Database Reference
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technical skills and has a strong scientific base but at the same time has built
stuff—building not just models but teams and maybe even businesses.
The search for a person who fit this profile led me to my partner, Brad Gillespie,
who is one of the few unicorns who has the combined knowledge and experi-
ence I felt the team needed. We were then fortunate enough to subsequently
find our colleague, Jesse Beyroutey, who embodies a similar profile. He had
gone through the Fisher Program at Penn, obtained his master's in CS, worked
at Microsoft, and then worked at Insight Ventures. So again, we went looking
for and found somebody who had exceptionally strong technical skills but also
the perspective and passion to be a builder. He's grown tremendously over
the last three years. We also have Drew Conway as a scientist-in-residence
who is a globally-known data hacker and data visualization expert. Again, he is
someone who has incredible horizontal skills.
Gutierrez:
How is Drew, as a scientist-in-residence, a competitive advantage
for your team?
Ehrenberg:
We felt that having Drew work and live with us would seep into
our DNA. He would also be able to work with some of our portfolio companies
on very prescribed projects. The way that we've been able to best apply his
skill sets, give him the best learning experience, and be the best resource for
our companies is when projects are very clearly scoped out. That is, when
there's a particular data set or a particular product initiative that would benefit
from Drew's experience in hacking data. Drew's worked with some of our
portfolio companies like PlaceIQ, Next Big Sound, and Recorded Future that
tend to have these very interesting, rich data sets that, from Drew's perspective,
can be mined to extract even greater value.
Drew sits in on our deal meetings and that has been worthwhile as well.
His greatest value has really been post-investment, because when we're first
investing, there generally isn't a rich data set for somebody like Drew to play
with. In the deal meetings, because we're investing so early, it's much more
about the technical due diligence and our assessment of the market opportunity.
That's where Brad, Jesse, and I really excel, and that's what our job entails.
Then, as the companies execute their plans and achieve scale, rich data assets
are developed. That's when Drew can come in and provide a valuable lens on
data assets.
Gutierrez:
What are some lessons you've learned from investing in data-
centric companies?
Ehrenberg:
It's interesting that the most valuable companies look a lot like
platforms, but they don't start out that way. They tend to look like companies
with very specific vertical applications. Over time, as success in a particular
use case or vertical is demonstrated, the companies expand into other verticals.
I think that the notion of having a very crisp early use case is vital because
