Last week I met Gus Tai of Trinity Ventures for the first time. We had an interesting conversation about the people aspect in investments and it was enlightening to share our experiences on the topic of people. If there was one thing that both of us have learned over the years, that was the fact that people are who they are, and that we shouldn’t try to make them be or do something different.
As I get to know entrepreneurs and get a sense for what they know, who they are, and where their strengths are, I get a sense for what they are capable of. At the seed stage where Launch Capital plays, we don’t have the luxury of being able to spend a long time getting to know founders than perhaps someone who invests at later stages. So I’ve had to hone my intuition and my interrogative skills to ferret out what I can at the time of investment. Later, I can watch them and see how they react and act and build up my knowledge about them. Unfortunately, if something problematic comes up at that point, it is somewhat late since my investment has already been committed. So the goal is to be able to get as much information about them before I invest, although a lot of that info needs to be gleaned from only one or two encounters prior to an investment decision.
I meet someone and then build some intuitive and informational view of a person. It’s pretty straightforward to ask them questions about their past and what they’ve done. But not only are their answers important but how they say them.
For example, I might ask an entrepreneur what their experience is with design. They may say they have a lot of experience designing, talk about what they’ve designed, and how they’ve managed a lot of design resources. This is all great. But as I listen to the language he uses and probe further, I realize there is an insensitivity to users’ needs and the words that he uses implies an attitude towards designers that is condescending and disrespectful. This is what I mean by paying attention to how it’s said as well as what’s being said.
The intuitive view is less certain, encompassing subtle, non-verbal cues which are coupled with what they say and how they say it. Books have been written about body language and detecting lies and surfacing their true feelings and intentions; these are all relevant. I try to take it all in and this builds the intuitive view of a person.
All this informational and intuitive probing are geared towards not only type of person they are (hopefully they have integrity, honesty, and the whole host of other positive entrepreneurial characteristics), but also how far they can take the startup idea they are working on.
For example, every time I meet an entrepreneur, I always bring up the vision discussion. One case that may happen is that I know a lot about the space he is working in and already have some formed opinions about where they should take their business. They ask me what those opinions are and of course I start ranting or spouting ideas. Then I gauge their reaction to my words.
Sometimes they have blank stares on their faces; I can tell they have little idea what I am talking about, or they have some sense but don’t have the depth of that knowledge. Sometimes they say they agree with me, but something in their body language or the way they say it tells me it is just talk and I cannot see any depth in understanding.
And the best reaction is when they actually know something about what I say and we have a bromance discussion about how geeky we are in that we both share knowledge and are big fans of this area.
However, if that bromance geek discussion doesn’t happen, then I begin to worry. I start to form the limitations of where this team can take a concept. Either they must learn this themselves (first the interest, then the ability to learn it) or they must have the awareness that they must hire the talent to fulfill the bigger vision and not the vision to the limits of their current abilities.
Not many people have the ability to change into new areas of growth, whether it’s physical, emotional or intellectual. It is the rare individual that can. Most likely, what we see by the time they are adults, and by the time they are working on this startup, is what we’re gonna get.
Believe me, I have tried to get people to do things outside their current areas of interest or strength. But most of the time, it is futile, especially as an outside entity to a startup. If I am not there day to day 24/7, it is really hard to get an initiative going that is not familiar to the personnel there already. This is why I try to be as creative as possible in providing a multitude of ideas and see which stick and which do not, and also try to be as creative as possible within the constraints of the team’s abilities and skills. But I have given up trying to make them someone other than who they are today unless they are willing or able to make the change in themselves.
The trick therefore, is to get a sense of these people through information gathering and through intuition, form a picture of their capabilities into the future, and then make the call. Building your sensitivity to determining who people are is an important part of investing; at early stage, however, we need to be able to make that determination as fast as possible since we don’t have the luxury of getting to know them over time before we invest.

This week I was at 500startups meeting the new accelerator class. The subject of data came up once again and I thought I’d finally get to this post which I’ve been meaning to write for a while now.
I have found that data always follows this path:
1. Measure the data – Some mechanism appears which allows us measure the data. The insertion of a tracking pixel on a web page, the creation of new type of sensor – these are just examples of activating the ability to measure data.
2. Collect the data – Once we can measure the data, we can collect it. So it gets dumped into a database or similar. For example, the tracking pixel’s loads from a server are saved in log files, or we connect a data collection device to the new sensor which takes readings at regular time intervals and saves them.
3. Display the data – After collecting the data, we can display it, usually in its most primitive form, which is often rows and columns of numbers.
4. Visualize the data – When we display data in raw form, it’s not optimal. Visualizing the data via graphing or through further number crunching can bring better interpretation of large data sets than scrolling through endless rows/columns of numbers.
5. Derive insight and action from the data – After we analyze the data, we can determine what happened and then what to do next.
Usually, people get through steps 1 through 4 very quickly. We see what I call the “Mint-ifying” of the data collected. But I contend that this is not good enough. It’s nice to see the data in some easily digestible form but always the next question is, “what do I do next?”
Almost no one ever gets to 5. It’s always up to the viewer to take a look and then figure out what to do next. But this is hard. Some people can figure it out and some people cannot. Some people could figure it out if they took the time to go deeper but they don’t have the time.
That’s why I think the ability to generate insights and what to do next is the holy grail. It can seem exceedingly difficult to create a system that not only displays data but also tells you what to do next.
Some observations here:
1. If you don’t have deep knowledge and experience in the area in which you’re building a data system for, you’ll never get there. Either that or you’ll never realize the full potential of the data.
2. If you are not a current user of the data in a real world application, you’ll never know what another person might want to do with the same set of data.
3. You might want to hire someone to help. The number of people who know how to use real, measurable data and figure out what to do next with it is very, very small. So trying to find someone in your area of operation may be very difficult. Or you will require a lot of time and experimentation to get there, maybe more time than you have.
I’ve met many startups over the years trying to exploit the data they are collecting. But as far as I can tell, virtually none of them have produced systems that can tell you what to do next from the data they display. These days I always ask the data startups how and when are they going to generate insight and action and I look for some glimmer of hope there. This is because I truly believe that if you can produce insight and action, you will have real gold in your business.