 Hi everyone. Welcome and thanks for attending the presentation. My name is Satya Indrananwal and I'm excited to speak to you about building products in the hyper growth stage. So a little bit about me. I'm currently a product lead at Uber and I've been here for the last five and a half years. Before this, I spent a couple of years at Facebook, a few years before that at Microsoft, and my academic training is in human computer interaction and social computing. And like all of you, I'm passionate about building products and that's what we're going to talk about today. So as a PM, every day you're faced with tough choices. Meet Alice. Alex works at a hyper growth FinTech company. Her payments product is really taking off. She's swamped with feature requests and had a has a full roadmap. Her competing company is investing in crypto. Alice believes crypto could be really big for her product, but it's torn between pursuing it or focusing on her core product. How should Alice proceed. I'm sure each one of you has been in similar situations where you've had to make similar decisions. And my goal today is in discussing a few learnings and some frameworks, so that after having gone through those. It gives you a framework to reason about such questions in terms of how do you understand your options in these stages. How do you evaluate the alternatives and plan trade offs. And finally, how do you act and what you should prioritize when you're in situations like this. Before we get there though, let's look a little bit more into hyper growth phase and what's interesting about that. So, there are various definitions out there, but my favorite one is one by Nicholas single who's a VP of product management at Facebook. So instead of thinking about a certain percentage of growth to define hyper growth, he looks at it from four different stages of the product. The first is a drunken walk, where essentially you are wandering around semi randomly and trying to find some kind of value and exploring product market fit. In the second stage you start to find a trade and refine that bit of product market fit. The third stage is where you reach hyper growth, where you've clearly achieved product market fit, and now your entire goal is to scale your product, increase the value your product provides, and really build and solidify that competitive advantage. So while it's amazing to be in the hyper growth stage. It comes with its unique challenges. This challenge primarily stems from the need to scale your current business and grow new business lines simultaneously. Now scaling the business is hard. You need to scale engineering, you need to scale design, grow the team, and doing all of that at high quality is hard by itself. So you can combine that with the search for a new venture, trying to use your growth and engagement as leverage and expand to other use cases with the limited resources you have. It's really challenging. And the only way to do it well is really to balance execution with strategy. That's one of the unique aspects of hyper growth stage in a product where product management truly becomes a strategic function. And you see examples of this kind of scaling and venturing into new business line, all the time in our industry. A great example is Uber. Uber's right sharing business, a clearly found product market fit, growing at a rapid pace. That's when they started and ventured into eats a whole new category. And just as the eats business for scaling up, moved into another new business freight, and then elevate and then autonomous, all at different stages, but each trying to do the same thing that while scaling the current business finding these new lines of growth. Facebook is another great example. The whole family of apps of processing huge and massive growth. I recently read an article where it said that 20% of Facebook employees now in some shape or form work on AR and VR. Another great example of how at even at such scale, they're trying to find the next growth lever in their business. Tiktok is another fascinating examples. There's been hyper growth in terms of short form video consumption. And even in this core category, when there's so much room to grow, they're already venturing out and exploring new growth engines like live and socials shopping. So whether you're at one of these companies, or at your own company, when you're faced with these kind of situations and office question is, which of these new ventures do we invest in. The interesting way of looking at that question is to think of these ventures as bets. Now bets is a really interesting word and has a very specific connotation here. So think of a game of chess versus a game of poker. In chess, your skill dominates quite a bit poker, while you need skill. The outcome is also dependent to a large scale on luck and uncertainty. When you build product in the real world, it resembles poker more than it resemble chess in the sense that outcomes depends significantly on uncertainty and in many cases luck. So when you think of planning your product portfolio, you need to balance the risk in your bets to maximize chances of success. When you think of these different kinds of bets, a useful framework I found is something Ken Beck proposed, which is to look at these three specific types of bets. Explore, expand and extract. Explore basically aligns with identifying new opportunities. Expand aligns more with growth and scaling and extract is more about optimizing and tweaking your processes and your product to maximize your revenue and profitability. Each of these types of bets has unique needs, which is quite different from the other. And that dictates what kind of things become important in when you're thinking of these bets and how you approach them. So in the Explore stage, it's very early stage and your primary goal is searching for value when there's high uncertainty. So a primary goal for you there is to de-risk and move as fast as possible, trying out many solutions and de-risking them as quickly as you can so that you can try out more things. On the second or the expand stage, your primary focus is on eliminating bottlenecks to growth. By eliminating these bottlenecks, you can unlock growth, whether it's in increasing revenue, increasing your number of users or increasing engagement. And finally, on the extract stage, the core focus is for a mature product to try to optimize for increasing profits and reducing costs. And you do that by optimizing and tweaking various levers you can press, and this is somewhere where scale really matters. So small changes that you can do can have an outsized impact because of the scale of things. Think of a small change you do on the Amazon homepage, and if it works, the impact you can have on revenue and profitability because of the number of users Amazon has. Now, when you're planning, it's important to allocate investments across these bed types to maximize your chances of success. Now, these are not recommendations, but just example allocations. But typically in the expand stage where there's high return on investment and the value is known so you know your products providing some value. And the key goal is to scale it, you want to invest a significant amount of resources, because this is known value that you want to extract. On the other hand, on the right hand side on the extract stage, you also want to invest quite a bit, because you know that targeted refinements, the ones that work out can give you huge advantages because you're leveraging economies of scale in a mature product and small improvements are going to give you large gains. But you do want to reserve some capacity and invested into the explore stage, because although the risk is high, there's a huge asymmetric upside. And if that risk works out, you could have a whole new line of business emerging from the explore category. But there is high risk, both in terms of the value you can provide and executing to provide that value. And de-risking that risk is an important aspect. So as a product manager, typically you need to spend more time on the explore stage than your entire organization would. And this is because there's extreme uncertainty in the explore stage. You're not really sure of who should be your core user or persona that you're focusing on. There's uncertainty around what would be valuable for that group that you've identified. And finally, does your product actually provide that value? And when there's such a lot of uncertainty in so many different dimensions, a really good approach is to be super focused. So if you're not really sure who should your focus be, it's always, always better to be extremely focused rather than going broad. A fascinating example is Tesla Roadster, where the entire audience group of people who would find their offering attractive was about 2.5,000 to 3,000 people who would actually buy that car. But for that group, they'd identified something that would be 10 times more valuable than anything else their peer group could provide. For example, for the Roadster, it was faster, it was cleaner technology, and it was more forward thinking technology than anything in its class. And so it's really important for you to identify a very, it could be a very narrow group, but identify a very focused group and for that group have a clear hypothesis on something that would provide them 10 times or a huge amount of value. And then you want to better the stage where you're trying to de-risk of the question that does our product provide that value. To do that, in the explore stage, you need to exit it with a clear understanding of what are your riskiest assumptions, and then systematically start to de-risk them. So now we'll talk a little bit about how to de-risk your riskiest assumptions and some examples that might give you some inspiration. So the first part is to, like we talked about, is to actually identify what your riskiest assumptions are. And it could be the entire value proposition of your product. For example, for DoorDash in the early days, a key question was, will people even pay for delivery? It might seem obvious now, but at that point that was a big question, and the entire company hinged on that. So in terms of another example, the question could be more at a feature level. For example, for Buffer, which is a company, the question could be, will people actually pay for this service? So it's a feature in a product. Or it could be at a solution level. For example, when we were looking at redesigning the UberRight sharing experience, one of the questions was, can we optimize the request flow? If it was at the top of the funnel, what if we didn't ask you for the pickup location and just asked you for drop-off? It was a risky proposition because it was right at the top of the funnel, but it could simplify the experience. So remember, you want to identify assumptions which, if you de-risk, will give you high confidence and or a unique insight advantage as you move forward with the rest of your product. Taking those same examples, in case of DoorDash, the founders actually did deliveries between their classes at Stanford. They gave a Google Voice number, pasted PDF menus, and charged $6 for deliveries to try to validate that people would be willing to pay for the solution, and they successfully did that. In case of Buffer, they launched on the first day with the payment solution without actually having built out the entire payment infrastructure. And this was possible because the CEO was manually emailing PayPal confirmation receipts to customers so that they felt there was the payment functionality was working. In case of our Uber example for destination first, we used a static screenshot to simulate the app flow and have users walk through it. And the users didn't know whether that was a real app or a screenshot, but if they clicked on where to and they didn't seem startled by this change in flow and give us confidence, early confidence that we could proceed in this direction. So remember, at this stage, you want to de-risk as fast and as cheaply as possible. The key goal is to really learn a lot quickly. And anything that doesn't contribute directly to that goal learning, you should try to shortcut or find your way around that. In the entire Explore stage, the biggest goal that I want to stress is to accelerate your learning. The more amount of experiments you can run, the faster you can run them, the higher you maximize your chances of success. If I give you a goal of in this month, can you increase the rate of your learning by 10 times? It seems like a really ambitious goal. But if you start to break it down creatively, you start to think that, can I run five times the experiment? And can I run them in half the time? And if you can do that, using creative ways like we just talked about, you can actually 10x the amount of learning you would get in that month. The faster pivots here are crucial because remember, there's a lot of uncertainty and you don't know which solutions will work and which won't. You just have hypotheses. So the faster you can pivot here, the more you increase your odds of success and the longevity of your idea and company. So that was a lot of stuff to walk through. But in summary, we talked about the hyper growth phase and how there are specific unique needs. And how because of those unique needs of balancing scale with growing new business ventures, product really starts to become a truly strategic function. And you are operating in an environment of a lot of uncertainty and luck. So in those cases, it helps about thinking about your product launches or ventures as best. And dividing up those bets in a portfolio along ideas such as exploring, expanding and extracting. Once you do that in the explore stage is where you find the highest amount of uncertainty. And in that stage, your key goal should be to de-risk and learn as much as possible as quickly as possible. To do that, you need to identify your riskiest assumptions. De-risk it fast and cheap and then learn and iterate in that way. And if you're doing all of that, hopefully you'd have a successful product and don't forget to have fun building it as a team. Thank you again for your time. I hope you enjoyed the talk. Please let me know if you have any questions or thoughts and have a great day. Bye bye.