This week’s podcast is more about Snowflake, the “data ecosystem” company. And how multiple companies are competing to create the standards and architecture for cloud services.

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Welcome, welcome everybody. My name is Jeff Towson and this is Asia Tech Strategy. And the topic for today, Snowflake Tuya and the fight for dominant design in cloud. That’s a bit of a wordy not awesome title, but a couple ideas in there. First is I wanna talk about Snowflake, which is sort of positioning itself, aspiring to be the data ecosystem for cloud services. Another company called Tuya, which is sort of positioning as the IoT ecosystem, again, also for cloud. And there’s this idea of this emerging, let’s say paradigm, ecosystem standard operating system for how things are done on the cloud. And it’s kind of a lot of chaos right now. So I want to sort of… talk about how that has happened in the past and how what we would call a dominant design has ended up emerging. Early 80s, Microsoft, Wintel, that ended up being the dominant design. Android’s open handset Alliance ended up being the dominant design in the 10, 15 years ago. Well, we’re gonna see one for cloud, which is much more of a B2B story. But yeah, that’s kind of the question I want to sort of lay out some thinking for how to take that apart. I’m struggling with this question. I’m looking at a lot of these companies and that’s kind of what I’m working on. OK, so that’ll be the topic for today. This will be a follow up. Last week’s podcast, podcast 105 was basically about Snowflake. So I went through some of the basics there. I haven’t covered Tuya yet. I will talk a little bit about them. For those of you who are subscribers, there’s some emails coming on Tuya. in the near future that’s kind of the next one I’m looking at. Yeah, and I think that’ll be it. Let’s see also subscribers I sent you an email last night about Ozone, which is was a little bit of a divergent into divergence into Russian e-commerce because it’s just kind of was an interesting company to look at it wasn’t too complicated it’s really easy to take apart that one, but definitely outside of Asia on that one. Anyways, that was kind of what’s on the plate for the next couple of days. For those of you who aren’t subscribers, you can go to jeffthousand.com, sign up there for free 30 day trials, see what you think, try it out. Last bit, standard disclaimer, nothing in this podcast or in my writing or on the website is investment advice. The numbers and information for me and any guess may be incorrect. The views and opinions expressed may no longer be relevant or accurate. Overall investing is risky. This is not investment advice. Do your own research. I guess one other thing to mention, my new book which is called Motes and Marathons, part one, it’s going to be kind of a long thing. There’s going to be four or five parts. Part one is available on Amazon starting December 1st. You can go over to Amazon right now. It’s up there. Now it can be pre-ordered and I’ll put a link in the show notes below. But yeah, that’s Basically all done, it’s just being formatted. Only, what was that? Only four months worth of work and six years of research. So it’s been kind of a long haul. Anyways, that’s going up. Okay, with that, let’s get into the content. Now, as always, there’s a couple sort of concepts, i.e. lessons for today. The two I wanted to talk about, I’m actually gonna repeat a little bit. I did a similar talk on. what we’ll call dominant design, I don’t know, 50 podcasts ago, something like that. I’m gonna repeat a little bit of that, but the two concepts are under this idea of the fight for dominant design, the fight to create a sort of standard approach in a new industry. It’s usually associated with a new technology. So let’s say, for example, when the automobile was first built, it wasn’t clear what an automobile was gonna be. You could have had four tires, you could have had three tires, you could have had six tires, you could have had the engine in the back, you could have had, you know, there was a lot of design sort of ideas, but, you know, Henry Ford pretty much established the design. Engine up front, four tires, you know, steering wheel, clutch, things like that. And once you get sort of through that phase of competing with different standards and overall designs. The competition and particularly the innovation shifts to another phase where then everyone starts innovating and competing to make the best components within an overall design, as opposed to fighting for another design. Nobody’s making cars with the engines in the back. Right, so we’ve seen the same thing every time we see a major technological advancement like personal computers, smartphones, and cloud, also airplanes and a lot of other things. So that’s kind of idea number one is innovation and dominant design. The other idea is innovation and how you get, you know, increasing returns to technology, which is unlike most things that become standard and used in this world, the more people that use a certain technology, usually the better and more valuable it becomes. When everyone agrees that we’re gonna use one type of, you know, alternating current electricity as opposed to direct current, there’s a lot of value to increasing adoption of technology. And that happens in, you know, definitely in the digital world. So that both of those, I think, are big questions within this whole sort of cloud paradigm that is emerging. So those are the two ideas for today. They’re both under the title of innovation, one for dominant design. One is increasing returns to technology scale or technology adoption, depending how you want. Now Snowflake is sort of, I think a really compelling company, which I’ve gone into in pretty good detail for a couple reasons. Number one is just sort of look, it has a really directly usable use case that companies seem to really like, which is put all your data on our Enterprise web as a service, data warehouse as a service, data storage as a service system, depending how you want to define it. And you can start to consolidate your data, get a lot of visibility, a lot of transparency, create a quote unquote single version of the truth for your company. That’s very, very useful. Almost immediately, you can start to do analysis, you can start to share with partners and other things. So there’s a really directly compelling use case that’s gonna get adoption. And that seems to be what’s happening. Okay, second to that. They are also clearly positioning themselves to sort of create a data ecosystem, a grander standard. You could almost say a dominant design for how data is gonna be treated in the cloud. The more people that sign up for their core use case and start to put their data in their system, they’re gonna adopt certain standards for how it’s tagged, how it’s categorized, how it is shared, what are the protocols, what’s the governance, what’s the security. So as that use case gets adoption, they are well positioned to sort of become this greater ecosystem. So they’re kind of talking out of both sides of their mouth. And that’s usually how this happens. I mean, it’s, you know, you could say the smartphone, the Apple system is definitely a dominant design, right? The entire operating system, really it’s much deeper. Their operating system goes all the way down to the chip level. you know, to iOS, to the App Store, it’s the full thing. Well, before they could create that entire design, they had to get a lot of adoption, which was the first iPhone which everyone loved. So, you know, they kind of did the same thing. So we can definitely see snowflakes sort of positioning themselves that way. And they always talk about a certain degree of proprietary versus openness, and they’re pretty much saying everyone can use our system. It works on AWS, it works on Azure, it works on Google, cloud and all of that. Now another company which I haven’t talked about, which I’ll send out an email in the next day or two about this, which is Tuya. They’re basically going out to brands and OEMs, let’s say like Schneider Electric, which is one of their clients, Philips. And they’re saying, look, you make razors, you make air conditioners, things like this, but those products. are becoming more and more software enabled. And those products are becoming sort of IoT devices, smart devices that all connect to each other, smart home, smart office, smart car. And we are basically selling software as a service that allows you to take your current products, could be a Phillips toothbrush, could be an air conditioner, and very quickly turn those into software enabled smart devices. And we will give you that part of the picture because most of these companies have no ability to do that. Now, in the same way as they get adoption, by these major brands and companies, and they have thousands of these companies that are doing this, well, they start to somewhat become a standard and an ecosystem, not for data, but for IoT devices that all connect and share with each other. So this is more like an IoT ecosystem play. as opposed to Snowflake, which is more of a data ecosystem play. And in both of those scenarios, they’re starting with the client, the corporation that’s running their operations on this data system, or these OEMs that are turning their products into smart devices. In both cases, they’re selling to clients, but immediately then they turn around to the application developers and they say, look at all these clients that are using our system, you should start writing your apps to work on our system. So there’s a sort of a fight for the operating system as well. And then of course we have AWS, we have Google Play, we have Azure, Microsoft, that’s out of the West, mostly out of the US, but we look out of Asia and then we start seeing similar companies coming out of China. Huawei, Tencent, Alibaba, maybe Baidu. So everyone’s kind of fighting, right? And everyone’s sort of. going for this new space, but there’s lots of different standards, lots of different proprietary ecosystems versus, it’s basically chaos as far as I can tell. I’ve been trying to take it apart, I can’t do it. And I think it’s just because it’s chaos. So that’s not uncommon. So I went back and I started to read Professor Melissa Schilling, who is a professor at NYU, Stern School of Business. She writes a very well known fairly big textbook on technology management. How do you manage big technology firms? It’s very sort of academic and wonky, but it’s good. I mean, it’s a pretty good read to get through it. I mean, it’s a serious textbook, but she’s been looking at tech companies for 30 years and just sort of talking about how they run them and what has been successful and what hasn’t. And she talks about this issue. So, Let me sort of tee up two cases and then I’ll talk about how she breaks it apart. But we can go back and look at B to C scenarios like the adoption of personal computers and we can look at the adoption of smartphones as at least two examples where we saw a similar level of chaos with lots of standards and lots of players and everyone was fighting. And then eventually in both cases, a dominant design emerged. And… these industries, these new technology paradigms, collapse to one or two players. And that’s kind of what the goal of looking at a company like Snowflake is. I’m trying to figure out if they’re gonna win the whole standard fight, is the market gonna collapse to them? And this is gonna be the next Microsoft Windows. Is this gonna be the next Android? That’s what I’m looking for, because I know the system’s gonna collapse to a couple players. They might be proprietary, they might be open source, who knows, they might be an alliance. But that’s kind of why I like this chaos of the cloud because there’s every reason to think it’s gonna collapse to one or two players. I just not sure who it is yet, but I’m hunting. Okay, so let’s say we go back to sort of the PC era. And I just pulled this from like Wikipedia. But when they look at sort of the emergence of personal computers, this is what they say, this is quote, By the early 1980s, the chaos and incompatibility that was rife in the early microcomputer market had given way to a smaller number of de facto industry standards, including, I’ll just read these, the S100 bus, CPM slash M, the Apple II, Microsoft Basic, and the 5 1⁄2, 5 1⁄4 inch floppy drive. Continuing, I’m just literally reading Wikipedia, which is not a great source, but it’s okay. No single firm controlled the industry and fierce competition ensured that innovation in both hardware and software was the rule rather than the exceptions. Microsoft Windows and Intel processors gained ascendance and their ongoing alliance gave them market dominance. Okay, I mean, that kind of sounds like the cloud world today. Chaos. and incompatibility is rife. We see lots of companies trying to be the de facto industry standard. And it’s not just the software, it’s the linking in with the hardware, it’s the usage by various partners, customers, developers, software developers, resellers, system integrators, hardware partners, I mean, it’s just all over the place. and everyone’s paying close attention to adoption, right? Whoever gets the most adoption, we should see a domino effect where all the other players start to switch to that standard. And that’s pretty much what happened with personal computers. Eventually, Microsoft Windows, the Intel processors became the standard and everyone making laptops gave up on the idea of, I’m gonna have my own operating system. They all said, well, I’m just gonna make laptops that are compatible or desktops that are compatible with Wintel. And all the peripherals, all the printers, all the mouses, all the cameras, everything that plugged in, they all just gave, we’re gonna all make it compatible to Wintel. Everything sort of collapsed to that industry standard. Eventually… And young Bill Gates became absolutely ridiculously wealthy at a very young age. Everyone thinks Mark Zuckerberg was like the youngest billionaire. It’s not technically true. It was like Bill Gates was unbelievably wealthy in like his early twenties. And after that, that’s kind of been the personal computer era. Um, we can fast forward 2007, 2008. We look at sort of the beginning of the smartphone era, but really we’re talking about smart devices. about really smartphones was the beginner. The iPhone kind of opens up the space. Again, it was a B2C play, which is different than cloud. But some of the biggest buyers of iPhones were company employees. And companies, it sort of became a B2B standard as well, because so many employees liked their iPhones. But we saw them come out. It was a bit of a simpler scenario. You had the handheld device, you had the basic chips. ARM out of London became sort of the standard for the script libraries and things like that. Qualcomm became more of the chip standard. But really what ended up happening was it was Apple out front, everyone else got panicked. They all sort of went under what was launched as the Open Handset Alliance, which was led by Google. And basically a consortium of 84 firms came together to basically develop open standards for mobile devices. Open Handset Alliance was established on November 5th, 2007, led by Google. Originally was 34 members. I’ll read just some of them. It’s actually pretty interesting to see who was involved. The founding members. We had network operators. So T-Mobile, China Mobile, Telecom Italia, Telefonica, which is Spain, NTT, Docomo, KDDI. So you had a handful of network operators. We had a bunch of software developers, eBay, Google, Nuance Communications, which is still around doing quite well. Well, interesting to keep an eye on that company. Packet Video, Skypop, I don’t know some of these. We see component manufacturers, Broadcom, Intel. Nvidia, Qualcomm, Texix Intramints, and then device manufacturers, LG, Sony, Motorola, Samsung, HTC, pretty much all the handset makers that weren’t Apple. And that’s kind of the founding members, the first wave, but very quickly after December 2008, 2009, 2010, lots of other companies eventually joined in in all of those categories, and hence you get… the Open Handset Alliance and you know that that fight went on for four to five years basically between OHA and Apple and then it was pretty much over. Now we basically have two standards really we have one standard. It’s pretty much a global monopoly. Every single smartphone on the planet if it’s not an Apple phone it runs on Android which is the Open Handset Alliance. So same thing, now in this case, it didn’t necessarily make any 21-year-old a billionaire because it’s mostly open source. Now Nokia and some other companies tried to be the proprietary standard. They tried to be the windows. And they couldn’t get the other parties to go along. It’s kind of like nobody trusted each other that much. And the rules weren’t right. I mean, launching an ecosystem, it’s a whole level of strategy of how you launch an ecosystem. and how you get all the parties to put their own self-interest second and put the interest of the ecosystem first in the sense that they will then do better. It’s hard to get everyone to agree to that. No one could pull it off, but Google did. And it had a lot to do with the fact that they didn’t make handsets. And that was part of it. So anyways, there’s at least two stories of how that sort of emerged. And then the question is, okay, We are gonna see some sort of standard, some sort of ecosystem emerge in the cloud. The difficulty is the cloud is just a lot more complicated. I mean, it’s a much bigger phenomenon than handsets or personal computers. I mean, it’s everything. It’s how all companies are run, infrastructure, cities. I mean, to a large degree, this is like, you know. the infrastructure of the next 100 years is being put together right now. So it’s not nearly as simple as, hey, let’s all agree on what’s gonna be on a handset. But it’s basically the same question, it’s just a lot bigger. Okay, so let me give you some of the frameworks for Professor Schilling, which I think are helpful. I think about these on a regular basis. She talks a lot about innovation, which is, you know, not innovation generally, which can be anything. It can be science, it can be whatever. It can be new candy bars if you want. But technology innovation, which is its own world, in large degree because unlike making, I don’t know, candy bars or whatever, you wanna shoes, whatever, technology all has to connect and work together. Everything depends on everything else. All the software depends on the coding language that you use. It depends on what people are trained on. It depends on the language being used. It depends on the chip architecture. I mean, it depends on the hardware, to the IP, to the software, everything links together. Very few things connect to that degree. So there have to be sort of agreed standards at every level of the tech stack. So this is kind of her area. So she says, okay, we can look at a lot of types of innovation, there’s product innovation. You know, fine. There’s process innovation, which people tend to undervalue. You know, how you do new processes within manufacturing is actually very, very important. One of my favorite examples is, I’ve mentioned this before, is how do you make ballpoint pens? Like ballpoint pens are not exciting. They’re actually really, really hard to make. You know, how you get that little ball. at the tip of the pen to sort of move and you know you can write smoothly and the ink goes around it. There was a big announcement in China a couple years ago that Chinese companies had finally cracked how do you make a ballpoint pen and they had been trying for decades. It’s surprisingly difficult as a process innovation. You can talk about business model innovation which is a lot of what Steve Jobs really did. He didn’t invent too many new things. I mean, he didn’t invent anything, but his teams, they didn’t invent too many new things. They just found things that were around and they put them in together in different configurations. You know, they didn’t invent the laser printer. They didn’t invent, well, they kind of invented the mouse. They improved it. I mean, they kind of hunted around and then packaged things together and brought them to consumers in compelling ways. But he didn’t have. bench research in many things. He was kind of a business model or a customer focused innovator. Competency enhancing versus competency destroying innovation. You know, when the calculator came out, that you could say was a competency enhancing innovation in terms of doing calculation, but it also devastated the slide rule business. Intel chips, you could argue, are more focused on getting better and better as opposed to disrupting and destroying something else. But the last component of innovation, I just gave you how many? One, two, three, four, four to five types of innovation. But the one we’re really talking about here is what she describes as architectural innovation versus component or modular innovation. That’s really what we’re talking about. chaos of innovation to create the architecture of this new technology which we’re calling cloud, the dominant design fight. Once that is done and there’s an established design, hey, we’re all using snowflake data standards and connectivity and compatibility. Once that is done, then you will see a shift to component level innovation. which is the Model T Ford innovation. Once we know what a car is, then we all, we have one group of companies that all tries to make the best brakes. And we have another company that makes the best tires. But we know how they fit within the design. So then it’ll shift to this, some people call it modular innovation. I think component is a little better. But component level innovation doesn’t change the overall architecture. We’re not there yet in cloud. We are there in PCs, we are there in smartphones. You know, there are specialty firms that make only the cameras for your smartphone. There’s a really good company in Taiwan that actually makes crazy gross margins on just making the smartphone cameras. I forget the name off the top of my head. I’m gonna look at that company again. Corning makes the glass, things like that. Okay, so that’s kind of her framework. I think that’s fairly useful. And I think when we break it into five parts, that’s mostly what we’re looking at in cloud today is this idea of architectural innovation versus component level innovation. The fight for the dominant design. Okay, so then you sort of ask, well, how do you tell who’s gonna win? Who’s gonna pull this off either as a proprietary, we own this ecosystem like Bill Gates and Windows, or is it gonna be open standard? Yes. Android controls the ecosystem, but they don’t really profit from it. I mean, they have one part of it’s open, one part of it’s licensed. Okay, well, you have to look at adoption and the diffusion of a technology into an industry. And that’s when people start talking about S-curves. People use the word S-curve all the time, the phrase S-curve all the time, but there’s actually a couple different types. Like one is… is a lot of venture capitalists and entrepreneurs, they’ll talk about a new product or a new service, and they’ll talk about the S-curve. Hey, this is a really cool new product, it’s WhatsApp. It’s been getting some growth, but now it’s starting to show an S-curve of adoption. Okay, so people talk about the S-curves at the product level. The other type of S-curve you can think about is the diffusion of technology. into an industry or into an economy or into a society, when you have a new tech, a new standard, you also see sort of an S curve of what we call cumulative adoption. When everyone starts, and we could let’s say, when everyone in society starts speaking French, it’s not a product, it’s a standard. It’s a type of technology is really what it is, language. When a certain percentage of the population is all speaking French, it starts to accelerate and we start to see an S curve because everyone realizes there’s so much benefit to speaking the same language as everyone else and everyone stops speaking other languages, which is why in virtually every country, most people speak one language. I mean, there’s a couple of countries that operate in two, but almost at every country level, we’ve seen one language dominate. It’s the S curve of technology adoption. Okay, so when I’m looking at a company like Snowflake or Tuya or I don’t know, Kingsoft Cloud or Azure or whatever, that’s really what I’m looking for. I’m looking for who’s getting adoption because I wanna see if a certain type of technology is gonna start to go vertical within its S curve. And so far, yeah, I mean, they’re all going up. It’s going pretty good, but. Often to see that level of adoption, to see the S-curve start to go vertical, you often need an alliance. And I’m not sure we’re seeing that yet. We saw it in smartphones. So anyways, that’s kind of one, is you look for this cumulative adoption curve. Then you start to talk about, okay, we’re seeing one company, we’re seeing one alliance, we’re starting to see a dominant design. That’s when people start to give up. They say, okay, let’s not have a competing standard. Let’s not have a competing ecosystem. Look, we have to accept that we’re not gonna be the ecosystem. We need to start thinking about being a component within an ecosystem that we don’t control, which is where most people are gonna step, or they’re gonna end up. So we’re looking for sort of a tipping point for when that happens. And then… you know, then it sort of accelerates and we start to see this other idea for today, which is the increasing returns to adoption of technology. So I gave you two concepts for today. One is this idea of innovation that’s driving towards a dominant design, architectural level innovation. The other idea for today is the increasing returns to the adoption of technology, which is… I gave you a language example that when a technology gets more adopted, there are increasing value of that technology. Language would be one example. But there’s actually quite a few reasons why that happens. One is we could call that a standardization network effect. When everyone speaks the same language, we’re all on the same standard, we call that a standardization network effect. That’s in the concept library. But we can also talk about learning effects, which is the more people use one type of technology, hey, we can all write in Python. The more it gets used, the more effective it becomes, the more efficient it becomes, the amount you need to invest to create new products and new services based on Python is less because we’re not making our new app. work with six different languages. It’s only working with one to two languages. So there’s a learning effect. There’s a lot of cost savings. We start to, the efficiencies go up. We start to just sort of see a broad level of expertise. There’s another thing in here which people talk, we talk about sort of what they call path dependency, which is once everyone is using one type of phone, and once that phone is using, let’s say the open handset alliance as its standard, then people start to code maybe in one language, or they start to make their interface protocols one way. One. step tends to lead to the other and we start to see sort of a path dependency where it’s almost impossible to launch a new ecosystem at that point, because it’s not like the ecosystem all happens at once. One step leads to the next, leads to the next, and everything that comes after that, you start to build on the previous step. So then people start making apps. The fight for what is gonna be the standard for a smartphone is over. It’s Android. Well, then everyone making apps starts to build on that and we start to see new standards within apps. Okay, WhatsApp is an ecosystem, it’s a network effect. Alibaba is using sort of an e-commerce ecosystem, but it sits on top of the Android ecosystem. So one step sort of gets built on top of the next, on top of the next. So we see this path dependency that is almost impossible to overcome. And this is actually something that the Chinese government is talking about a lot. They are very aggressively trying to become the next level of infrastructure standard in technology because they recognize the current standards were created 20 years ago. People aren’t gonna move off the current programming languages. They aren’t gonna move off Android. Those standards have already been built. and people have built the next stack of, the next level of technology on top of those. And that path dependency, it’s impossible to overcome. So they’re waiting for the next iteration of technology, AI, cloud, to try and leapfrog in and set the new standards going forward for the next 20 to 30 years. So you’ll see like China has major initiatives based on setting the new international standards because they know the current. standards were all set by the West 20 plus years ago. You’ll see they have big announcements about this all the time. People don’t really talk about it because I think they don’t understand how important it is, in my opinion. Okay and I think that’s kind of the second concept I really wanted to talk about today is just this idea of the increasing returns of technology as they are adopted. There’s a lot of ways this plays out. It’s really pretty powerful. Okay, and that brings us back to sort of the key question for today, which is who is gonna be the dominant design for cloud? We’ve got this chaos of standards, we’ve got this chaos of companies all trying to be the de facto standard, the ecosystem for data, the ecosystem for IoT, the ecosystem for ERP, everyone’s in there. And… The two things I’m looking for, I’m looking for adoption and I’m looking for network externalities. Those are the two things I’m looking for. Okay, adoption, fine, we know what that means. More companies are using this than that. More companies are using this for their data than that. More companies are using this type of cloud printer versus that type of cloud printer. More consumers are putting these. ring and linked cameras in their doorways because Amazon has them, then the competing Xiaomi cameras. We can look at adoption in all of these things. That’s fine, that’s important. I’m looking more B2B than B2C. But then we really wanna see, okay, who is getting adoption around a design that has network externalities? Which is, it’s a network defect. It’s not just, hey, I really like my camera that’s sitting in my living room and it sends me a note every time a pigeon lands on my balcony, which I was doing for a while. That’s fine, it’s more adoption, but it’s not gonna kick in with network effects where maybe we will start to see the whole thing collapse. And that’s why people are talking about this relationship between corporate clients and developers. That’s what Snowfleet will talk about. When they talk about their user groups, they point to two user groups, corporate clients and application developers. They’re trying to get those to both jump on board and that basically looks a lot like Windows in 1985. Who did Bill Gates really capture? He captured consumers and businesses that were buying PCs, that’s the user, and he… captured all of the application developers that wrote programs that ran on Windows. You know, that was what we would call the innovation platform. So those are the two I’m kind of looking for. And that starts to get you a network effect and it starts to collapse. And you can see the same thing in smartphones. People who make the apps versus people that have phones in pockets. And based on that. Let me go back and talk about Snowflake, and this will be sort of the last topic for today. Now, for those of you who are subscribers, I sent you out an article which took me a long, long time, about a week and a half, two weeks ago. Basically, it was titled, Snowflake is Building Three Complementary Platforms with Four Network Effects. That actually took a long time. There’s some pretty crazy graphics in there breaking apart Snowflake. But the argument was basically, When people start using the word ecosystem, that’s pretty much a red flag that the thinking is fuzzy, a lot of hand waving. I don’t usually like to talk about that. I like to look at platform business models and I’ve outlined for you five different platform business models, marketplace, innovation platform, audience builder platform, payment platform, coordination and standardization platforms. And then. learning platforms, those are much more sort of component level granular approaches to creating interactions between user groups as opposed to just throwing up your hands and saying, oh, it’s an ecosystem and lots of user groups interact with each other. I like to sort of think at that level and that’s kind of how I looked at Snowflake and I basically pointed to look, this company clearly is building three complementary platform business models that all support each other. And within those three business models that we can see today, they’re building others, but we can see three today. Within that, we can see at least four network effects starting to kick in. And when I’m looking to determine who’s gonna win the dominant design fight, the architectural innovation fight, if I can see three platform business models with lots of adoption and four network effects, That’s a solid maybe. Okay, so what did I say? I said the core use case for Snowflake. Snowflake has a couple user groups, right? Anytime you look at a platform business model, you wanna identify the user groups because that’s what platform business models are. They are network-based business models that help different user groups interact. Okay, first user group for Snowflake. internal providers and users of data. I actually thought about that language for a long time. This is every corporate client. They have Geico as a client. Geico provides the data. They’re the internal provider inside the company, and then they use the data. So we have entities within Geico that are providing data to Snowflake. It’s being consolidated. It’s being warehoused. It’s being standardized. And then people from Geico are looking at the data. The other user group we could say is external providers and users of data. This might be a partner of Geico. It might be someone in their supply chain. It might be customers. It might be, I don’t know, some other partner they deal with. And what Snowflake does is it lets them sort of, lets those user groups coordinate and standardize their activity. So it’s a coordination and standardization platform. Just like Microsoft Teams, just like Zoom, these platform business models help different groups coordinate a more complicated activity. Now in this case, it’s all about the data. So all those internal providers and users of data at Geico can start to use the service and share data and look at data and work on projects together and do analysis of the data and all those things. And we immediately start to see a network effect. for coordination and sharing, and we see a network effect for standardization and interconnection. That’s a lot of theory. If you look on the concept library, you’ll see all of those terms defined. Network effect for standardization and interconnection, coordination and standardization platform, they’re all there. That starts to get them scaled. They can then interact with users outside. That’s the core case. and they have to build some capabilities to make this happen. It’s not easy. They gotta have a ton of servers and web capabilities. They have to have some fairly impressive capabilities that allow the ingesting of all this corporate data very easily. So you need to have, clean the data, you need to standardize it, you need to ingest it into the platform, such that, you know, if a company signs up for Snowflake today, they submit their data, they can start doing pretty good analysis almost immediately of the data that has been ingested. But it’s actually pretty tricky to do that. Especially as you move out of sort of standard easy data like an Excel spreadsheet to something like the video feed coming out of cameras, which is very unstructured data. It’s much harder to sort of standardize that, ingest that, and put it in a workable form. but that’s kind of what Snowflake is in the business of doing. And then you also need, they need to sort of apply governance, security and compliance rules so that everyone can’t see their data, especially if they share it outside. But that’s kind of their core use case and their core platform is a coordination platform. The secondary platform, that’s the innovation platform. That’s when they start to open up all this data. to application developers. The same way Microsoft Windows enabled connections between users of Windows and application developers of Windows, it’s the same idea. It’s the same reason your app store on your phone is full of hundreds of thousands of apps. Well, once you have that first platform with all that data and all that corporate clients, then you can start to open up that data and people can start to make apps for those. that use all that data in your company, and you can start to have all sorts of functions that run on the data once it’s consolidated. So that’s the secondary platform. Third platform, it’s a marketplace platform. You can start to reach out to companies that sell data, the same way Alibaba and the same way Shopee have lots of merchants that sell products. Well, there’s lots of merchants out there in the world that sell data and you can start to let them sell to your big client base that is very data enabled at this point and they can buy other data to compliment their current situation. Or if they have a lot of data they wanna sell and monetize, they can sell their data. So you have a coordination platform, on top of that you have an innovation platform and on top of that you have a marketplace platform. Three. complementary platforms that all support each other. And you can count up at least four network effects within all of this. That’s a powerhouse of a business model. If it works and it looks like it’s working, that will be one of the most, in my opinion, one of the most powerful business models on the planet. That’ll be up there with Google. That’ll be up there with Facebook. It’ll be up there with Alibaba. it’ll be up there with 10 cent. You know, in terms of my competition tower, my six levels of competition, that’s top level. I mean, it’s as powerful as you’re gonna find. So a lot of this is why if you look at the share price of Snowflake, it’s really, really high. It’s because a lot of people are recognizing this could be the next Google. It may not be, but it certainly looks like it has all the pieces. Anyways, that’s where it is. Now for me, it’s a question of, could that business model end up becoming the dominant design for the cloud for data? And the answer is yeah, maybe, maybe. Now, the big caveat that overshadows that is, who are their competitors? Oh, Amazon, Google, and Microsoft. Well, that’s pretty intimidating. I mean, that’s… you know, that’s not good. So, yeah, that’s a bit daunting there. So it’s really cool on one side and it’s really daunting on the other side. So it’s kind of an interesting company to take a look at. But yeah, that’s kind of the question I’ve been struggling with for about really six months is how is the sort of cloud paradigm gonna shake out in the next couple of years, which I think will happen. Well, I mean, it depends what. Aspect of it you’re looking at if you’re looking at the data aspect of the cloud then this company and Amazon and a couple others Look very compelling if you’re looking at IOT and smart devices Well, Amazon’s in there Alexa, you know You ever know what’s funny about Google? I’m sorry Amazon Alexa is no one will ever name their child Alexa ever again because you literally couldn’t have a child named Alexa in your house, if you have any of these devices, which is kind of funny to think about. So Xiaomi’s in that space trying to make smart homes. They’re actually doing quite well in the smart home world in China and Asia. So in that world, it’s not as clear. Public cloud, that’s another sector. Autonomous vehicles, transportation, mobility. That’s another aspect of the cloud. The financial cloud, which is something that banks and financial services companies are starting to put their data on, that’s a different thing because of the security and compliance standards required there. So there’s a lot going on, but within data, Snowflake is looking pretty good, but Amazon definitely wants the space, so we’ll see. Anyways, that’s kind of where I am in my thinking at this point, but takeaways for today. Keep an eye on Snowflake. I’ll send you some information about Tuya. Kingsoft Cloud is okay, kind of interesting. I’ve sent you some information on that. Those are kind of the companies on my list right now. If you have any other cloud companies to look at, please send them my way. I’m looking at a lot of these. And the two concepts for today are both about innovation. One is innovation related to dominant design. The other is innovation related to the increasing returns to technology adoption. And that is it for content for today. As for me, it’s been, God, it’s been a good week. I mean, like, I’m having such like a good period of life. I’m kind of becoming like, not nervous, but I’m kind of wondering, am I gonna look back and this is gonna, I’m gonna be like, man, those were the good old days. I’m wondering like, maybe I’m not being mindful enough of maybe how things are going right now, because it’s really just been great. You know, the country here is opening up in Bangkok. Everything’s open. Gyms are open. Restaurants are open. Theaters, it’s, you know, people are coming back. The airports, people started flying in internationally in the last couple of days. That’s pretty good. I’m renovating the new condo right now. There’s a team upstairs sort of painting and doing all this. And they’re real fun. So I’ve been hanging out with those guys. you know, they’re painting and fixing everything. And what’s funny is they’re smokers, but you’re not allowed to smoke in the building. And they’re trying to do it secretly. So the one guy, he has cigarettes, he hides under his jacket, and then he sort of closes the bedroom door. And I know he’s smoking in there because when I go out on the street, I look up, and this is like up on the 23rd floor, I see a dude leaning way out the window on the 23rd floor. smoking like his half his torso and his arm are leaned outside and I’m like that’s my apartment so yeah like the worst secret smokers I’ve ever seen they’re all fun guys so yeah that was my afternoon today and it was that’ll be done in the next day so I’m kind of looking forward to that but otherwise not it’s just great no real recommendations the last one I gave you was that movie Dune man that was a good movie I’m gonna go see that again like It’s not a moving story or anything like that. It’s just a sci-fi story. But man, it’s visually… and even the music is unbelievable. It’s really just spectacular to watch. I’m gonna go see that one again on the really big screen before it goes. But yeah, that’s been my week. It’s doing pretty well. Anyways, that’s it for me. I hope this is helpful. I know this was a bit more sort of theory-dense. I try not to go too much into theory. I try to balance that company level thinking and also theory. Build out both of those at the same time. But sometimes I go down the rabbit hole a little bit on theory, I know that. Anyways, I’ll try and keep it more company focused. But yeah, that’s it. I hope that’s helpful if I can ever be of help. And if you have any suggestions on companies to look at, please let me know, I’m always hunting. Ozone was recommended by someone. I’ve gotten some really great recommendations, I appreciate that. Anyways, just let me know, I’m easy to reach on LinkedIn or by email. So that’s it, hope everyone is doing well and I will talk to you next week. Bye bye.