Invest Like the Best with Patrick O'Shaughnessy
00:06:41 · Patrick O'Shaughnessy, Martin Casado
[00:06:41] S0: You were saying before we hit start that nobody understands network effects. Can you explain what you meant? [00:06:46] S1: I've realized that even the most common terms I use, there's no consensus on. And so for example, network effects is the favorite one that I pick up. I asked you before [00:06:55] S0: I messed it up. [00:06:56] S1: No, you did mess it up. You said you said what? Like a third of people say. So said, so what does a network affect? And what did you say? [00:07:01] S0: I said a product that gets better as it adds a marginal user.
00:07:01 · Patrick O'Shaughnessy, Martin Casado
[00:07:01] S0: I said a product that gets better as it adds a marginal user. [00:07:05] S1: Right. So to me this is almost a tautological definition because most products will get better as you add a user, right? They will find a bug, they will provide feedback, they will tell other people. That doesn't say anything about defensibility. But other people when they use the term network effects, they actually mean the original meaning of the term network effect from the seventies which is a telephone network where when users join, they interact with each other. That grows super linearly and that's why you get like natural monopolies. And other people use the term network effect more to mean like an actual flywheel, so like a self reinforcing flywheel. So not just like things get better but like it self reinforces in some sort of a way. This is where you hear the term like data network effects. But even in that sense, like you don't know if that self reinforcement is super linear or not. So you don't know if it makes it defensible or not. So you have this very common word that's on 70% of pitch decks where a founder's sitting in front doing a pitch and nobody has consensus on what it means and [00:08:03] S0: so how would you define it?
00:08:04 · Martin Casado
[00:08:04] S1: So I think the root of the confusion is not a definitional problem. I think the root of the confusion is conceptually we conflate the mechanism with the shape of the moat. There's many things that could create a moat, right? Like a brand, scale, a two sided marketplace, network effect. But that moat, to reason about that, is only really useful if it has some properties that makes the company defensible against somebody else. If that moat grows super linearly with scale, like a classic Metcalfe's law network effect would, that's really defensible. If it grows sub linearly with scale, it may not be useful at all. And so I think to you and I have a conversation of defensibility, I think the first thing we need to do is not conflate the shape of the moat with the mechanism that caused it. So first, I think we should say the mode that we have is super linear, it's linear, or it's sublinear with scale. And then the second thing, a lot of things actually contribute to a mode. For example, like we mentioned, network effects will or scale effect. What's a scale effect? A scale effect to me is as the company scale, it can reduce unit economics normally because it has pricing power for example or maybe CAC goes down because of brand. What's a two sided marketplace that's very different to me than a network effect? That's where basically you've got self reinforcing supply and demand. So I think that there are many mechanisms and then there's the shape and then to have a discussion I think you want to make sure that the shape is something that actually provides long term defensibility. Then the last thing I'll say is it's almost impossible to have these conversations in isolation because we're actually talking about competitive equilibria. Because if you have a network effect, then maybe the competitor has a network effect too. And maybe if they have more capital than you and grow faster, that probably impacts the shape of your moat. You may not grow as fast marginally because they're stealing your customers or something like that. And so I just think that we need a very very basic concepts. We need to not conflate the notion of the actual shape with the actual mechanism. And then I think we should enumerate the mechanisms because something like the definition that you had just doesn't really help anybody.
00:10:08 · Patrick O'Shaughnessy, Martin Casado
[00:10:08] S0: Can you give examples of super linear, linear, sub linear just to bring it to life? [00:10:12] S1: Yeah, for sure. A common view of where network effects came from was from the seventies. I forgot the name of the economist that did it but he worked at Bell Labs and he noticed for train networks and communications networks, the interactions of users grows with the square of the number of people that join. As a user joins they can communicate to many other people so the actual number of connections grows more than the number of users. Therefore, the value grows more than just legally within that. The same thing with destinations on a highway or destinations on a train. So that would mean that if you have two competing companies, one takes $5,000,000 of funding and the other takes $5,000,000 of funding but this one is marginally better, marginally larger. This one's a little bit larger. For the same amount of investment, it will grow faster than a challenger. The growth actually increases over time and that's why you get a monopoly. Whereas sublinear means if I'm a leader and I invest the same amount as a challenger, I grow marginally slower than the challenger. That would be sublinear. Clearly this is very important when it comes to modes because if you have two competing companies and there's a sublinear mode, the challenger will always catch up to the leader because the leader has to spend ever more money to grow, all things being equal. [00:11:28] S0: Favorite recent company examples of these different types?
00:11:28 · Patrick O'Shaughnessy, Martin Casado
[00:11:28] S0: Favorite recent company examples of these different types? [00:11:31] S1: How many actual network effects in the Metcalfe's law of super linear do you think there have actually been? [00:11:36] S0: Very few, I don't
00:11:37 · Martin Casado
[00:11:37] S1: know. I feel like this almost never happens. Like I think we can all agree, the telcos, that's why we had to break them up. We could probably all agree LinkedIn, They haven't had to change very much and they seem to have a permanent status. Social networking. But all of these examples, it's like the interconnections of people. I would say GitHub was another one that had a It's effectively interconnection. It's interconnections of users, right? So I think there are not very many examples but when you have them these are these very durable high value companies. So that to me would be like a classic network effect. Other companies probably are more scale effects. For example, people will say Uber. I'm not sure that that would follow the definition of a network effect. Maybe a two sided marketplace because you have the drivers and you have the passengers. Maybe you could use that but even then, you don't have a lock on either of them. Like all drivers drive for everybody and all passengers could use anybody. That was more like of a funding scale effect because they could raise more money and therefore the unit economics went down. My meta observation... So first off, I actually think the network effecting was more of a personal annoyance and me being a pedantic. But I actually think defensibility in most is not really even worth talking about most of the time. Let me explain why. Here's my experience for what it's worth. If a market you're investing in is growing, then companies are not gonna wanna compete. There's like a lot of new white space that gets created and so what they'll try and do is they'll try and just move into other white space. Talking about defensibility is kind of a second or third order thing if the market is growing. And if the market is slowing down or shrinking, normally it consolidates anyways independent of most or not. And so I do think we spend a lot of time as investors hand wringing about defensibility when in practice it doesn't really matter especially in growing markets which we invest in and we've seen this with AI. I remember early discussions on models. I mean, I can't tell you how many investors are like, I will never invest in a model. It'll never accrue value. It's not defensible. That's fine, but as long as the market's growing in a large market, it's gonna accrue a lot of value.