path: root/transcripts/startup-science-2012/elizabeth-iorns-science-exchange.mdwn

Science Exchange Elizabeth Iorns

So, um. We started thinking yesterday about what to talk here. I thought about
the different aspects of bringing the tech ideas into the science space. Some
of the key points that Joseph wrote about was catalyzing the formation of teams
and companies that positively transform science. The emergence of a new type of
science entrepreneurs to .. effect contemporary relationship. That's
inspirational and inspiring and it's exciting to think about how to encourage
scientists to consider this alongside the academic careers that we all know
about.

I came from a traditional academic career path. I did my PhD in London and I
did a postdoc at University of Miami. I was ddoing academic research until I
realized that there were problems that I could address with technology, and it
was more exciting than running a lab. So then I founded scienceexchange.com.
Today I hope to share some lessons about starting a company that might help
other scientists with the transfer. I am really happy to help people make a
transition to this career.

Just a brief introduction to what Science Exchange is.. it's an online market
space where people pay for services from institutions. It wsa for building
access to expertise and infrastructure in a marketplace. Instead of a local
core facility at your own institution, what about a portal where researchers
could transact on expertise available outside their institution and globally.

So we were founded last year in May, we launched in August, we are based in
Palo Alto and took part in the ycombinator S11 program. We built our product
quickly, we raised a seed round of financing including Jason Harowitz, and
Cross Sight amongst others. So we now are used by more than 1000 core
facilities across the United States. There are some nice brand names like MIT,
Harvard and Stanford.

We have critical mass and we have users accessing core facilities they wouldn't
have had access to anyway. I don't want to talk about this. I want to talk
about why I created Science Exchange. I would be happy to answer questions
about creating a startup in this space.

You need to solve a real problem. Often there is technology searching for
problems, especially the young guys coming into ycombinator. I was one of only
two women out of 164 people in the program. Almost everyone was young, white
males, all engineers straight out of college. They are so talented and
brilliant- some of the smartest people I've ever interacted with- they were
looking for problems and weren't sure what to use these skills to solve. When
thinking about building a startup, you need to research the market and maek
sure that the problem exists. If you are going to make a tech startup, building
a small one is just as hard as a big one so you might as well solve a hard
problem.

So the Science Exchange mission was that core facilities is increasingly
important, but access is just as hard. So we talked with a lot of scientists,
and I was able to understand as a scientist that it was a problem that people
experienced on a daily basis. So we were able to get numbers on $100B spent on
research every year, much of that through things other than core facilities,
but increasingly so.

So, do something you're really passionate about. I love this quote from Paul
Graham. The best problems to solve are the ones that effect you personally. You
have to understad the problem that you are trying to address. Often this can be
hard when you are starting a company. The problem you are solving has to be
important. You have to have that connection. For me and my own research, my
credit card balance was effected by the lack of a good marketplace.

Make a start. It's hard to make that first step, that initial step into this
world, especially if you're not from the tech community. It can be really
scary, and you might not know what to do to start a company. But one of the
things that... and get on with building a company.

You need to share your idea. One of the problems was that people thought their
ideas would be stolen. You shouldn't tell anyone, and my cofounders were both
in the tech startup world. No, that's not the way you do it, tell everyone
about your idea so that you can get feedback and build something that people
really want. That was a valuable lesson. We started with market research and we
thought about the problem, and whether people found this to be a problem, and
then we applied to ycombinator. That was from February 2011 to taking
ycombinator in May. Making a start and making progress was what allowed us to
make a successful company.

Surround yourself with the right people. If you actually look at all these
companies, these startups were often done by a single founder. When you're
looking for investment, or skills required to actually get up and running, it's
important to have diversity in that team so that you can handle any of the
problems that you will be addressing. Science Exchange has 3 very different
founders. I am an academic scientist, we have a technical engineer and a
business person. That diversity has really helped us with understanding all
sorts of different problems that has helped us with building a company.

Do things that don't scale. If you have a really complicated accounting,
dealing with transactions, I have to build this technology around that.. and
then being a part of ycombinator is valuable because Paul was like, that's a
great problem to have. You should just get started, start taking money
manually, and then you will figure it out when you need to. Only scale when you
need to. Doing things manually was actually really important, to understand our
customers and see what they needed, and that when we needed to scale that we
were doing so in an important way. Customer service is super valuable when you
are starting.

The sixth point is to listen to your users. This goes back to the customer
support. This is a really interesting quote. Customers are used to companies
ignoring them. Some startups have fanatic loyalty from their initial users..
might not have the best product, or might have a shitty website with errors,
but they reach out and engage with the users, and that personal interaction
creates a community around the product that is extremely loyal. That was
something really valuable from the start, it was making sure that when they
tweeted that we would reply to them, we were calling them and visiting them and
making sure they feel involved in the community of Science Exchange.

Don't always do what they say. If they have a problem, you should listen, but
their solution might not be the best solution. Your company is your company,
and it is up to you that to figure out how to solve the problem most optimally.

The seventh one is iterate quickly. This is true of startups in general.
Iterating enough times until you find something that works until you run out of
money. That's really a startup. I think when you have this really early users
that interacted with you and are your community and driving your growth, you
can listen to them, they want you to speak and improve quickly, they don't want
you to just sit around. So, that's really important for iterating quickly.

When we first launched, our product was post a project and we would find
someone to do the experiment for you. That was a frustrating experience. But we
physically went to the person, and we checked if the person was able to do it.
You don't know if anyone would be able to help you, we switched from this
auction model to an order model. We built a database where we exposed the value
from the start, we had the ability to see and filter, see the feedback on using
those core facilities from other users. So exposing the site right from the
interaction of the site, and that was frustrating for people who were posting
projects, but it helped providers because they didn't have to post and miss out
on work. So when someone was actually requesting, then they were more likely to
actually order and they already went through that process.

Get the right investors and advisors. This is something that I never realized
before coming to SV. When we talk about the type of startups that we're talking
about today, they are around infrastructure changes and technology, they are
not the equivalent of biotech startups. We're facing a marketplace that is
similar to Airbnb or Odesk that are very different from the problems that
Genentech faced. These are very different advisors from Biotech companies. THis
is probably true of other scientist startups. ResearchGate has more
similarities to Kaggle or Faceboeok, not the other sites. PeerJ is more similar
towards sites like youtube or spotify that have to license content from
providers.

For us when we were thinking about adivsors, we looked at talents that could
help us with an online marketplace and understand the things we need to put in
place. We had Jason Horowotizz, including the OpenTable person, and the Airbnb
person and the former CEO of Ebay, and this helped us figure out our problems.

The ninth lesson is to commit. I think this is something that is very hard to
do. It is very scary that you need to have these backup plans, I need to keep
my day job and all of tehse kind of things that you put in place where, if it
does fail- which it will, by the way- that you are not kept high and dry. I
think that's a self-defeating attitude. If you truly believe that your startup
is a good idea, and you're executing on it well, then you need to commit to it
and go to it. There is a limited runway and enthusiastic energy. When you
start, you get enthusiastic, make the phone calls and do all the hard things
that are not fun. Over time you will lose that energy, so you do need to make
progress so that you don't lose your energy, otherwise your startup will fail.

Finally, you need to have fun. At Science Exchange, it's the only time you will
ever have to work with people you choose with and to do the things you want to
do. We want to make sure our team is happy with each other, we're good friends,
we do things outside of work as well as working on the startup. That's what we
focus on at Science Exchange as well.

I am really happy to make introductions for people, or giving advice and doing
science startups. You can reach me at elizabeth@scienceexchange.com.

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It was interesting that you compared yourself more to Airbnb or Peerj or Ebay
or something like that. That's really interesting. Could you explain on what
you see, what are the core similarities between Science Exchange and Airbnb?

For us, Airbnb is a company that we looked to for inspiration. When you think
about airbnb, we think about people renting out their house to strangers.
That's a pretty scary prospect. They have to make sure that people trust them,
they have to build a community not afraid to stay with strangers, and it's the
same thing with Science Exchange. It's not about selling something online, it's
your job- it costs a lot of money- these transcations are thousands of dollars,
so that ability to have trust in the site, and that we look at verification and
connections between our researchers in the facilities that they work at and all
of thsoe aspects that we look to Airbnb for andd their problems, and what can
we do at Science Exchange.

To tie that back to the theme of today, what do you think the effects are on
the overall marketplace of skills would be, if there are more people taking
that up? Could it make more efficient science? What is the opportunity there?

It would make it a lot more efficient and a lot faster. There is this culture
in science to do everything yourself, or to learn each experiment,a nd a lot of
the time that will be related to quality issues in academic research and
reproducibility. Using core facilities can help on these core points. These
people do these experiments all the time. That's all they do. They don't have
to publish, they just provide data back. They don't have an interest in what
the outcome is. There are none of the original perverse incentive. Instead of
outdated revenue model, it's a parallel approach to funding science.

Quick question: when you were raising money, did you have to envangelizing
science and explain the flows of moneys, did you have to educate the investment
community about science? We find that they don't know science.

I think that VCs don't know about academic science. For me, I was really lucky
that there were people like academia.edu that had gone out and rallied the VCs
about the academic world. We weren't the first ones. For us, it's all about the
economics and doing a value proposition for them. It's very easy to sort of go
in there and say this is how much money is in academic research, these are the
trends, this is where it's being spent, here's the collaboration for core
facilities, so going out there and .. from an understanding of the academic
research world, just say look at it as a market and an ability to disrupt a
market. That's how we convinced them.

Could you share what your model is? It's our payment platform. We are totally
open access, we're free for core facilities to list, and free for researchers.
Our whole thing is that it's too hard for people to transact money between
institutions. The big barrier was that when you work with a university, you
can't just pay money to anyone, you have to have an approved vendor to receive
that money. That process is very time consuming, and there's these university
purchasing system. So we ewent throug hthe university purcahsing system. So the
researchers can now use the researcher somewhere else, and figure out how they
are going to transact otherwise. So then we charge a transaction fee.

From the standpoint of justifying expenditures on a research budget? No, that's
an issue. We've never had an issue in terms of service in terms of how much to
allocate to different things. They have a lot of discretion in how they spend
that money- they could buy the reagents and do it with their own research
staff, or they can use their core facility or some other core facility. Yes,
we're totally open, we want to be a central market, so we're looking for
anybody to find anything. It's not restricted at all. We verify everybody who
is a provider, but you can be a private consultant, you can be a CRO, you can
be a commercial service provider or an academic core faciltiy. Yes, all members
are vetted. We have a manual approval process for providers, we physically
speak with people and check out every facility on our site, so we create the
content on the site. We want to make sure that our experimental classification
system si correct, and that's really hard if you have community generated
information, so it's really hard for them to know what they're buying, so we
just do that manually.

Thank you for a very nice talk. You are solving a lot of dilemmas for the
research community is that, I hope this is part of your model, you're very
talented and bright, the ability to notice how much effective flux is going
through different parts of research is a wonderful metric for being able to
talk about the monetization of the science budget... if scientists forget, but
financial anylsts like myself, the velocity of money, the fact that you put so
much into a particular experiment or somebody performing one of your services,
that creates an opportunity for someone else to do the same, so it speeds up,
so it advances it internally, so you can do a velocity indicator for turning
things around. THis is very attractive to the funding cycle as well. It allows
people to fund more quickly. So if I add a little more, it goes down the same
path and now it's a big industry.. so communicating that back and publicizing
that as an effect, may cause a tremendous attraction from the financial
inddustry... historically, that's how industries surveyed each other.
Scientists don't tend to exploit that.

We try to track, at a very detailed level, around the use of our site. Metrics.
In terms of value proposition that we offer is the first time, where money is
being spent on experiments. Not just local, but globally. It's valuable on that
level. When you look at the published literature, only 1% of experiments are
published. Which money is being spent where? This is what funding agencies are
interested in looking in. They know that most people are spending money on
which experiment now, and then target them directly in real time.