The Successful Entrepreneur Formula w/ Salim Ismail | EP #47

0:00You know, in the old school companies, you would hire a consultant to tell you what to do. Well, that's gone today because the market is changing too fast. The day before something is truly a breakthrough, it's a crazy idea. It's the most fundamental archetypal process in life. You never know where the breakthrough idea is going to come from. Your ability to adapt is going to drive market value. Value is okay. So you just got to go with it. And so you have to be able to build that deeply into your business to succeed properly, especially in all the telegraph. So if you're an entrepreneur starting a company, one of the things I you know, be seated you to try is Welcome to our next episode of moonshots and mindsets.

0:40I'm here with my dear friend Selim Ismail, my co -author of our newest book, Exponential Organizations 2 .0, the first CEO of Singularity University. Selim, let's talk about one of my favorite subjects of an EXO, which is experimentation. We're living in a world where your ability as an entrepreneur to experiment on your products and services at lightning speed is better than ever. And ultimately, we're giving up our belief that we humans know what's right and saying, forget about that, let's find out what actually works as a product in a service. But before we get into that, my friend, would you refine, define what is an exponential organization?

1:26So, and EXO as we call it, is a 21st century organizational design that goes away from the top down hierarchical pyramid style command and control structures of the 20th century and moves to a much flatter experimentation driven, purpose driven agile, flexible, scalable organization structure. And we found that we looked at the fastest growing unicorns and teased out the model. So we're not really inventing something. We're putting labels on what already exists. And EXO is delivering typically 10x better faster cheaper than it's peers in the same space. Just to give you a hard data point, we mapped the Fortune 100 against this model and found that the top 10 most EXO friendly of the Fortune 100 outperformed the bottom 10 least like the least flexible least agile of the Fortune 100 over a seven year period, delivered 40 times better shareholder returns between the top 10 and bottom 10.

2:21This just blows your mind. As the external world becomes more volatile, your ability to adapt is gonna drive market value. So if you're an EXO, a key driver of that adaptation is running experiments and constantly sensing the outside world. Yeah, I mean, people need to wake up to the fact that things have changed. This is not your dad's or your granddad's old business environment. People are building brand new types of companies that are outperforming multi -billion dollar conglomerate, global companies at lightning speed. So we talk about in previous podcasts, the idea that we have internal attributes that your company uses, your employees use to run an exponential organization, and external ways that you manage the external world, or you leverage the external world.

3:10And experiments are, you know, they cross both, right? You can run internal experiments and external, I'll mention this, I have an EXO, my PhD ventures that manages a lot of my companies and products. I am constantly just demanding that the team be running experiments. One of the things I realized is a lot of companies that are being born today, These are startups by entrepreneur started today are born with a culture of experimentation from the very beginning, their running experimentation, versus the old school, which was, you know, the old school companies you would hire a consultant to tell you what to do.

3:56And that consultant had over time built a model in their mind and you were paying them for their for their knowledge, but But that's just broken right now. It's completely broken in. And this is a really key point that the difference between the old and the new, right? In the old, you rose to the leadership of a big company. Let's say you were the head of supply chain for BMW is because you ran supply chain at some local level and understood the dynamics of that. Then you rose to a country supply chain level. Then you were supply chain for one, one tech of a car and you understood, okay, if the bit of a recession, what suppliers do I go after, etc.

4:31in you rose in prominence over usually by seniority and having deep intuition about that domain space. Well, intuition. As really important. In intuition, you drove your thing by deep experience and intuition and you had a gut sense of how the market was operating. Well, that's gone today because the market is changing too fast. Anybody who's got 20 years of experience with supply chain of combustion engine cars is irrelevant as electric cars come along because the dynamics are completely different. Right? So now what the only way to make sense and do sense making the outside world is constantly be running experiments, testing the outside world.

5:08You think of an amoeba, right? Constantly probing outward from itself, trying to see what's going on and then absorbing the things that it sees as food. That's kind of the way we think of organizations in the future. You know, it's interesting. As a young startup, you have, you go in with an assumption, You go in with what I think people are going to want. And then the ability to run not just a couple of experiments like what subject line should we use, but thousands of experiments simultaneously given the rise of generative AI and algorithms is massive. And a lot of times our intuition is wrong about what people want or what they're going react to.

5:51And it's only when you run these experiments, do you find yourself evolving the product rapidly? And you've got to be building an internal culture of experimentation, one in which failure is okay. Because if you're going to experiment, probably 90 to 99 .9 % of the time, you're going to be failing. And failure means, okay, I've learned something. I'm not going to do it that way. Yeah. Exactly. You know, I got a little story here when we were on, I was a Yahoo, who we came across as because AB testing on a website is kind of one of the original forms of experimentation. You throw out a million pages with this and a million pages with this, you know, with the responses and you have hard driven data as to what works.

6:29On the Yahoo homepage, there used to be seven headlines in the middle box. Okay. And we found over tweaking this that if you reduced it to six or increased to eight, the clickthroughs dropped off radically. But seven for some reason was a magic number that worked. Nobody knew why it worked. Nobody had any rationale for why that number worked. It doesn't make any sense at all, but for some reason, and we found that just from A, B testing and trialling the experimentation, that number works. So you go, okay, it works, you go with it, but you've no idea why and how. And that's the thesis of the external world.

7:02You may come across something that works. You can't explain how or why. So you just got to go with it. And the only way we're going to find that is running lots and lots of different tests and experiments. I was on stage with Steve Wozniak for an hour and a half debating this and he called it Tinkerin Right, can you just get in the bag and just play let your people just play with stuff and interesting things will happen a quick break from our episode On June the 6th Selim and I are gonna be running a free three -hour workshop on how to actually build and design an Exponential organization would love to have you join us if you join us on June the 6th first of all You'll get free access to the book, Exponential Organizations 2 .0, access to an AI that we've built that allows you to query the book and helps you design your exponential organization.

7:48It's June the 6th, it's three hours, it's free, we've never done this before. Click on the link below, dmandis .com, backslash, EXO, and join us. Alright, now back to the episode. Yeah. And you know, it's a lot of, for larger companies that are trying to figure out where they go next, right? Your products and services are stayed and you're trying to design what do you do? I remember in my book, Bold, we wrote about something called a 555 plan, which was a form of experimentation. Now if you have a thousand employees, imagine forming groups of five and you say to them, listen, over the next five days, we want you to in your group of five, which by the way, diversity in the group, like having an engineer and a scientist and an executive assistant, like different groups, it's not all engineering or not all marketing.

8:43We're going to give you a $500 budget. We want you to go and experiment out there with designing, you product or service. It works really well in the digital world, right? And if you get hundreds of ideas and they're experimented on, then you find a signal in the noise, like, Huh, this idea that we didn't expect, and if you're running a 555 experiment, it's really important to incentivize people to try crazy ideas. One of the things I like to say is the day before something is truly a breakthrough, it's a crazy idea. If it wasn't a crazy idea yesterday, then it wouldn't be a breakthrough today.

9:21It would be an incremental improvement. If, in fact, breakthroughs require experimenting with crazy ideas, when I'm in the the boardroom or on stage like you are, I say, where is your crazy idea department inside your company if you don't have one, if you don't allow your team to play with crazy ideas, your stock on incrementalism. You know, Amazon in fact actually measures this down to that level. They ask for every team inside Amazon, you're asked, how many experiments did you run this quarter? How many succeeded? How many failed? If you're not running enough experiments and not enough for failing, your bonus gets distinct, right?

9:58Because you're constantly pushing the learning of the organization at a whole not by accident as Amazon on the biggest companies in the world. Yeah, Jeff Holden, who's a friend, I haven't seen him in a while though, unfortunately, but Jeff was on my boy at X Prize and he was the chief product officer at Amazon and also at Uber. And he was deeply involved. In fact, I think Amazon built a experimentation engine. I think They were exactly doing that. It was like, they're running thousands of experiments. I remember Jeff Bezos quoted him, said, you know, the success of Amazon is a function of the number of experiments we run per year, per month, per day.

10:41And because we actually, as humans, are biased, but we don't know what works until you try it until you try, we check writers out there. So if we lift up a level, this gives the rationale for this, I think, very powerfully, because The external world today is so volatile and so unclear as to what's coming. We have 20 good, more moments. You call them asteroid impacts. We've got pandemics. We've got bank closures. We've got geopolitical risk at a kind of a crazy level. The only way, you know, in the past, you're a senior executive's based on their intuition will go off and hunker down and come up with a strategy.

11:15And you can't do that anymore. That's irrelevant. What you need to be doing today is basically running a thousand experiments, constantly probing the edges of the world and seeing what works and doing sense making in that way. Seeing what works and ruthlessly following that, even though it goes against your experience, it goes against your intuition, just ruthlessly following that. Eric Greasecock talks about this as a startup being an experiment looking for a business model. That's a startup. And so you just got to run tons of experiments and you look at the biggest companies in the world. All of them started with Tinkrin.

11:50Okay? Larian Sergei playing with algorithms and Steven, Steve Jobs and Wozniak tinkering with a computer, playing around with Facebook groups. All of them started as little companies that experimented a lot and iterated like hell. And sometimes your intuition, like you said, is wrong. So when, Jeff on the was talking about at Amazon when Prime was first proposed, you know, the idea of free shipping for people, it was thought of as a crazy idea. And Bezos said, let's try it. And of course, Amazon Prime is now driving huge double digit majority of their revenues, their profits. It's incredible when people come across those things and hindsight it looks so obvious, right?

12:37And at the time it looked like a crazy idea, just as you talk about it, and you won't find them unless you have that culture. Well, what I think is one of the most powerful developments today is with the rise of chat GPT and auto GPT and some of the generative AI capabilities, we can now train AI's to run those experiments and even conceive of those experiments. So you should be kind of going, hey AI, go run a thousand experiments on this domain and figure out what works. Yeah, we're getting there very quickly. And you know, one of the companies out there that's one of probably the great experimenting companies of our lifetime is Google, right?

13:16And Google, not on experiments at the tiny level of bits on a sort of pixels on a page, they built something called Google X when Google went to Alphabet, it became known as X. And Astro Teller runs that. And he's been on my stage now a number of times a good friend and a brilliant individual. And he talks about the importance of rapid experimentation with companies. So Google, Google X, I'll call it for the moment versus X, has built and experimented with thousands of companies. And you wouldn't know that because it's kept somewhat internally secret. I asked him why you keep all the companies you're experimenting with secret.

14:04And he said because we kill so many of them so rapidly, we don't want to have on the front page of the news in San Jose, Google fails another company. It looks like we're doing poorly, but the idea of starting an experiment and failing it quickly is critical because if you have a startup and a startup can be a single person spending their afternoons or weekends or a small team, and you have a thesis for what you're going to create, but after a period of time you realize it's not working, the worst thing you want to do is keep spending your time and your money on that. So the best thing you can do is kill it quickly and then recycle those individuals and to another idea.

14:46And make sure you trap the learning. I may have some small part to play in this period. In 2010, we had a singularity event. The Larry page was there. Remember he came and spoke at the closing ceremonies. And he grabbed me at the reception afterwards and he said, Hey, your your brick house unit, Yahoo, it was really great. Should I do that at Google? And I said, no, I said, don't do it because Yahoo used our innovation unit as a PR exercise to show the world that we're really cool, which put a massive spotlight on us, which might we couldn't fail. Right? I said, keep it stealth and point it into adjacent areas.

15:20And now, you know, obviously lots of his own thinking, but then that essentially is Google X where they keep it stealth. You have to be able to fail elegantly and take the learnings. The thing that I remember that was the most powerful from your conversations with Astro was that when they do a project at X, they will say, what are the 10th reasons that this might fail? Let's take them, go and tell us. Yeah, it is, it's really important heuristic. It's called a pre -mortem. So we all know what a post -mortem is. Like after a project has failed or a product or service or company, you look back and say, okay, why did it fail?

15:55And you said, what we do is a something called a pre -mortem. So before we launch a product or a service, we get together with the team and we say, okay, I want you to imagine that we are three months after the launch of the product or the service and it failed miserably. And you know why it failed. Write down on a piece of paper the reason that this product failed and they collect all of those and then they discuss them. And sometimes they find actually great reasons why this is going to fail, but no one was felt permission to share their idea. So anyway, that's for me, these ideas of a primordom are super helpful.

16:38What I loved about what I loved about that approach was they take the biggest reasons why they might fail and they test those first. Right? And then you should be able to knock that idea off the perch pretty quickly. If you take the top highest reasons that may fail and then it's just work right down the list. But if you get to the end of the list, this is going to be a successful product because you worked out all the big issues. This episode is brought to you by levels. One of the most important things that I do to try and maintain my peak vitality and longevity is to monitor my blood glucose.

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17:50And these are things that I've learned from wearing a continuous glucose monitor and using the Levels app. So, Levels is a company that helps you in analyzing what's going on in your body. It's continuous monitoring 24 .7. I wear it all the time. It really helps me to stay on top of the food I eat, remain conscious of the food that I eat, and to understand which foods affect me based upon my physiology and my genetics. You know, on this podcast, I only recommend products and services that I use, that I use not only for myself, but my friends and my family, that I think are high quality and safe and really impact a person's life.

18:30So check it out, levels .link slash Peter, give you two additional months of membership, and it's something that I think everyone should be doing. Eventually, this stuff is gonna be in your body, on your body, part of our future of medicine today, it's a product that I think I'm going to be using for the years ahead and hope you'll consider as well. I mean, there's so many other things that have changed in the world that allow us to do rapid experimentation, like, you know, basically being able to launch a website product even before it exists or go out with Google search terms and see whether people will search on your term or you can describe in offering, get people to the credit card page where they would click to buy and say, I'm sorry, this product is not available right now, but when it becomes available, we'll let you know.

19:22Thank you for your willingness to buy. I mean, you can run virtualized experiments on virtualized products and get the data to the point where, you know, I'm pretty clear this is going to function. We talked about this in the last episode a bit, but it was worth restating Kickstarter. Yes, a lot of Kickstarter. Crowdfunding means that for the first time in the history of business, you can get market validation for a product before you build a product. That's just unbelievably powerful to getting an idea to market, especially for consumer facing products. I think this is where this entire time, even think about the idea that the evolution itself operates on an experimentation basis.

20:02Right? We throw out GM mutations and you see what works and those for survive by natural selection. It's the most fundamental archetypal process in life. And so you have to be able to build that deeply into your business to succeed properly, especially in volatile world. So if you're an entrepreneur starting a company or you're in a company and you're managing a team, one of the things I you know, be seated you to try is building a culture of experimentation that constantly be describing experiments that you're going to run, what you're looking for as the answer, and then run those experiments.

20:42And at a minimum, it's the subject line of the email that you're sending out. At a maximum, it's like, let's come up with 10 variations of the business and try an MVP in some of those and see what actually works. MVP for those unfamiliar is from Lean Startup, was the minimum viable product, right? What's the smallest set of features that get it out there and allow you to test and iterate? When we were building products at Yahoo Peter, I remember cattering up, we brought cattering effect to come in and she was the founder of Flickr. And she would say to the teams, okay great, you're building this product with 20 features, fabulous.

21:17It's gonna take you two years. Give me the two features that we're gonna have to succeed. Which are the two out of the 20 that go, oh this and this, she go great. Build those two, show me that the product succeeds at all and then iterate and add the others rest. Don't wait till you build 20 features before you get out there. You may fail. So that's essentially the birth of the entire idea of MVP. Critical idea, you take the smallest feature footprint, get it out there and iterate very, very fast. Yeah. I mean, what you're battling as an EXO is what I'd call the tyranny of confidence. Like, you know what the right answer is and the reality is you don't.

21:55And you've got to be running these experiments. And it's easy for a startup, especially at T equals zero, in the culture for you as the founder or founders to say, just, you know, every time you're meeting, it's like what its experiments were running, what are the variations were running, what's the data we're collecting, and just getting into that mindset of rapid experimentation. If you're a large company, and you're dealing with a tyranny of confidence, the tyranny of of a seniority, you know, which is a problem. It's a huge issue. I love that phrasing term of confidence. You know what solves that is the is the dedication to the MTP, right?

22:40If you're if you're really trying to solve that problem, okay, it doesn't matter how many times you fail, it doesn't matter. You just keep plugging away at it because you're so emotionally excited and connected to the problem space. So let's talk about experimentation in large companies. I mentioned the idea of a large company running these 555 experiments. It's unleashing. You never know, and one of the important things here, is you never know where the breakthrough idea is going to come from. You think it's going to come from your head of engineering or your, you know, but it could be the person in literally the production, the mail room or the executive assistant who happened to put two or two together.

23:17It's typically again a crazy idea. It's not coming from your normal sources. So how do you tap into the wealth of knowledge inside your organization? This is the hardest thing for big companies to adopt because big companies don't tolerate failure. It's what we call a CLM, a career limiting move. You fail, you're done. That's the basic ethos. So people stay keep it safe and they never test an experiment. And this is the hardest cultural paradigm to shift. That's why you have to build the company as an EXO to start or start EXOs at the edge in order to do this. You have to, and you can turn it into a game, you know what Adobe did that was really successful?

23:57They gave every employee a red box issue box with startup instructions and a $1 ,000 check. They said, if your manager won't let you build some feature or some product that you think was rebuilding, here's a $1 ,000 school build, it go higher, some developers in Estonia, or India or wherever and start building that. So people got together pooled their red boxes, got together 10, 20, 30 grand, and started building features. And it turned out something like 50 % of Adobe's revenues three years later came from those red box programs. It's crazy. It's like, crazy. If you let them go, you know, I'm Google talks about this as their 20 % time, right?

24:34We yielded Gmail. 3M I think is the most legendary. They would give their researchers 30 % time to tinker and play. I think in today's world it's got to be 50 to 70 % of time. Like let people just play around and you'll find those results are where things work. One of the other places you can go to get great ideas that you might not think about is not inside your organization, but it's the community out there. It's your customers and people who love what you do, what you stand for. Well, this is where community and crowd are so critical as elements, right? If you can run experiments in the community, it gives you a free place to test things and then you bring them in.

25:17And you've given an example before of actually going out to the community and saying, what features should we add? What product should we create? Yeah, this is Chris Anderson doing DIY drones did this. You know, 300 ,000 people that are drones enthusiasts. When they want a product, they just go, what do you guys want? And they go, oh, we want to DIY kit. Great. That drives your product development. And And I think successfully running and asking the community or getting your community to run experiments and sourcing that back in is essentially the future of most products going forward in the world.

25:50But in order to run an organization that is that experimental, it's got to be agile, it's got to be data driven. You have to be able to actually collect the information, measure it, and make decisions based upon the data. There's some critical cultural prerequisites, right? You have to have the culture allowing failure You have to have an MTP by the way So and you have to have the third one you really need will talk about this in another episode is autonomy You know GE worked with Eric Reese and they ran the biggest corporate training exercise in business history They trained 60 ,000 managers on lean startup, okay, and it failed and it failed why because they didn't have autonomy They were expected to experiment only in that particular domain, which blows the reason for experimentation.

26:39It's antithetical to experimentation and play and tinkering. And so there's some prerequisites. It's not an easy attribute to put into legacy organizations. Maybe one of the hardest, but it's the most critical. You know, it's interesting. I was just on a board meeting yesterday of Vatem, which is Eric Polier's company that that creates these extraordinary metaverse experiences. And they've built the tool kits that allow people to build on top of their platform. And the stuff that was coming out of it, it would have, you know, the company's relatively small engineering staff and what these other companies were building was crazy, right?