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

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Edu Some people think nature is like this, but actually it's like this. That's why Columbia engineers everything we make for anything nature can throw at you. Columbia engineered for whatever. You 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 a volatile world.

So if you're an entreprene starting a company, one of the things I beseech you to try is. Welcome to our next episode of Moonshots and Mindsets. I'm here with my dear friend Salim Ismail, my co author of our newest book Exponential Organizations 2.0. The first CEO of Singularity University. Saleem. Let's talk about one of my favorite subjects of an exo, which is experimentation. You know, 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, you know, 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 and a service. But before we get into that, my friend, would you refine define what is an exponential organization?

So an 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. We found that we looked at the fastest growing unicorns and teased out the model. So we're not inventing something, we're putting labels on what already exists and exos delivering typically 10x better, faster, cheaper than its 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. 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. This just blows your mind. As the external world becomes more volatile, your ability to adapt is going to 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 multibillion dollar conglomerate global companies at lightning speed. So we talked 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 and experiments are, you know, they cross both. Right. You can run internal experiments and external. I'll mention this, you know, I have an external, an EXO, my PhD ventures that manages a lot of my companies and products and I am constantly just demanding that the team be running experiments. And it's like one of the things I realized is a lot of companies that are being born today, these are startups by entrepreneurs started today, are born with a culture of experimentation from the very beginning. They're running experimentation versus the old school which was, you know, in the old school companies you would hire a consultant to tell you what to do and that consultant had over time built a model in their mind and you were paying them for their, for their knowledge. But that's just broken right now.

It's completely broken. And this is a really key point. That's 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, the head of supply chain for BMW. It's 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 type of a car and you understood okay, if the bit of a recession, what suppliers do I go after, et cetera. And you rose in prominence over usually by seniority and having deep intuition about that domain space. Yes, intuition is 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 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 of the outside world is constantly running experiments, testing the outside world. You 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 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 to react to. And it's only when you run these experiments do you find yourself evolving the product rapidly. And there's 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.

Exactly. You know, I got a little story here. When I was at Yahoo, we came across this because a B 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, let's see what the responses. And you have hard driven data as to what works. On 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 it to eight, the click throughs 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 ab testing and trialing and experimentation, that number works. So you go, okay, it works, you go with it, but you have no idea why and how. And that's the thesis of the external world. You 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 you'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 tinkering. Right? Can you just get in? Bang. Just play. Let Your people just play with stuff and interesting things will happen.

A quick break from our episode. On June 6, Salim and I are going to 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 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. It's June 6th, it's three hours, it's free. We've never done this before. Click on the link below diamandis.com EXO and join us. All right, 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 1,000 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 you know, executive assistant, like different groups, it's not all engineering or not all marketing. We're going to give you a $500 budget. We want you to go and experiment out there with designing new product or service. It works really well in the digital world. 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. It would be an incremental improvement. And so if in fact breakthroughs require experimenting with crazy ideas, you know, when I'm in the boardroom or I'm on stage like you are, I say, where's 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, you're stuck on incrementalism.

You know, Amazon in fact actually measures this down to that level. They've asked 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 are failing, your bonus gets dinged. Right, because you're constantly pushing the learning of the organization. And a whole. Not by accident. Is Amazon one of the biggest companies in the world?

Yeah. Jeff Holden, who is a friend. I haven't seen him in a while, though, unfortunately. But Jeff was on my board at xprize, 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. Thing was called Morpheus. Morpheus, yeah. And they were exactly doing that. It was like they're running thousands of experiments. I remember Jeff Bezos, I quoted him, said, the success of Amazon is a function of the number of experiments we run per year, per month, per day. Because we actually, as humans, are biased, but we don't know what works until you try it. Until you try with check writers out there.

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 Gutenberg 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, your senior executives, based on their intuition, would go off and hunker down and come up with a strategy, and 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 making, doing sense, making in that way, seeing what works, and ruthlessly following that, even though it goes against your gut, that it might say goes against your experience, goes against your intuition, just ruthlessly following that. Eric Reesk talks about this as a startup being an experiment, looking for a business model. Right? 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 tinkering. Okay? Larry and Sergey playing with algorithms, and 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 Holden, Jeff Holden was telling me 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. In hindsight it looks so obvious, right? And at the time it looked like a crazy idea, just as you talk about. And you won't find them unless you have that culture. What I think is one of the most powerful developments today is with the rise of ChatGPT and Auto GPT and some of the generative AI capabilities, we can now train AIs to run those experiments and even conceive of those experiments. So you should be kind of going, hey AI, go run 1000 experiments on this domain and figure out what works.

Yeah, we're getting there very quickly. And one of the companies out there that's one of probably the great experimenting companies of our lifetime is Google. And Google not only 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 as 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 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 do you keep all the companies you're experimenting with secret? And 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, Right? 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 into another idea and make.

Sure you trap the learning. I may have some small part to play in this. Peter. In 2010 we had a singularity event. Larry Paige was there. Remember he came and spoke at the closing ceremonies and he grabbed me at the reception afterwards and he said, hey, your brick house unit Yahoo is really great. Should I do that at Google?

What did you say?

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 meant we couldn't fail. I said, keep it stealth and pointed into adjacent areas. And now 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 10 reasons that this might fail? It's a really important heuristic.

It's called a pre. Mortem. So we all know what a post mortem is. After a project has failed or product or service or company, you look back and say, okay, why did it fail? And he said, what we do is 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, for me, these ideas of a pre mortem are what I loved.

About that approach was they take the biggest reasons why it 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 just work your way 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.

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We talked about this in the last episode a bit, but it's worth restating. Kickstarter.

Yes, I love 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. Right. That's just unbelievably powerful to getting an idea out to market, especially for consumer facing products. And I think this is where this entire think about the idea that the evolution itself operates on an experimentation basis. We throw out gene mutations and you see what works and those 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 a 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 beseech 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. And at a minimum, it's the subject line of the emails 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 Starter. What's 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 Katerina, we brought Katerina Fake to come in. She was the founder of Flickr and she would say to the teams, okay, great, you're building this product with 20 features. Fabulous. It's going to take you two years. Give me the two features that are going to have it succeed. Which of the two out of the 20 that go, oh, this and this should 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 that 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. And 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 experiments we're running, what are the variations we're 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 the tyranny of confidence, the tyranny of seniority, which is a problem.

It's a huge issue. I love that phrasing tyranny of confidence. You know what solves that is the dedication to the mtp. 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. 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. But it could be the person in literally the production in the mailroom or the executive assistant who happened to put two or two together. It'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, right? That's the basic ethos. So people keep it safe and they never test and experiment. And this is the hardest cultural paradigm to shift. That's why you have to build a 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? They gave every employee a red box, a shoebox with startup instructions and $1,000 check. And they said, if your manager won't let you build some feature or some product that you think was worth Building, here's $1,000, go build it. Go hire 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, crazy if you let them go. You know, Google talks about this as their 20% time, which 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, right? It's your customers and people who love what you do and 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.

And, you know, you've given an example before of actually going out to community and saying, what features should we add, what products should we create?

Yeah. This is Chris Anderson doing DIY. Drones did this. You know, about 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 a DIY kit. Great. That drives your product development. 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.

But 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, and you have to. The third one you really need. We'll talk about this in another episode, is autonomy. You know, GE worked with Eric Ries, and they ran the biggest corporate training exercise in business history. They trained 60,000 managers on lean startup. 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. It's antithetical to experimentation and play and tinkering. Right. And so there's some prerequisites. It's not an easy attribute to put into legacy organizations. Maybe the. One of the hardest, but it's the most critical.

You know, it's interesting. I was just at a board meeting yesterday of Vadim, which is Eric Poulier's company that creates these extraordinary metaverse experiences. And they've built the toolkits that allow people to build on top of their platform and the stuff that was coming out of it. The company's relatively small engineering staff and what these other companies were building was crazy. Right. So it's like Roblox as well. Roblox offers a platform that allows other people to build games on top of. And so they get thousands of new games, and there's no way that the internal team could have built any of these successful games at scale.

Yeah. So this becomes incredible. If you can build a platform and offer tool sets to a community and let them build on top of you, then you're onto a total winner and nobody will unseat you from that because you're. You're the coral reef, right? And a million little organisms are running around building on top of your coral reef and adding to it as time goes by.

Hey, everybody, this is Peter. A quick break from the episode. I'm a firm believer that science and technology and how entrepreneurs can change the world is the only real news out there worth consuming. I don't watch the Crisis News Network. I call CNN or Fox and hear every devastating piece of news on the planet. I spend my time training my neural net the way I see the world by looking at the incredible breakthroughs in science and technology, how entrepreneurs are solving the world's grand challenges, what the breakthroughs are in longevity, how exponential technologies are transforming our world. So twice once a week, I put out a blog. One blog is looking at the future of longevity, age reversal, biotech, increasing your health span. The other blog looks at exponential technologies. AI, 3D printing, synthetic biology, AR.VR blockchain. These technologies are transforming what you as an entrepreneur can do. If this is the kind of muse you want to learn about and shape your neural nets with, go to dmanandis.com and learn more. Now back to the episode. So we just to wrap this up, I want to just bring back how all of these exo internal and external attributes work together. So we've been talking about experimentation here. And experimentation works when you've got access to, first of all, AI and algorithms to help you analyze the data you're experimenting with. The second is you have dashboards that allow you to measure and track which experiments are working and which are going in the wrong direction. Because if you're building an exo, things move fast and you need those dashboards to be live and visual to everybody involved. Autonomy, like you just said, to allow teams to go off and try crazy ideas because if they can't have the autonomy to try to follow their gut and try things out, then you're stuck. And then we talk about community and crowd, which is you can tap the community and crowd to help generate ideas for you, and then engagement for you to able to like, engage them, incentivize them to play these games with you.

And then the MTP becomes the guiding directive thing saying, okay, this is the direction in which we're going. You know, if you look, think about your X prizes, Peter, right? Super proud to be on the board. And the way what get me so excited is you have a huge problem like curing cancer or fighting wildfires, right? And then you're essentially allowing the entire world to run experiments and win an incentive prize as a result of that experiment. I think XPRIZE has learned how to run experiments at scale in the crowd, at a global level, unlike any other organization in the world.

Thank you for that, and I'm very proud of what the team has done. I think it's important to realize that MTP as the guiding light. And we come back to that again. And I think everybody here, please, if you're an entrepreneur, if you're running a company, even if you're running part of a company or for yourself or for your family, having a massive transformative purpose that helps you decide what to do and what not to do. I'll go back to that quote from Martine Rothblatt where she said, listen, the difference between successful and very successful people is successful people learn to say no to a lot of things. Very successful people say no to almost everything. They're focused. Right? And if you're running experiments inside of an organization, you want to make sure that your experiments, if you're a coding company, don't take you into making shoes. I mean, it's like, what's your purpose in life? And running experiments that all are marching in the right direction because you might find yourself in a business area that you don't care about anymore. And money is not a reason to be making a business work. It really is to make a difference on the planet, and money comes along with that.

You know, I've. I struggle with this because I get excited about so many things. I'm terrible at this. The focusing and the narrowing down. I'm like, oh, let's do that. Ooh, let's do that. And then you end up chasing a ton of butterflies, and you're not effective at all. So, yeah, the MTV becomes critically important to kind of keeping yourself on the. On the. On the rails.

All right, buddy. Well, this was fun. Again, just to echo, experimentation is something you can now do. It wasn't something easily done even 20 years ago. But today, experimentation is table stakes. And your ability to use AI, to use the crowd, to be running experiments is fundamental to being an exponential organization. Because your intuition may not be what actually is the best decision for your product or service.

An easy thing to try. Go to ChatGPT and say, here's my company. What experiments should I be running? Just run some iterative queries on that. You'll find something, some amazing things to test and try out. Pricing models, customer interaction, behavior changes, et cetera, et cetera.

All right, pal, Good to have this conversation.

Great.

Excited for exponential organizations 2.0 to make a difference in the world.

It's a big experiment.

It is.

Sam.