Why some tech investors succeed while others fail

Dmitri Lisitski, Influ2 This post is the result of numerous discussions and brainstorming sessions I had with my old-time partners and friends. These discussions brought to life a model that could be helpful as a framework for anybody who considers pursuing a technology investment path. The cases I provide are for illustration purposes only — some people might laugh at them. I am not a veteran VC investor; I just use some examples of compelling cases that I am aware of in order to illustrate how the model works.

Nevertheless, this model DOES explain why I decided to refrain from creating an investment firm to continue my entrepreneurship path. Also, I think it provides a high-level explanation for why some investors succeed while others … well, couldn’t beat S&P. With this disclaimer, I still encourage everybody to comment on whether this framework is illustrative enough and if it has logical flaws that should be fixed.

Before we dive into the model, I would like to address the purpose of this model. Why do we need a model at all? Look at Tim Draper, Peter Thiel, or Paul Graham: they invested in Skype, Facebook, and Airbnb, respectively, and made fortunes from these investments — so let’s rush to do the same! This is a perfect example of narrative fallacy. Unfortunately, if you judge VC performance based on Forbes articles, your sample will be dramatically skewed towards successful cases. In real life, technology investment is a negative-sum game on average. Investing randomly in technology companies or attempting to build the VC equivalent of a mutual fund by investing small amounts in many companies are both very similar to another negative-sum game called “casino” — you better be extremely lucky if you try.

The VC industry on average is struggling to consistently beat S&P while offering much higher risk:

As you can see from this chart, the industry average is barely showing meaningful returns. If we remove star funds such as Sequoia or Andreessen Horowitz, average returns for mediocre funds are negative. And this is despite the fact that the venture partners of these firms are clever people doing their best to select great startups, leaving dumb startups to an even more struggling asset class of “Friends, Family and Fools”. Hope you are convinced by now that it would be nice to have some explanation for why some VCs perform while others don’t.

Imagine yourself standing on the coast of a big blue ocean, and you know there are precious treasures at the bottom of this ocean called “unicorns”. Unfortunately, you can’t swim. Luckily, you spot a gang of weird-looking dudes who you wouldn’t lend a penny in another situation — but they say they can swim! Those unicorns are so tantalizingly great that you decide to take a risk and buy equipment for these weird folks, hoping one of them will succeed and make a fortune for both of you.

 

The problem is that there are too many divers, so you have to choose the guys who are the most likely to deliver on their promise. Luckily, they are not silent. In fact, they talk too much. They describe amazing spots in the ocean where the water is not deep and where they saw a lot of unicorns along the bottom. You squeeze through shabby divers talking about “search”, “social networks”, and “on-demand transportation” as people say these once-great spots have been exhausted by now. You can hear one diver talking about an awesome spot called “cloud”, but he is interrupted by another one talking about “big data”. Suddenly your ear catches something people whisper with awe: “A.I.”. You realize this particular spot is full of unicorns (why would they whisper it otherwise?), -so you start chasing rare old divers that look like schoolteachers in thick glasses. They claim that they know the AI spot, bombarding you with acronyms like DNN, CNN, and RNN and promising to bring you the ultimate, or what they call “singularity”, unicorn called “General AI”.

You can’t stand this total mess, so you hire a guy who promises to sort things out. He calls himself an “analyst”. He can’t swim, just like you, but he wears glasses and has binoculars, so he can help you look at a spot with the hope that you will see the alluring shine of a unicorn.

As you talk to divers, you discover another complexity. There are different layers of water as they dive. Unfortunately, analysts can see only through the top layer; let’s call it an “analytical layer”. You can get more information only by diving. Young divers can dive to “MVP”; that’s the only layer you can reach without any equipment. MVP is followed by “traction”, then a diver could “growth hack“ through to “organizational design” followed by “corporate culture”, and on to many other layers. Deep in the water you can find a dark “compliance” layer or be chased by “IP wars” predators before you find unicorns somewhere close to the “IPO” layer. The problem is that very few divers can dive so deeply, and most of the crowd just talk about what other divers talk about. So, you quickly find yourself mastering the terminology, freely speaking about all these spots and layers, but your conversation with divers remains at the level of teenage talk about sex — you know how everything is supposed to work, but the lack of practical knowledge is a mammoth barrier to getting a girlfriend.

Let’s visualize this model before we compare great VCs to mediocre ones side-by-side:

 

This picture is self-explanatory. Spots are vertical (they’re what we sometimes call “verticals”), layers are horizontal, unicorns are on the bottom, and there are multiple red predators that can kill you on your way to hunt unicorns. The depth of the ocean represents the amount of knowledge you need to gather to build a unicorn — including founders’ knowledge, investors’ knowledge, and organizational knowledge of a startup that develops as it grows.

What does this picture show? In order to identify a unicorn, you better be an experienced diver yourself. If you are a good diver you can spot other good divers. A good example is PayPal mafia. Analysts can see only the surface, so you can’t predict unicorns just by reading Gartner reports even though it feels like you are seeing the shine coming from the dark depths of the ocean when you do.

There are many elements you can only learn by doing: will customers need this product? will they LOVE it, and if so how can you win this love? which customer acquisition model works, and how much will it cost? will you face competition, and what substitutes will deteriorate your customer base? which external partnerships will take you to the next level, and which acquisitions will fuel your growth? and so on and so forth… Here is an interesting study confirming that top-performing funds have more past entrepreneurs than mediocre funds: https://techcrunch.com/2015/12/02/entrepreneurial-experience-separates-top-vcs-from-other-investors/

Technology investment becomes even more complicated if you think about the breadth of the ocean. Knowing one spot (industry) doesn’t mean that you know how to dive in other spots. The industry focus of the fund and each of its partners comes into play.

 

I witnessed how good VCs with a clear technology focus can be amazingly effective. We met with Blue Run Ventures, pitching them Thickbuttons. In short, we were aiming to build a better keyboard technology for small smartphone screens. The Blue Run folks instantly got what we were talking about, estimated how much we would be making, explained why the size of the opportunity was too small for them, and, despite this, gracefully offered to introduce us to a top mobile vendor. They dived in the spot where we were planning to dive before, knew what was at the bottom, and even offered to bring us up a nice seashell from down there.

Startup programs are another interesting case. Why did YCombinator bring to life unicorns such as Airbnb, Dropbox, Docker, Stripe, and more to come, while you can barely name a unicorn coming from all the European startup programs combined? Of course this is a big generalization, and it’s likely there are some very good programs in Europe (if you poke my nose into one I will be very grateful). The explanation is very simple. Both offer small investments to a large number of startups, hoping one of them will be a unicorn, but the difference is that YCombinator has the depth of practical knowledge of their mentors and network that its European counterparts lack.

 

This model helped us to realize a bitter truth about where we stand on the technology investment front and about the odds of succeeding in this game. The only conclusion I could draw was that being a diver is a very exciting endeavor, full of discoveries that guys who just buy diving equipment can only listen about. As Jacques Yves Cousteau put it: “The sea, once it casts its spell, holds one in its net of wonder forever.” This is why I’ve chosen to stay on the entrepreneurial path.

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