks are now managing what I call out-of-office. So it's the stuff that's not even yours. Matter of fact, in business schools, we teach just-in-time inventory management. I think with Airbnb and Facebook and Uber, it's not even mine inventory management. It's just somebody else's resource. It's a way of having the ecosystem add that value as opposed to the firm itself having to create that value. You can do both, but I think that network effect is where a lot of the leverage happens. So Marshall, last question I have is, how is teaching changing to accommodate the research that you've done and others? So I know you had some conversation with Dean Schmitlein and others in MIT. It's interesting. It's also ties into your win-or-take-all effects. It's really interesting. I think the nature of education will be changing dramatically over the next 10, even maybe five years. In the United States, there are 3,000 colleges and universities. Each of them has, in some sense, a geographic specialization. As courses move online, we're going to observe much the same phenomenon that's happened with newspapers. It's an information good. It can now be delivered across great distances. It's very difficult to justify 3,000 different versions of Econ 101 or Computer Science 101. On Coursera, for example, or edX, you might be able to find one of the world's best courses on Python programming. And I saw, there's a faculty member, I think it was at UT Austin, that had a 4.8 rating out of five. That's extraordinary. But now, anyone can gain access to that, not just people at MIT. You can spread that information wealth, that reach all across the ecosystem. Education is about to be platform transformed, like many of the other industries. One of the arguments is that the hierarchy of industries to be transformed is the greater the proportion of value that is created by information or community, the sooner it will transform. And I think education is a great example of that, where ecosystem partners may come from faculty members or students, or indeed, I think there are people in a location such as Skillshare, that are creating, based on their own expertise, novel but highly valuable classes that anyone can take. In some sense, that democratization is making it possible for anyone to take, but also anyone to generate some of the best content and then place it on one of these educational platforms. Well, Marshall, thanks very much for coming on theCUBE. I know you've got to go, and the program is starting next door. So thanks again. Good luck today. Thank you very much for your help. I appreciate it. I'll keep you right there. We'll be back with our next guest in the live stream from MIT IDE. This is theCUBE, right back.