I participated in my first hackathon two weekends ago. I use code to do data analysis most of the time, not write apps or websites. For me, it was more of a fun learning experience and I got to see what kinds of work are expected and rewarded.
One of the judges for the hackathon was a principal at a venture capital fund. The questions he asked the hackathon teams during judging were clearly the type of questions one would ask a founder about their startup. It was super useful to hear those questions and to think about how I can use them to sell my research and future project pitches.
Who else is doing it?
You need to show that you’ve done your research about the market. Your product/research isn’t exciting if someone else is already doing it. You need to put your own spin on it and offer something unique. If you can’t say that your idea is the “Uber for dogs” or something, then you haven’t made a great case.
How many people will use this?
VCs want to invest in products that are highly impactful. That means tailoring your product to a specific group of people who are most likely to use and benefit from it. Very often, we get excited about what we’re working on and think that everyone else will be excited about it too. But that’s not very effective: in trying to please everyone, you end up pleasing no one. Funders want to see that you know your target audience and that you’re tailoring your product to them appropriately.
How much impact do you expect?
Again, VCs want to see that your product will be highly impactful. They also want to have metrics by which they can gauge impact. You don’t want to say something generic like “my apps helps people do this one particular thing”. They want to hear “x million people have used my app in y cities around the world”. They want to hear how many dollars you’ll earn, or how many tons of CO2 emissions you’ll save, or how many hours your users will save. The more specific, the better. It shows that you have performance goals and you’re actively working towards them, not just plodding along.
How will you know if it’s working?
This is related to metrics for impact. This is why you need to lay out your expected impact clearly with measurable outcomes. If you’re not hitting those outcomes, then you can figure out what’s going wrong and make a plan to do better. Without this kind of feedback, you’re putting your product out there and hoping that your target audience is adopting it. The funders are less likely to have faith in your product if you don’t have a plan to detect when it’s not doing well.
Applying the ideas to academic work
Thinking about these questions highlights one of my frustrations with academia: people work on obscure research that has little impact outside of their field. I’m just not sold on why it’s important. Most research papers, I’d guess, are read by tens or maybe hundreds of people who work on similar, related questions. Even when I do read a paper that I think is intellectually interesting, I often don’t see how it’ll be put into practice: lots of statistical methods sit in academic papers and never get turned into code that’s widely distributed or used. I try to avoid that kind of work and instead make sure that I do research where the potential impact is clear and quantifiable, publish things online where people can find them, give good talks and write clearly so my work is accessible, and write open source code that people can download and use. In the future, I’d like to set better metrics and outcome goals for my work.