I wrote a post a few weeks ago about how algorithms will be driving more and more parts of our lives in the future.
One example of how businesses are using algorithms was with a VC called Correlation Ventures. Correlation has specific criteria for evaluating new opportunities and they feed the data into an algorithm that tells them whether to invest. The firm relies on this method to make better decisions and also make the process more efficient and less time consuming on both sides.
I’ve not heard of many VC’s using these machine based methods and it made me think about how far you could take this and whether early stage investment decisions can be made in a scientific way.
The most important thing an investor does is try to pick the best companies and then strike a deal to gain a stake in them. I believe the way that we do this is constantly evolving based on a combination of experience and market forces.
I’m always thinking about how I can identify the very best companies to invest in so I thought I’d try to review my process in the hope of putting some more structure around it.
For me there are three cornerstones to a great opportunity – team, product and market.
This is the most important thing and drives everything else. I really believe that the team you build is the company you build.
There are many aspects to team and there can be a danger of looking for too much, especially in an early stage business. I believe that the single-most important factor is to have founders who are compelling, driven, passionate and bright. In short to have founders who can ‘fill the room.’ To get this piece right is so important and, in my opinion, the biggest driver of success in a start-up.
I want to feel that the company has an idea that really meets a need and makes their customers lives better. I also want to see that the product ‘walks the walk’ – even an early version needs to looks great, be easy to use and demonstrate some real innovation.
Beyond that, it’s great to see a roadmap that shows a clear sense of priorities, that the team know what ‘they want to be the best in the world at’ and that decisions are set in the context of customer feedback and some real conviction about where the market is heading. I also like to see the product leveraging recent technology developments that provide the opportunity to approach a problem in a new and improved way.
At MessageLabs, the market had changed because almost all viruses started to piggyback on email to spread much faster and to more people then before. At the same time the internet infrastructure had become good enough to run some less demanding applications from remote data centers. These developments made it possible for us to deliver an internet-level anti-virus service that scanned email while it was in transit and used a range of techniques that would not have been possible with PC based software. We also decided, from an early stage, that the one thing we never wanted to compromise on was being the best at stopping threats and this drove our decision making on product priorities.
The company needs to be entering a market big enough to deliver good returns to its shareholders. As a VC that invests mainly at the ‘Series A’ stage we want to believe that the company we’re investing in has a market that could deliver an exit of at least $100m. We also want to feel that this kind of exit would be possible without any overly aggressive assumptions on market share – this would usually mean less than 10%. Very few companies manage to eke out a market share of more than 10% so it makes sense to assume it will be below this level.
I also like a market that has two characteristics – A) Widespread dissatisfaction with the status quo and the incumbents and B) Recent developments (usually technical but could also be political, economic or sociological) have paved the way for a new generation of competitors.
The banking sector is a great example of this where almost everybody is frustrated with banks and the internet, as the great transparency enabler, has opened up all kinds of new possibilities.
I want to feel that the business is strong in each of these areas and that tells me it could be a racehorse. In the best opportunities, the way these ingredients combine together will also be more than the sum of their parts and you just have a feeling that this is something special. I call this the x-factor and it’s not something you can really explain or measure.
The next stage for me is seeing where our racehorse is on its journey and what kind of speeds it’s achieving.
In my world, I like to see a business with meaningful revenues, fantastic growth, healthy margins and a representative group of committed customers. Customer commitment is demonstrated by the money they are paying, the feedback they are giving and the length of time they have been on the service or are contracted to be on the service.
Once I’m satisfied that the traction suggests my racehorse has made a good start on its journey to the promised land I then start to think about the deal.
The deal is simply the instrument that allows me to buy a stake in the company and its future success. It’s difficult to value an early stage business in a scientific way. There is value in the three attributes of team, product and market. There is also value in the traction that the business has established. But working out exactly what that value should be is a difficult thing.
I like to feel that I/Notion can bring a good deal of added-value to the table and we are therefore never likely to be the highest payers. The most important thing is that both sides should come out of the process feeling good about the deal, feeling aligned on what they are trying to get out of it and looking forwards to working together.
So this is how I go about selecting and investing in start-ups. It is by no means a perfect process and I’ve made my share of mistakes. But I like to think that I’ll keep learning and keep improving.
I still believe that early stage investing is more about instinct than anything else but that you can bring some structure to it and you can keep refining that structure as you go. Maybe the best way to describe it would be structured instinct?