 Hello, everyone. Welcome to this session of learning about how to make decisions at a startup and about zero-to-one products in general. My name is Chandr Chawla and I have been a founder of three startups. I worked at three or four startups as VP or head of product. So I think in total, I have launched at least 250-to-one products in both big companies and startups. I've advised, I don't know, 40-50 startups on launching products. So in total, I've seen products go through maybe 60-70 products go through the process of coming to life and you can learn more about me on LinkedIn. I have a blog that's cdoc.blogspot.com. I am a co-host of a podcast that's Valley Nordic and that's about providing Silicon Valley and Nordic perspectives to people mainly in the Nordic countries because the venture capitalist who's the other co-host is based in Norway. So let's get started. So before we get started, let's do a quiz or do set the frame or the discussion. If you look at the slide here, there are three options since this is not live. So let's see. Generally when I do this presentation live, most people say C is the wrong answer, A, B and D are the right answers. And we assume because we mainly deal with base 10 arithmetic or addition that anything that doesn't fit into that frame is wrong. So C is right if you use base 12 addition. So base 10 is A, B and D, C is using base 12. So that's kind of very similar to going from a big company to startup or doing things at a startup. You have to think differently. So in essence, this presentation is all about how to think about making decisions at startup. Let's go to the next slide. That's what is a startup about or business in general? So at a very fundamental level, startups or business in general is about four things. First, you need an idea and that idea becomes product or a service. You need a market for that idea or product service. And then you need capital to grow that business and you need people to execute work on building the product, marketing sales, etc. So when we say execution, that execution is really important in startup, it is the interplay of these four things, product, market, capital and people. So it's important to know as product managers who are listening to this, product is one part of the interplay that you are responsible for. But you have to think in terms of what is the market, how much capital is it costing and what kind of people do we need or what we have, what we can do with that. Then another framing is given that there are things or let's see how you think about knowledge. So knowledge, you can structure that into two things. One is things that are knowable and things that are unknowable. So knowable things are the things you can learn from others, from reading, from talking to people. So in a startup construct, you can learn about people, capital, technology, get the product, what the market is, what the competition is, what the history is. But as a startup, you are creating something new that's innovation that has not existed before. So this is something new where we don't have a track record or history. You can find similar things, but actually how it will work in the real world, you can only find out by doing. So that's the unknowable zone. So that's where the innovation happens, that's where or the innovation operates in the unknowable zone. So meaning things you can learn only by doing. And that's where startups are, especially in the early stages. So now what we'll go through are seven heuristics that I have learned from my own experience working at startups and also launching zero to one products and bigger companies. But they're derived from teachings of Dr. Yaneer Baryam, who is a complex system scientist and I've attended New England Complex Systems Institute programs or work with them. So a lot of the credit what I will share goes to Dr. Yaneer Baryam. And you will see many of them are the mistakes I've made. So my point of sharing these mistakes or learnings is that you don't have to make them and you can change your thinking before you make them mistakes. So let's see what they are. There are seven of them. First is business plan is useless. So when you're launching something new, innovating, creating a startup, there's a lot of uncertainty, a lot of variability of what will happen, ambiguity, randomness, everything you see on the slide here. And I got it from Naseem Khaleb, who's another author. I think who's been very influential in changing my thinking. So they operate in this domain of uncertainty and ambiguity. And plan is about the future. You are stating that you're going to do something in X number of years. This will be the revenue and cost and growth, et cetera. But you don't really know. It's all made up. So that's why I say it's useless, especially in the early stages of a startup. Instead, what you need is a learning plan. So there, as we just talked, you're operating in the unknowable zone. So what do you want to learn in that unknowable zone that can only be learned by doing? So you figure out a plan. This is what we're going to do. This is the hypothesis we want to task by doing. And these are the things we want to learn. So I think a learning plan is much more important than a business plan. But in the real world, when you go to a venture capitalist to ask for money, they all want a business plan. And even at a bigger company, you need to show a business plan for your new product idea. So what do you do? So I've seen this so many times. So much detail goes into finding the accuracy of the models in Excel we create. Oh, is the growth rate going to be 97% or 93%? You spend hours trying to be precise. Or the conversion rate is 3.2% or 4.9%. All that doesn't matter. You need a plan. And everybody wants to see a hockey stick. You create a plan that shows a hockey stick. Otherwise, you won't get funded. But so spend less time on creating a business plan and spend more time on doing a learning plan. So that to summarize that learning here or heuristic here is plan less and do more. And that doing involves creating a learning plan and executing it. Next is winner takes all. That's mainly applicable to digital products, which most of them are today. So the picture you see here is Wilfredo or Vincento Pereira. He was a famous mathematician in Italy. He came up with the 80-20 rule, which I think most of us are familiar with. It's also called Pereira rule. He observed that 80% of the property in Italy was owned by 20% of the people. But it applies to level deeper. So if you take 80% of 80%, it's 64%. And if you take 80% of 64%, it's 50%. And then on the other side, you have 20%. So if you do 20% of 20%, that's 4%. And if you take 20% of 4%, that's 0.75%. So you can say 1% owns 50%. So if you are one company that means can own more than half the market or majority of the market. So that's a very, I think, powerful insight in the digital domain. And there are many examples in the business world. So you can see the market's share of search that's Google owns, I don't know, 80%, 90% or huge number. Uber owns majority of the market and right-sharing, etc., etc. So there are many examples of that. So how do you apply that to your startup or when you are building products? So you have to think big, but you have to act small. And if you are not getting bigger, you may disappear. And the reason for that is, let's say you start a company, you don't really want to get bigger. You are happy with owning 10% of a niche. But the other players in the market are trying to get bigger. So they will gain more efficiencies and they will gain more and more market share and eventually come after the niche you are targeting. And if you are not growing, they may acquire you or find drive you out of business and you may have to sell to them. So you have to put this thinking in mind of growth, especially in the digital space, is one of the key elements of success or winning in the startup space, especially for digital products. So the lesson is think big, act small. Because early stages, you have to make small, maybe, they're launching a product, just launch in one city, just launch to 1000 people. So you prove the hypothesis, have a learning plan, but always having the vision in mind that you want to debate. Otherwise, you may disappear. And next is understanding causation. So you may be noticing that I'm taking examples from outside of the business world, how they're applied, can be applied through the startup world. So what you see here is a graph of UN food price index, where you see the red lines, that's where the food prices went up. And you may remember at a spring that happened a decade or so ago. And if you asked most people in Silicon Valley why that happened, I think most people would say it was because of social media, camera phones, people were protesting. And that's how it happened. But that's not the causation that didn't cause these things existed before the revolution or Arab Spring happened. So what caused the Arab Spring was the increase in food prices. The food prices doubled, more than doubled in many cases, as you see on the graph. In the countries listed here, and you see this is the number of, I think in the parentheses is the number of deaths in that country because of the riots and protests. So it's very applicable to startups because I see over and over how we don't really understand causation of why people are buying or using the product. To give you a practical example or first-hand example, I was had a product at a company and when I joined, I had to decide the roadmap. So do we focus on making the machine learning algorithms for the core of the product better or add new features? So how do you decide? So we had like 30 something features in the product. I asked the team which ones are being used and nobody knew. So then I went to the customers and I asked them and I learned we had to figure it out. They weren't quite sure either. Out of 30 something features, we had only two were being used. So that told me, okay, we need to make those features better. But that was the harder thing to do than creating something new. But that's critical because that's why people are using the product, not because of all the features we have. So as a startup, what do you do? So let's say you have a product idea and to simplify, let's say it has two features, A and B. If it's a digital product, you can launch three versions. There's version for feature A, version of feature B, and a version with A and B. And then you see, okay, which one is more in use and it'll give you a crystal clear understanding of how people are prioritizing. Users are actually using the product, what's causing the adoption, usage or purchase. So you have to find ways to understand that position. So the lesson is get a crystal clear understanding of why people are using the product. Next is do not confuse risk with probability. This example I got from Naseem Talib. So it's very interesting. I think every year, a few hundred people die from falling from ladders. And you can see, you can predict, okay, there's all this data from last 40, 50 years, these many people are dying from falling from ladders. It's not going to become millions of people next year. We have all the past data. So the probability is very high that the numbers will be close to what it was last few years. But on the other hand, the risk of dying somebody from terrorism, you don't know. It's unknown. You can look at all, you know, 50 years of data and you still don't know what's going to happen tomorrow. So the risk is much higher of dying from a terrorist attack than from falling from ladders. But how it's portrayed in media sometimes, and even scholars, PhD, you read these articles, oh, the threat is over of terrorism and you have higher risk of dying from a traffic accident or falling from ladders than from a terrorist attack. So I think that's incorrect. The risk is higher with terrorism attack because we don't know. The past data doesn't tell us anything. So how does that apply to startups? Or decision making? So it applies that you have to create optionality because as a startup, you're operating in a high risk area. If you look at the data, most of the startups fail, but that doesn't determine necessarily your outcome or your success. So you have to, since you're operating in that high risk domain, you have to find optionality of your idea. Have optionality. Don't fall in love with the original idea. Think of other options. Many of the successful startups have pivoted or evolved their idea. So if you fall in love with your idea, it's harder to succeed because you take that idea to the market and market doesn't agree with it, then what do you do? So when you're designing the product, thinking of architecture, think of how you can make it flexible so you can do other things with it and test a lot of options, especially in the early stages when you are trying to figure things out, what would work with people? Okay, next is TMI stands for too much information. Too much information increases confidence and not accuracy. So the chart you see here is analyzed GDP growth in percentage from 1950 to 2010, and the yellow area is the great moderation. So you see until 1985, there are huge swings in GDP growth in the U.S. It could grow up to 15% one year or declined by 10% in one year. And Ben Bernanke was the Fed chair in early 2000s. He gave a talk or lectures on the concept of great moderation that the era of this wild swings and GDP is over, now we are in this era of great moderation. And I think most people would know the power the U.S. Federal Chair has. Everything they say, it's analyzed to the nth degree. You know, when Chairman Powell now when he speaks, like there's commentary for ours on CNBC, on Bloomberg, oh, he touched his nose that means he wasn't sure. Like everything analyzed. So they're very, very cautious in what they say and what they don't say. So if Bernanke came up with this concept and gave a lecture, that means they had done a lot of research. Hundreds of PhDs worked on this and came up with this idea. And then what happens? Next year in 2008, the market crashes. The GDP goes down more than 5%. So the point here is such smart people, PhDs working at the Fed chair can get confident with the amount of data they have, then so can be. So you have to find out how not are you getting overconfident with data? And there are many examples in the business world of that, that people had thought they had a lot of data. It said one thing, the reality was something else. And how it applies to startups is understand correlation among the variables in your business. Like how is marketing related to how much customer acquisition cost with product development, with how much capital is needed, how the customer success or support things are increasing when you launch a new version of the product. And because there's too much information in the world, how do you stand out? How do you position your startup for success? Because how do people find out you exist? So one of the tricks I see that Mary Meeker, who is one of the venture capitalists she uses or used to use was saying things in aggregate. When they presented numbers about wearable devices, which they had investments in, they would say the aggregate number of steps people have taken using a wearable device. So that number is in trillions, the total number of steps people take in a year. So that raises eyebrows or you pay attention. But if you say the same thing, okay, people take 10,000 steps in a day. There are 365 days in a year. You divide that by number of steps. The actual number of devices in use is probably at the time was a few million. So that doesn't raise any attention, doesn't make you stand out. So find ways how you can stand out and rise above the noise for too much information in the world that people are getting every day. So you get noticed. So find ways for making your start position well in the market. And next is replication with variation and selection with competition. This idea comes from biology. So the theory of evolution that Darwin came up with states that genes, they replicate with variation. So and let's say there's a gene A, then when it replicates or goes to the next generation, you have A1, A2, A3, and they compete with each other. And then the, let's say A3 wins in that competition. And then that reproduces again and on and on. So that's the general idea. I think the venture capital world and Silicon Valley and many other places around the world work in a similar way. Some idea gets hot and then a lot of investment goes to that idea. So for example, right now, Web 3 is hot. Like everybody's investing money in Web 3. Before that it was AI. Before that it was big data. Before that it was cloud. Like there's always something where the money is going. So how do you position yourself in that world, because you need capital to get the, to execute on that idea? Like going back to the earlier slide, capital is one of the core things for a startup. If you run out of capital, it's over. So you may have to position your startup that you are able to get attention from the venture community and raise capital. And even you may have to do that in a big company as well, whatever, in all big companies, something's always hot. You find ways to position yourself so you get funding internally or externally for that idea to make a product. And then find a market, et cetera. That doesn't mean you just copy what everybody's doing. You have an idea and if you are having, if you can raise capital with that, great. But if you can, you may change the positioning. Let's say you're using some ML machine learning for some simple task in the back end. You can position yourself as an ML company, but that doesn't mean you change. You succeed by creating value, but to succeed, you need capital. So you may have to play the game of where the money is going, wearing that hat to get the capital and focusing on creating unique value. Next is competition and cooperation work together. So this is really interesting because the example I have here is from sports. So let's say the American Football League. So at the sport level, you're competing with all the other sports. Football is competing with basketball or Netflix or any other forms of entertainment. But the teams collaborate to form a league and they advertise. The people come and watch the games, et cetera. And at the team level, teams compete with each other. That's the sport. But if you go to the player level, then the players are collaborating within a team to win the game, but they're also competing with each other to win the sponsorships, get more money, get more followers, et cetera, et cetera. So depending on the scale you have, or where you're operating, you have to see the competition and cooperation work together. So in the tech world, a lot of the competitors align to fight that we keep the principle of net neutrality in the US. So that's the teams, companies collaborating. And since this is an open environment, I'm based in Silicon Valley. People talk to each other. Generally, people don't try to hide the idea. So if you see somebody else is doing the exact same thing you're doing, then you try to do that differently. And that actually reminds me the previous slide where I said the competition is also among the startups. A lot of money goes into different forms of the same idea. And they compete and one of them wins. Okay, coming back to here, what do you do with that as a startup or how do you make decisions? So choose the right environment which is open so you can learn what other companies are doing and adapt your idea and have access to capital and capital connections and competence. So choose the right place where you can have that. But I think that's changing now with things getting remote. So I think startups will have more access to capital connections and competence. Things are getting remote. So let's summarize the seven heuristics as they apply to the startup or entrepreneurial success. First is plan less, do more, create a learning plan. Second, think big, act small. If you're not growing, you may disappear. Third, get a crystal clear understanding of why people are using your product. Four, don't fall in love with their idea. Test a lot of options. Five, understand correlation amongst variables in your business. Position your startup to be noticed. Six, pick a positioning category where money is going and focus on creating unique value. Seven, choose the right environment which is open and gives you access to capital connections and competence. And there is an article I wrote about the subject in Forbes a few years ago. The link to that article is here in this presentation. But if you search my name and Forbes, you will find that as well. And the other things I've learned are on my blog and you can learn more about what I have learned from the startup world and product on our podcast. Thanks everyone for joining us today. Bye.