Investing ideas that changed my life
If something has a chance of either destroying you or making you very wealthy and you don’t know how to measure what that chance is, it’s understandable that people default to high levels of credulity.
You can’t believe in risk without also believing in luck, because they are fundamentally the same thing—an acknowledgment that you are one person in a 7 billion player game, and the accidental impact of other people’s actions can be more consequential than your own. But the path of least resistance is to be keenly aware of risk when it affects you, and oblivious to luck when it helps you. Investors adjust returns for risk; never for luck. Companies disclose known risks in their annual reports; lucky breaks are rarely mentioned. The danger is that experiencing risk reduces confidence when it should merely highlight reality, which can make future decisions more conservative than they ought to be. Luck increases confidence without increasing ability, which makes people double down with less room for error than before. Realizing that luck and risk are ever-present and normal makes you accept that not everything is in your control, which is the only way to identify whatever is in your control.
If you think the world is all art, you’ll miss how much stuff is too complicated to think about intuitively. But if you think the world is all science, you’ll miss how much people like to take shortcuts, believe only what they want to believe, and have to deal with stuff that is too complicated for them to summarize in a statistic. Another way to think about this: Investing is not physics, which is guided by cold, immutable laws. It’s like biology, guided by the messy mutations and accidents of evolution, constantly adapting and sometimes defying logic.
“How long will this remain important given my strategy and time horizon?”
The dynamics of network effects
So how can entrepreneurs and founders navigate this era of seemingly diminishing network effects? The trick is to know what your network effects look like today, but also project how they’ll evolve over time. To that end, you’ll need to understand three aspects of your company and how they could change going forward: 1) your value proposition, 2) your users/inventory, and 3) your competitive ecosystem. Otherwise you could get caught flat-footed, claiming that network effects are dead.
Early on, more friends in Frank groups meant more demand and more liquidity, which created a bigger incentive for people to join those groups. But once a group had more than 7 people, they became less likely to lend or borrow: turns out people only have ~7 friends/family members they have that level of trust with! The network effects in this case went from positive to negative as an individual’s network outgrew the value proposition. This pattern has also held true for a number of other highly social products.
Platforms/marketplaces with more differentiated inventory have stronger and longer-lasting network effects, because they have a diversity of inventory that suits the unique preferences of customers (while maintaining just-enough substitutability across that inventory as well). For example, AirBnB can show users every iteration of lodging from $225-$325/night in Los Angeles, which overlaps with someone else’s search for something that costs $150-$250 and has a both a balcony and a hot tub. The platform is therefore more valuable on both sides of the marketplace than a site that just shows a commoditized set of standard and executive rooms. The network effects remain strong not only because it reaches a base level of liquidity across all these different types of inventory (making them valuable to more users), but because it also continues to see increasing returns with new supply.
When you forecast out your network effects — and more importantly, your growth strategy for acquiring and engaging more users — you will need to pay attention to the incremental users you’re likely to attract. Are they network “contaminants”, “neutrals”, or “contributors”? For a social network, adding a troll that disengages other users is a pollutant who removes value. Adding a lurker is neutral since that person doesn’t add or subtract any value from the network. Adding a great content producer contributes an enormous amount of value to the network. So, making sure to incent the users you want while disincenting the ones you don’t want, is key. This is why most great platforms also invest heavily in curation mechanisms to screen and remove bad inventory/users (e.g., Wikipedia’s editors, Airbnb’s reviews/onboarding, etc.). Unfortunately, these screening mechanisms don’t always work and sometimes the cost of finding strong contributors becomes very high, so the calculus of growth relative to cost matters a lot here.
While network effects businesses tend to be more defensible at scale, they are not immune to competition. But for these types of businesses it’s not just a matter of figuring out who your direct competitors are — you also need to think about the network overlap. If someone else has a similar network to yours, there’s always existential risk they’ll move into your market. Because they have a similar network already, they’ll more easily be able to enter your space (Instagram’s foray into Snapchat-like disposable “Stories” is a good example of this). This is also true where the competition may already have registered a superset of your network (e.g., DoorDash and Uber Eats; Didi and Uber in China).
The increasing speed of product iteration, the pace at which networks can scale, and the ease with which competitors can get started has therefore dramatically changed how we project network effects in businesses. Instead of winner-take-all markets where early movers may have once had a seemingly lasting advantage, network effects change more quickly than ever. Especially where specific factors — an asymptotic value proposition, network overlap, increasing number of contaminants, etc. — can lower the platform’s ability to generate a sustainable network effect in the future.