Reducing uncertainty is one of the CEO’s key roles. In building and selling his first company, Matt recognised that besides hard work, there was a fair amount of luck involved. In starting his second venture, he decided not only to try and reduce his dependence on luck, but to equip as many entrepreneurs as possible to do the same.
Drawing on his research, his experience, and physics Matt explains strategies and techniques CEOs can employ to spot patterns and trends in order to reduce uncertainty and get better at predicting strategic outcomes.
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Okay,I’m Matt, thanks for the intro, I didn’t hire somebody to replace me in the last company didn’t leave them headless. So that’s that, that story can share it at lunch, can you predict your company’s success, I have to say that I did not pick that title. I thought we were going to talk about forecasting and kind of moderator expectations a little bit. But I feel like it’s a little bit of a setup now, because I have to make you guys not sceptical about predicting things. And these are startups. And you guys are largely engineering minded. And you’re gonna say it’s, it’s impossible. But what I hope to do for you today is reduce the amount of luck that you’re depending on for your business.
I got very lucky the first time, I resonated a lot with Patrick’s talk, that initial period, I started learning Python, to write software for my first company, which was called risk pulse. When my daughter was one, she’s 15. Now in in the audience, and It’s been a very long time trying to get that off the ground. And finally did, but it was, as you’ll see later, through a lot of what people call insanity, it’s like hitting your head against the same thing over and over again, expecting it to move and kind of ignoring your injuries. And I don’t want to have to get that lucky again, right? I want to – as much as possible – look at the world and say, are trends on my side? Or if you don’t like living coral? Are macro factors on my side? And then also, do I understand what’s going on inside of my business? Can I forecast what’s going to happen next, predict it and get ahead of it.?Because I don’t want to depend on luck. And I don’t want to take as long and ultimately I want to equip entrepreneurs.
So my talk today is going to go pretty deep into domain, this domain of forecasting. So we’re going to nerd out quite a bit. But I hope to leave you with a technique to think about how the market is changing for your business. And also some new ways of looking at your business within that market. And so we’re going to kind of frame that around this world of physics. So I said, How can I help people be a little less sceptical of this idea of fortune telling? I said, physics, yes, these these laws that we can’t escape, even when we’re starting businesses. And there’s this growing body of evidence that startups actually do obey, and businesses obey something like physics. And there are certain laws that are really hard to escape. And people that are focused on growing, start to realise these things when they hit these plateaus, or they hit these inflection points. And we even use words that are very laden with physics, like, you know, leaving a dent in the universe. For example, we always talked about that our founders have a reality distortion field. And it’s like, seems like physics is always a thing to reach for, we’re looking for a metaphor to describe what’s actually going on in this magical land of startups. So I want to talk about macro physics. And I want to talk with micro physics starting up. And for the macro side, to turn to a person that you guys completely respect, I hope and talk about, what I would like to say is a fundamental force behind the landscape that you’re in.
So what kind of whatever business you’re in, you’re in a market, and your might be one of those markets with the 5000 companies in it. But if you think about your customer and their needs, and kind of reduce it down to these fundamental forces, and I’m gonna use that as an extended metaphor, and if you don’t like that, there’s also the fundamental force, which I learned, apparently, the guide Industrial Light and Magic did have a poster of Einstien on his wall. And I’ve probably ruined Yoda for you. But this is that was his inspiration. And the reason we want to talk about fundamental forces is we want to think long range for once. And I say for once, because it’s really easy to just live in that cycle. I love the the freakout cycle of day to day, you know what’s going on? What am I reacting to. But as leaders, we want to think long range. And we want to able to plan ahead, and I really believe that that is possible. While you have to stay adaptive and responsive to what’s going on the environment, you can plan long range. And I think physics has great examples of this. So like, apparently, we can count on physics to go somewhere between 34,million – 250 million miles away from Earth at some point. And some people who trust in physics will get on these ships and do that. And if anybody signed up for that yet, but I’m going to see how the first one goes. And then maybe, maybe, maybe try out the next one.
So we can count on these things. To work, and I think of it as inevitability, so put this ball at the top of this and rolled it down. None of you have a problem believing that that’s going to happen, right? We figured it out. It’s inevitable. And I want to talk about at the beginning, what is this idea of inevitability, and what’s happening in your market, that you would point out and say, at some point, this is going to happen, right? So let’s, let’s talk about what’s inevitable in business. I’m gonna think, long two dimensions here, but I’m going to give credit where it’s due. Simon Wardley, know if you any of you have heard of him, fantastic business strategist and thinker. He broke it down in kind of two ways. Here. First, things always go from novel to commonplace. So things get invented, things transition into products and services that we use, and then eventually they become commodities. Right. And this is inevitable flow of progress that I don’t think any of us would argue with, is happening constantly. And the other one is, and this one drives some of us mad, but perspective affects value perception. So people, your customers, and different members of the industry, are always going to look at value differently, depending on their perspective. So there’s a relative relativity, if you will, to value perception. And you can actually take these two and put them onto a classic y an X axis, we’ll put on the y axis, we’ll put perspective, that’s that perception of value. on the x axis, we’ll put evolution that’s that inevitable flow of progress from zero to n.
And also, as you move along, couple other things happen as things evolve, what happens things go from being invented in someone’s garage, or basement. And the market size for that product as it grows, or as it gets successful, grows as well. So commodities on the far right, have huge markets, right – power, oil energy. Acceleration also occurs as you go from left to right. So things take less time to go from the Newton, for example, which did anybody have one to the iPhone, right, but then ultimately, to the place where smartphones are ubiquitous, that actually took less time. So as you go from left to right, things accelerate.
So let’s take an example here, let’s look at photography in 2009. And if you think photography today, and we played a word association game, your brain, probably or some part of it goes to Instagram, but 2009, there was no Instagram. So if anybody can remember way back then, let’s talk about what the user needed for photography in 2009. We’re gonna map it on the y axis here, things that are visible to them to things that are invisible to them, but still things that they need. So there’s a photographer, this user, ultimately, they may or may not want to print, they might want a digital print, or they just might want to store it online. And these are things that they, they would say, if you talk to them, right? They also might want to take that image and do something with it, they want it, they want it to look great, right? It’s not enough just to have a photo, you never have to edit it and manipulate it and change it. And then somewhere in the back of their mind, they’re like, yeah, I need a website or an application for that to happen on right. And this is still pretty new in 2009. And then there’s kind of his waterline, where to them. What’s beyond that, as far as this needs, dependencies, dependency of needs is kinda invisible, right? So now, somewhere, that website needs a CRM, right? It’s resting on top of that, to host all these photos and to do the work for the user, right. And they don’t really care about that, right? But it’s needed. And then the CRM probably needs to be on some hosting or some platform, there’s computing that drives that. And then there’s power that drives the computing, right? So you have this vertical stack of all the things that a user actually needs, or you need to provide to the user for them to achieve their their goal of having a great photo online that they can share with their friends and family.
Now, let’s also shift that along the x axis and say, Okay, this is their perception of value from top to bottom, they would say the most valuable thing to me is a great print. If you said, Hey, by the way your prints are created with renewable energy, they’d say, interesting. I don’t know if I care as much as I should, maybe I should care more. But you can see that ultimately, what matters to them is how good the print is. Now let’s also take all those dots and cascade them along the x axis, and talk about where is each of those things relative to its kind of beginning of life cycle to the middle where more people are catching on to is going mainstream, and ultimately to the place where it’s a commodity, right.
So in 2009, online image manipulation was still very new. I was creating graphics online 2009. And I use this action technology called Macromedia Flash. And it did great things. It was good for what I was good for. But we were a long way from having something that was great online for editing photos, online photo storage, Dropbox was brand new. I’m not sure if Google Drive was out then but I know that we had things like flickr. So that was just Entering the product phase, there were web platforms where you could host things of course.
Digital prints, the idea of taking digital photo and printing out at home was not as new that had been around for a while, websites were old by now are growing into the commodity space. CRM is computing power, so forth, right? So you can look at this and say, Okay, we have this user. And these are the things they need. And we can actually connect those now and say, What does the user need?
Well, they directly need to manipulate that image online, they need to print, they know they need a website, and then you just store it somewhere. And then you have that waterline, right where well, the website needs those other things. But that’s not as visible to them. But it’s important if you’re a business providing for this user, you’re thinking about the whole stack.
So now, let’s go to Instagram. So it’s really interesting that Instagram is that in 2009. Kevin Systrom, is travelling Europe, and he’s taking photos. And as the story goes, he noticed that all these cool photos are being taken with these cameras and these other kind of old fashioned cameras. And they produce these just really interesting prints. And they were always interesting. And people would look at the photos and say, Wow, that’s, that’s an interesting photo, that’s really cool.
And out of left field, essentially, the idea came that you know, what actually matters to the user is creating interesting photos that people actually want to look at and share. Because ultimately, the goal is to share an interesting photo with friends. Instagram comes along and what essentially happens is it collapses that entire value tree, if you will, all the way to the right. So it takes what was novel, right, this idea of having flash and editing pixels, and oh, gosh, I need to adjust the blackness levels and the alphas and contrast and all this stuff. people doing that work to say, No people just want a button where they can make it look old fashioned, right. And real photographers may scream in their brains at that. But I think Ansel Adams would loved that actually. And ultimately shifts this entire thing to the right. So in 2012, this is a three year period, inevitability catches up, and somebody positions themselves on the left hand side of that graph and a huge amount of gravity essentially gets created, and it draws everything in.
So what’s that platform now it’s actually Facebook. Prints now is a thing that you can actually go online, and you can buy prints of your Instagram photos, right? And your all of your best photos. Well, for me, at least are the Instagram ones, like the ones that actually took the time to edit and put out there are the ones that I’m most proud of. And now there’s suddenly is this just orbit of photography online or on Instagram, right?
So I want to talk about is this idea of inevitability that this market, this desire to have photos online, it was there, right, and the market wanted to be fulfilled, and it will be fulfilled by the first viable product that comes along. And that was Marc Andreessen, his famous blog post on product market fit. And I liked that definition because it says it will be fulfilled. So there was this need for people to edit their photos online. And there was this bottleneck and Instagram solved that bottleneck by pushing the boundaries of online photo manipulation, storage all the way to the right.
Now, just to sum up, and then we’re gonna apply this technique to another industry, which affects all of us – startups. Macro predictions is about perceiving, overallchange and you can take your business and you can plot it on those axes and encourage you to do it. And it can reveal some interesting things around inevitability. We’ll come back to that in a second. Second thing to talk about is predicting things at the micro level. And the first way to think about predictions at the micro level, meaning your business within that larger universe of the industry, is calculation. And to learn a little bit more about calculation, we’re actually gonna do a brief history of forecasting.
The Royal Charter in 1859, was a ship, it sank. Many people died and the Admiral Robert Fitzroy, in the United Kingdom, was distraught about this and all the death and loss that was occurring to the Navy and the fleet’s and said, There’s got to be a better way of doing this and he started to take measurements of the weather. A lot of people thought he was crazy, actually, because they really believe that it was impossible to predict the weather in 1859. And yet, he was undeterred. He said, No, there’s there’s science to this, there’s actually predictability involved. And I’m going to chart these measurements and to take measurements of the coast. And what I’m going to do is I’m actually going to send that information as fast as possible to the other side of the country. And so kind of an interesting twist that the first forecasts were actually just those the electric telegraph. And the electric telegraph enabled information to travel faster than the weather. So the original weather forecasts, were actually just somebody noticing the weather, saying, there’s wind here, and then hitting some buttons and sending the information that there’s wind here faster than the wind. Literally downwind to somebody else who then get a weather forecast or prediction that said, it’s gonna be windy. And then yes, the wind hits them, right.
And there’s so much I could go into about that, because this actually isn’t how so many things work. But save it for lunch. The breakthrough here was speed and extrapolation. So the idea was, we can just take a measurement, and we can extrapolate logically what’s going to happen next, we can send that information on. And we can say, Well, clearly, you’re gonna experience this. Now, the state of the art before this was actually the behaviour of farm animals, and frogs inside jars and all kinds of crazy stuff. As far as this is what’s gonna happen. Now, we’re all laughing at that to some extent. But if I told you that your business forecasting was often predicated on the behaviour of a single customer cancelling, or a certain upsell occurring, or these kind of, you know, things happening in your environment, suddenly we hit a lot closer to home, you’re like, no, now we use data. And we predict things. And that’s how we know that things are going to happen to our business. It’s like, we’re more anecdotal than we think. So let’s talk about this speed idea for a second. And this just blows my mind.
So this is called the weather forecasting factory. It’s a painting or illustration by Steven Conlon, about 50 years after that first weather forecasts, casting started to occur – thanks for the Admiral – this mathematician and brilliant person, by the name of Lewis Fry Richardson. Also in the UK, early 19 hundred’s said, You know what? This weather forecasting and things actually kind of make sense. And by the way, there’s physics attached to it. There’s these governing equations. So you know, mass has to go somewhere energy has to go somewhere, the sun heats things up. And, you know, what if to do a weather forecast, we actually had, and you can see, this is a, this is a map. So this is Florida. And you know, here’s the UK, and this is map here. So what if we put all these people into a room, and we divided all of the parts of the earth into little squares. Now we had people at these desks and you see there’s a guy in a ladder there, right, and he’s got a certain job, what they’re actually doing is writing equations, into each of those little cells. And then that is the weather for that little part of the world, right. But then that affects the next cell over next cell over next cell over. So what you could create, and he estimated he’d need, well, this is actually a sad, this is when he realised wasn’t going to work. He’s how need 64,000 people doing this math all the time, just to get a forecast. And it would take them 24 hours to do once around the globe. And that would actually forecast the weather 24 hours in advance. So by the time they finished, they would know what the weather was today. Slightly discouraging.
But amazing idea. And it turns out that this idea actually became the foundation of the weather forecasting. So if you, if you look at other weather forecasting model, what they actually are doing is they are carving Earth up into a grid, each grid has certain equations, we now have super key. So it wasn’t until the ENIAC computer, that they could actually run the math on the entire Earth, these same sets of equations, but they could run over the entire Earth, I think it took took six hours to run, and it would give them a forecast for 12 hours or something like that. So they could finally give you like a six hour weather forecast. But all it was is was collecting the data in one part of the earth, running the numbers, and then faster than the Earth essentially could catch up sharing those numbers with everybody and saying, right, this is what you’re gonna experience next. And if you think about a hurricane forecast, which near and dear to my heart, that’s essentially what you’re seeing, right? Here’s the storm, it’s going to go here, hey, you people over here. This is what’s coming, right? And we call that a forecast.
Now, it’s silly to imagine that we would have hundreds or 1000s of people just looking at a grid all day and running equations inside of it, right? I mean, who in the world would actually just have a bunch of people sitting there all day running equations through a, you know, a big system of some kind, and then passing their notes along to each other and actually trying to forecast things? I mean, that would be that’d be ridiculous, right?
But that is the state of the art that we have in business today. It’s essentially we have a bunch of math and equations and you know, MRR Arr, ARPU, LTV, etc. And we’re essentially passing those around, we have this forecasting factory, which is a bunch of spreadsheets, right? So I want to use that absurdity for a second to say, Okay, this, this, inevitably is going to change, right. And I think when this changes the same way that it became an assumption that you can actually predict the weather and fly because you know, the weather or make life, you know, life critical decisions, because the weather I think that forecasting business will also change. And I think when it does, I think it’ll affect every single one of us in the room and I want to talk about why.
So let’s use the seeds the technique that we had earlier right and talk about early stage financing. So funding was mentioned earlier, bootstrapping, very polarising topic. I think that’s part of the fun. But I’ve raised money. I’ve also bootstrapped. I bootstrap, and then raise money. And I think about it this way, right. So you have the customer with, who is the founder, founder just needs cash. Right? Primarily, they’re hoping for some kind of liquidity that’s important to them as well, which means exit, cash out, etc.
The investor brand kind of matters sometimes depends, if you care about being in TechCrunch, or being able to brag to folks about it, there is a pecking order in people’s minds of who you raise money from, the investor themself may or may not be as important as the brand, then you need a bank to store the large piles of cash. You need terms that the money was accepted on, that money has to come from a fund. And ultimately, you have to have what are called limited partners, which are the people who actually invested in the fund so that that can all flow back up to the founder.
Now it scattered out across and connect the dots. So these days, we have liquidity is this rare thing that is still custom- so it’s not exactly a product, some people are trying to productize it. But this is the rare thing that a lot of people are searching for in their founder life, you have cash, which is a total commodity sitting out over here, a bank to store things. And then you have investors sitting somewhere in the middle. They’re not products yet, although we can talk about maybe getting them there. Terms, they depend on terms diligence, financial aid, this is essentially a dependency map of early stage financing. And if you’re the founder, all you’re really thinking is how do I get cash into my bank account? How do I give the investor the information that they need? And how do I find that investor as fast as possible?
So this was 2007. And this is actually when I started raising money for my first company and alot’s changed in the last 12 years. So let’s talk about that. So in the last 10 years, there’s been this inevitable flow of progress. And what’s happened is terms for early stage financing have shifted way towards the product side. So seed funding, convertible notes, the idea of pre seed funding, I mean, there’s more talk now about seed funding than there is any other stages because terms are becoming commoditized mean productize. So you can actually go out now 2007, you couldn’t go out and just find a standard set of terms to raise money on right, now you can actually google online and say, you know, I want to fundraise a series A you can go to Y Combinator and you can actually find their series A docs, and they encourage their founders to use those. And suddenly, there’s an almost a interchangeability right to those terms, there’s an expectation that people will work with you on those terms, which wasn’t the case before.
The other thing has happened is that financial data has flown all the way over here. And when I say that, I mean that it’s essentially entered the cloud, right? So if you look at profitwell, and the other 34 competitors, etc, QuickBooks moving online, all the data that’s used to make financial decisions, or early stage funding decisions has also gone from offline to online. And that means that it’s much more of a product, you actually have expectations around formats, we are trying to measure things in a pretty standardised way. I mean, Patrick talked about 25% of the subscription economy is in profitwell, which actually means 25% of this subscription data is normalised, standardised, which is a huge shift.
And we also have diligence, which is move slightly down here, diligence, essentially, you know, investors deciding if they’re going to do a deal or not. And this shift and this shift, are really fundamental. I want to talk about why.
So the investors who are kind of still sitting here, have responded to this change in some extent by saying, oh, but we have value add, right? So value add means is, we have people too. And we have things too. And even though you know, these terms are getting more commoditized and interchangeable. And you could go raise money on the same terms as from somebody else, we have this unique value add, right. So, you know, we have these operational people and marketing help and sales help, and we have all these things. And I created a dotted line, because we talked to founders these days. Not really sure if that’s actually value add or not, right? A lot of times it’s advice, and not actual help. And it’s I would just say it’s questionable, right? So this is this is part of the response to this shift in the landscape.
But things kept moving, right. So there’s this continued evolution where terms are now going farther, right and as evidence of that, we have the rise of quite a few industry changing financial products and companies. So this is the alt space, I’ll call it right here on the side. So they have alternative VC, which Thomson yesterday, raised money from all banking, who call it stripe capital just announced that you know if you have AR with them, you can actually get a loan against your accounts receivable. They’re getting obviously processed very fast by stripe itself. They’re essentially writing you a loan on very terms that are okay, right. But the beauty of it is the speed. And why is it fast? Well, it’s fast because they have all your financial data. So it’s very easy for them to look at your financial data, they don’t have to go into the startup forecasting factory anymore. And get all this information from all these people, they say, we actually know that you’re doing pretty good. And we’d like to offer you that $50,000 that you need on pretty good terms. And if you’d like to click this button, we can wire that to your account, actually, as well, because we’ve been depositing things into your account for the last five years.
And then, in addition to this, you also have what I would call kind of an all quants space. So lighter capital, revenue based financing, they will look at this data as well. And they’ll say, Hmm, you don’t need to dilute yourself, well, we’ll give you the money that you need to grow. And my question to us is, where’s the bottleneck? So if you think back to that Instagram example, where was the bottleneck here? So again, we’re looking at this world, we have all these things that over here have shifted to products, and in some cases, commodities. And then here, we have a similar world where we have a bunch of things that are essentially the product and commodity space, and they have a few things are still hanging out here on the left, right. So what we have is a bottleneck because remember, the demand and the usage of things over here is much, much higher than the things that are on the left. So websites, you know, 10, 100,1000 times more common than online photo storage, if we go back to our example, investor investors and diligence itself is on the left hand side of this box. And what I believe is going to happen is that ultimately, this is going to break. Because these folks want to invest at a scale that this cannot possibly occur.
So when you’re making 10, to 20 investments a year, but you’re able to fund 1000s and 1000s of companies, your little factory, essentially, this making forecasts, making diligence investment decisions, is essentially not keeping up with the earth, right? This is this is the equivalent of, you know, we can we can decide to invest in 10 companies a year. But by the time we decide to invest in those 10, there’s like another 100 that we missed that we should have invested in, we’re not keeping up with the pace of demand, which is what these folks are doing. So ultimately, I believe that we’re seeing a split in the market, where some set of worlds here will come together, and you’ll have a brand new orbit. Now, that seems to look crazy, but you’ve had eight speakers so far today. And three of those speakers have actually received investment from this side of this universe. So that would be myself. That will be Thompson, and actually spoiling it, but there’s another person speaking tomorrow, who will be the third. So this is happening, and it’s happening now. And the reason that’s happening is that this side, good news for BoSers is also much happier with real businesses than a profit, right. And the reason they’re happy with your business and make profit is because their business also depends on the profitability the businesses that they fund.
So this is a big shift. So this is a shift from investors looking for markup, and liquidity that they can pass on their LPs to investors are actually operating a lot more like banks who say, I just want an interest rate return. My IRR is dependent on your revenue, your profit, your success, I have your financial data, I can make an investment decision in 24 hours and give you the cash you need. And if you look at this diagram, the founder who’s sitting over here says I really need cash. And all this stuff over here is nice to have. But honestly, if I could just get the cash in my bank account, I could get going. And this is going to create what I think is another kind of shift in the market where there will be a kind of Instagram like orbit, I think stripe is wanting to be this large planet. Kind of own the internet subscription economy. But there are a lot of people who are obviously vying for it.
Now, again, this is an inevitability, I believe this tension can’t stand and it will be fulfilled by something. So kind of let that digest for a second and think, Okay, what does that actual planet or universe look like? Right, that new orbit? Can you give me some examples of that? So let me give you some kind of concrete examples of what that new world looks like and, and how I think it’s going to operate. And to do that we’re going to talk about this other subject called simulations. We talked about calculations, essentially running all those equations and whatnot through spreadsheet. I want to talk about simulating the future, which is what a modern weather forecast does.
So give you first step is replacing human computers. So I believe this is going to be outmoded very soon, if not already. And I think early stage investing for folks who are on the right hand side, not for the pickers who need to find the person that went to Stanford and, you know, you know that they’re gonna raise the next round in 18 months, and you’re all gonna be billionaires. But for the people who are actually trying to make decisions based on unit economics, and this kind of rational world, I really believe that the pace of finance and the pace of investing is going to look a lot more like kind of the public markets. But for folks, you’re trying to build real companies. And the nice thing about that is it’s going to be based on math, and not speculation.
So here on the left hand side, this is actually a startups revenue, right? This is a seasonal business. So you see kind of some fun stuff happening where there’s a seasonal trends. And turns out that you can do some really cool math on these kinds of things and create a forecast everything to the right of this pale grey lines are it’s so light, this is a forecast. And so if you’re a founder, and you’re kind of sitting here going, Oh, my gosh, life is amazing. And oh, no, it sucks again. And oh, this is amazing. And oh, no, you’re kind of sitting here around this time going, like, what, what is my future look like?
And I had a seasonal business, actually, my first one that was seasonal, so is based on weather. Turns out that winter weather is a really big deal. And summer weather is really big deal. And spring and fall are like, everyone loves the weather, right? It’s just like, it’s easy. People have problems, and I lived this cycle for 10 years. And it was feast or famine. And the challenge is raising money in a feast or famine, kind of business is really hard. Because people want to know, like, How much money do you need? And what’s gonna happen next? There’s really no good answers. But with the shift that we have, I think we actually can start provide answers for folks. And I think it’s going to change the funding landscape. So you heard about metrics in the last talk from Patrick, and profitwell, bearmetrics, chartmogul, all of this metrics data, is feeding into trends. And we can take those trends, we can actually do something better than just extending the future. So back to the weather example, you know, the admiral would take measurements, which is metrics, this is what it’s like here, he would send it to the telegraph. And you’ll get it someplace else. And you’re essentially just doing an extrapolation.
So how many folks have a forecast for their business today? Okay, how many of you would say it’s an extrapolation of the business for the last three to six to 12 months? Okay. Does anybody have something that’s much more sophisticated than that? Okay, great. So what you’re basically doing is you’re doing the equivalent of weather forecasting in the 1860s. Which is, it’s hot, it’s hotter, it’s even hotter. It’s gonna be really, really hot.
The problem with that is that complex systems don’t work that way. So if you think about something like seasons, which is what this is, you cannot just extrapolate what the temperature is going to be in October based on what temperature was in May, June and July, right, otherwise, would always forecast is going to be 450 degrees. At Christmas, it just doesn’t work that way, right. So what you actually need to do in order to make good planning decisions is you need to feed those trends, all of them, into a simulation. And a simulator, its job is essentially bring all those trends together and say, Ah, yes, your revenue is going up, and it has been going up. But you know, what’s also happening is your cash is going down. And because your cash is going down, you can’t hire another salesperson, and you’re going to have to stop investing in marketing. And when you do that, your revenues not going to keep going up at the rate it has been, you’re actually going to plateau. Right. And so the job of a simulation, which is what I’ve been spending the last nine months building one of these is to take all that data in and run it through a bunch of crazy probabilistic engines, decide what the randomness factors are, and all these different things and give you an answer.
Now, I had a fork in the road on this talk where I was like, I could go totally deep on this. And just geek out on how a Monte Carlo simulation works and all this fun stuff. But I said this is the BoS crowd, and missing an opportunity to talk about things that are more practical, but I still need to tell you what a simulator is like and what its job is. So I said, Hi, I know. simulator is basically a dungeon master. The job of a simulator is to do two things, right? And if you don’t get this reference, I’m really sorry. Okay, ask the person, the person chuckling next to you ask them what this means at lunch, and you’ll learn more than you ever wanted to know about their childhood, but it’s a game. It’s a game, okay? And those are dice and you roll the dice and things happen, amazing things happen.
Okay, so the job of a dungeon master is essentially two things; One is to enforce constraints, And the other one is to choose the dice. So you play this game, you say, Oh, I want to do this, the Dungeon Master says, In order to do that, you’re gonna have to roll a D 20. Now a D 20. is a 20 sided dice right to do other things. You might have to roll a D 6 or a D 3, or the weird pyramid shaped ones, right? And essentially, what’s happening inside that game, that simulation, Is that the dungeon master who Stranger Things, he’s essentially telling you to calculate the probability of that happening, use this kind of factor, right? So one out of 20 is a D 20. one out of six, and so on and so forth. Now, inside of simulation, you can get a lot more complicated distributions, right? So uniform is essentially it’s all weighted equally. But in the real world, you have weighted dice, right? So sometimes you roll a dice and just keeps coming up the same in a biassed way. And so not all dice are the same.
And then there’s constraints, right? So I talked about this in my lightning talk last year. And I want to cover it again in a little more detail. So in thinking about how to build something that kind of replicates what goes on in a startup world. I wanted to go back to the fundamentals and the basics and say, Okay, what are the things that we come to these kinds of conferences to talk about, right? We are all facing these constraints, which is, our sales reps have a finite capacity, right? The spreadsheet that we build doesn’t acknowledge that at all, it’s like, John’s gonna keep closing deals and closing deals, because he he’s gonna carry 1000 opportunities at once. And he’s gonna close all these deals. Now, we’re not that amateur, but I’ve seen it.
And what also happens is all channels eventually saturate. So what happens is you go into market, you start investing, cost of acquisition goes up, suddenly all the competitors doing the same thing. And it’s no longer this evergreen territory, right? So you have the saturation problem.
New hires, when you bring folks on, have a ramp up period, so people aren’t productive. As soon as you drop them into column ff, right? You need to account for the fact that it’s going to take three months for your sales person to become productive, right? They’re gonna have to learn how to the product even works, right? There’s a huge delay here. There’s learning curves and all of our businesses, right? If we’re going to forecast that properly, we actually do account for that. Time is the enemy of all deals, people make mistakes. So wouldn’t it be nice if we could actually, you know, assume that maybe our people aren’t going to be perfect all the time. When we’re forecasting the future. Engineers creating value communicating value, sales capturing value. And then the last one, which is big x, like it’s the 10 commandments, or something is a drag on the organisation as it scales, so inevitably, and Dharmesh hit on this, ultimately, the fight is complexity,
So if you’re lucky enough to survive the first part, you suddenly really enter a zone where the biggest problem with your growth is just the inefficiencies, the friction, the drag that happens, because you’re growing so fast, right. And if we have a simulator for business, that should actually take these things into account.
So let’s assume for a second that we have one of these, and I’m happy to talk about what goes into building one. But let’s assume for a second, we have one, I want to show you some of the cool things that you can do with a tool like this, that you couldn’t do before. So let’s go back into the, into the world that, you know, as we are going to know it in a year or two where a lot of us, especially BoS minded folks are, maybe we’re bootstrapping. But we also might find out that we can actually go get money, we need to run our businesses on this right hand side, this alt space, what can we do with a tool like this that we couldn’t do before?
Okay, so let’s let’s look at growth, for example. So kind of laying out the classic quadrants here. Different growth curves, who here knows about the SaaS ramp of death or is familiar with that phrase? Cool. It was, I think it’s popularised here. And it’s great. It’s one of those ones, I think, stuck in everyone’s head, because so many of us have been there, right? But there’s not just one SaaS ramp, right? All ramps are a little bit different. And part of the fun that I’ve had in building this simulation is I can kind of generate these ramps at will, right? And I can just see like, what are the differences, right? Are they all, they all the same shape, or some a little bit different than others and create something like a taxonomy. So this is four of them. But there’s many, many, many more, and we’ll talk about the application in a second. So high retention and high word of mouth or Net Promoter scores. top right, of course, we all want to be there, right? Average retention, average net promoter scores, bottom left, I’m not saying bad, just average, right? And then obviously, the other the other aspects.
So let’s kind of push those out, get them out of the way. And let’s look at what growth curves look like inside of those. So cohorts, all is pretty little colours are groups of customers signing up, right? And cohorts are, I like the cream analogy, cohorts rule, every actual metric. So if you want to think about a growth ramp, you really can’t do it without thinking about cohorts and what’s going on underneath your business. So if you think about the bottom left, average retention, and average, net promoter score, people hearing about it, ultimately, you grow your business, and each of these layers is shrinking, as you grow. This feels pretty awesome, right? So you’re like, wow, we’re just crushing it. And then there’s this concavity that happens or convex turn, and now you’re on this plateau, right? And suddenly, you’re like, what happened? Why can’t we grow?
This is where a lot of SAS businesses start. And as well, a lot of them stop. And ultimately, when the market dries up, this will cascade and you actually have drawn a graph before of what it looks like when a SaaS company dies. And it’s really wild. Like this gyrations all the way down to zero. Now high retention and average net promoter score this is this is a beautiful ramp, right? This is the most boring thing. But what’s happening here is these customers are like not cancelling. So if you have an enterprise SaaS business, you’re adding customers every single month. This is essentially the stairway to heaven right? Now, that’s great. But not as good as in the right. But before we go there, let’s talk about the bottom right for a second. So what happens if you have average attention, meaning people are cancelling, but people are telling each other about it quite a bit, right? You actually get this kind of weird shape, it’s a little bit more of a lumpy ride to the top. And this one, I think, makes it really clear that if you just are looking at the top surface, if you’re just looking at revenue, right? And if you’re just looking at revenue here, if you’re just looking at revenue, here it close, what’s actually happening underneath, right? So it’s really hard to say without seeing these these different shades. Where am I headed, right? So this is great. And then it’s kind of down again, it’s great. Well, this lumpiness is happening because I got churn, right? And the churn is actually fighting, the great references that I’m getting. So for some reason people are cancelling, maybe they’re outgrowing my product, they’re still telling people about it while they’re in it. Maybe there’s an awesome referral programme, whatever it is, but they’re ultimately leaving.
And then this one, which is rarely seen in the wild, but is awesome. People are sticking around, and they’re telling everybody about it, right. And so you finally see in this in this top right hand corner what most founders draw in their first forecast for their business. And yet, they haven’t figured out how they’re actually going to achieve this kind of retention, this kind of reference ability, but doesn’t matter, investors today need a forecast. And I’m going to give them a forecast. So this is what they get. And I gave kind of names to the so cake I stole from someone else. Jeff, online, I can link you to him, but a VC that was following he said, I like cake like charts I do too, this one I feel like is quicksand, you’re essentially running up this hill as fast as you can. But ultimately, it’s sagging out from underneath you right and you’re sinking.
This is not a huge problem if you have a huge market, because you can just keep going up and up and up and up. But what happens is founders sometimes will look at companies that we want to imitate right will say like, yeah, I want to be just like them, and we adopt their ways and practices. But turns out they have a market like oh, I don’t know, email marketing or something where there’s literally like 50,000 possible customers. And they just keep running on this quicksand all the way up to success. Meanwhile, we’re doing something like your I don’t know, software for schools in our area. And turns out that once you hit this point, you’re flat, right? You don’t have any more customers to turn and burn.
Viral quicksand, which sounds horrible, worst possible thing, although viral cake might be worse, is, you know, quicksand. But you’re getting these reference abilities. And then viral cake. I like to say if you see viral cake in the wild, don’t touch it. But tell me about it. Because we may want to invest somehow. These are some growth curves. And then the question becomes now that we can, now that we have this simulation, we can kind of play all these different scenarios out really fast. You can kind of put on our strategic hat quicker sooner and say, okay, which box are we in right now? Now these are all kind of spectrums? You’re probably not exactly one of these. But you’re closer to one of these, and you are the other most likely.
If you’re in the bottom left, what makes most sense for your business to do next is to move to the bottom right. You’re probably not going to try a diagonal, right? That’s kind of like Dharmesh yesterday saying new products, new customers highest risk, right? trying to fix retention, and you know, creating references the same time, but which direction should you go? And what outcomes? What outcome is your next growth initiative? So understanding where you are in this kind of layout becomes really easy when you have a simulation where you essentially put in your assumptions, run your business through it and say, Okay, we’re actually going to grow our revenue slower. If we take the cake approach than the quicksand because we’re not focused on acquisition as much, we’re gonna slow down our acquisition efforts. But we’re not going to plateau, the same way we can keep building our revenue base.
So this is one example of the kind of strategic thinking that’s possible once you’re not spending hours and hours in Excel. Let’s talk about one more. net income. Classically defined is this breakeven point. This is where economists you know, love the idea of things being like an ill structured problem versus well structured. So this is a well structured problem, right for your business. See, you have this breakeven point, I’m sure you did the math once you know exactly when you’re gonna breakeven on costs and income intersect. It’s that P right there. You’re driving towards that and that’s it right?
But in reality, net income forecasts have uncertainty in it. So this is a forecast that I generated for the same SAS business around through 10 different scenarios for it. Just to look at, you know, when is this thing going to break even now, you’ll see there’s a lot of consensus. So the idea that, you know, we’re going to be below water for a while. But then if you look at when it’s going to break even so when this line when these purple lines cross is when you’re finally getting to some profit, this is nine months here, right? This is six? Six to nine months is kind of a big deal, right? When you’re first turning out, six months might mean, everything’s great nine months might mean, we had to lay off an engineer, right? or half our team or whatever, like, we don’t have nine months of runway. But the question is, do we really understand the sensitivity of ourselves and our business to these uncertainties?
So you have all these uncertainties? But have you actually done the modelling to figure out the effect of that now, I think the good news is, is that once you do this kind of math, or you do this kind of modelling, where you at least know is that you have six to nine months for breakeven, you know that you’re burning something almost $20,000 a month, let’s just call it 20 to round up, but it’s going to less. So let’s just take 9 x 20000 = $180,000 $200,000, that’s actually amount of money that you need, right? You’re looking at this going maybe a little more, let’s make it 250,000. Right to be on the safe side. Now, I need $250,000 to go out to the market. And if you’re in the old world is like, Hey, we don’t write $250,000 checks. Really sorry, right? Write $1 million checks, you write $2 million checks, right? And we By the way, we only write them for like, 18 months usage. So you need to tell me what you’re doing, like a year from now. And then maybe even like, 18 months from now, and I just need $250,000? Like, what but is it gonna be a billion dollar company, right? I mean, I need to know if like, I’ll give you the 250 now, but you need to come back for more, it’s broken, right? You just need $250,000 to get this business off the ground, because on the right hand side is a really cool business, right? of profit, and all these things that we actually care about. So let’s go back to this new world, or capital is a lot more productize. And think about how, if you understand how much money you need, you actually can model it that fast. And you can go out to a market that’s willing to give you that money based on data that fast. Like, how different is this than having to go to Sand Hill Road, or New York City, wherever it is that you go? Making a bunch of phone calls. To me, this is actually the evolution towards something I like to call the Amazon of VC.
The Amazon VC completely flips the whole thing around and says, you know, entrepreneurs are actually a scarce resource. Like your willingness to build a company and sacrifice and do something innovative is actually scarce. There’s a cash is a commodity, right? We’re not commodities, cash is a commodity. So if that’s the case, what we need is we need to understand what is a clear cost of capital, right? How much is it actually going to cost to take this money? I need that money right away. Right? I don’t want to wait six to eight weeks for an answer. I don’t want to deal with people ghosting me over email, I want to know that I get that money, I also want to raise the amount of money that I need. So like, I don’t need 4000 of these. I just need 12. Right? So I need two or $3,000, not $2.5 million. And it’d also be really nice. By the way, if you have all this data, if you could just like let me know when you’re wanting to give me money, right? So I wake up one day, and I find out like, hey, you like how my business is doing, you’d like to offer me some money.
I think this is possible. And this is what funding is for right. And so just to give you kind of an example of my personal life. And to tell you what this is. This was my win loss record on startup funding pitches. And I didn’t get to start at the right. I started at the left. So this is me pitching. Now when I say pitching, I don’t mean like, Oh, I send an email or or something like that. Or I got an introduction over email like no, I actually had a phone call or an in person meeting to raise money for my startup, my first company. And those only came after I talked to like probably three or four or five people before that, and you filter them down, you take the one now, this is what happens when an entrepreneur with no credibility, no reputation, or whatever has an idea kind of goes out to the market and says, I have this great idea. Let’s solve this huge problem. And actually, I had a business at the time. So we were doing about $250,000 a year in revenue, right? And we wanted to grow it. And it was just me and a co founder. So it was actually profitable. And I wanted to go raise money, but this is the response that I got. And in case you’re wondering, this is actually 27 rejections.
Followed by my first Yes, this Yes, came the week of Thanksgiving. And I remember because when I finally got it, I think I threw up in the front yard of someone’s house in the middle of the night because I pull off to the side of the road and I found out that we’re going to be able to pay our server bills that month our Amazon bill was coming due and we had no way of paying it. So I got that yes, that was $25,000 which saved the day and then I got nine more rejections and then I got another Yes. And then I got five more rejections and I’m really disappointed that this is five and not three, because this would be three – nine – 27 beautiful, right? Yes. Okay, so I’m But you know, plus or minus, right? And then a few more rejections than to and then oh my gosh, what happened here like this was, I’m a success, right? And it’s, it’s sad. But this felt different. And it’s clear to me that there is something happening here, which is people call it the herd mentality, right? I would call it gravity. But what was really sad about that is that I was going out there saying, I have a business doing a quarter million dollars in revenue, it’s profitable. I know what I need to get it off the ground. But what I was having to do instead was make up a pitch for this to be this humongous business, right? Something that exceeded my wildest dreams, and then actually logic my way to that, right.
So I like to say, there was only one item on the menu, and it was cheeseburger, cheeseburger, cheeseburger, cheeseburgers, which was essentially unicorn food. And that’s the only thing that was on the menu, right? That was my only choice. But imagine that this was me back then. And I said, I have a clear knee, right? I have a model, you can even look at it. If you want to, you can play around with it and see if you believe me. Why don’t you send me some options, right? And imagine if instead it said, Okay, here’s some options:
Number one, is to give you some money to do some marketing, right, we’ll give you a loan $250,000, you’ll pay it back over an 18 month period, and you’re gonna invest in marketing, and it’s actually going to get you your net income is going to grow as you invest in that marketing campaign, you acquire new customers, like, that’s pretty cool.
Or, alternatively, you could do revenue based financing. And so these green payments are payments to the investor here, are actually going to ebb and flow with your net income. So as my profit goes up, these payments increase, when I don’t have any profit, these payments are small, right? Again, option number two, I okay, that’s kind of interesting, I pay back over 24 month period, but I just random money that I need. And I don’t have to tell you that I’m going to be a unicorn.
And then maybe option number three is I’m actually going to fund you, I’m going to take place an equity investment in you. But when you get to this area over here, like you can pay me back through dividends. And I’m totally okay with that. Right. Like, that’s pretty cool.
So I really believe that the next generation of capital, because of this is going to be entrepreneurs actually get to make choices and decide on trade offs and how they fund their businesses, as opposed to only picking the one thing on the menu, which is that you have to go become this huge, great thing, right?
Success, as you define, it suddenly becomes the measure of success you get to use when making these trade offs. And you can pick one. And now you have for the first time founder investment fit, right, you’re taking money on your terms, to get to the goals, you have to solve for the problem that you have. And ultimately, that creates less risk; less risk of burnout, less risk of trying to do things that your business is really not designed for, and you don’t care for. And that ultimately creates more success.
So just kind of review. Two things you can do. One is clearly state your assumptions about the inevitable. This is a really fun exercise to do. You can do it with your team. It’s takes maybe 10-15 minutes to get the first version done. And you can talk about what’s changing in the market. Can you plot the needs of your customers? How are things evolving? And what are those things that are going to give in the landscape, right? They’re going to ultimately, that are bottlenecks. Right now they’re going to change. And then the second one is consider the physics of your particular business. What is the shape of your growth ramp? What is your business doing right now to get to its next level? And how do you use that to prioritise change? What do you actually need to change about your business? Is it retention?
And some of the things we didn’t mention? Just a few variables; how long your sales cycles? How many deals can your salespeople handle at once? Right? How much revenue can a customer success person handle at once? Right, so there’s many different variables that you can shift. And I think we focus, I think, because we’re still looking at the frogs and jars and the cow is moving in the field is are indications that things are changing, we keep going back to churn and churn and churn and charge more and all this, it was just great. That might not actually be the thing you need to do next in your business, and it might not be the low hanging fruit. And then lastly, if you’re considering funding, ask yourself if it really fits your needs. I ended up taking funding from a firm called tiny seed, which is a bootstrapper friendly funding option. I think that’s going to become more and more popular for folks who have a mindset about building real businesses, sustainable businesses. And I think the future is coming where the solutions to your funding problems actually come to you, which is the way it should be.
So thank you very much.
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