welcome to Founders stories today with
me I have Mike Scanlon from Lumosity
thanks Mike for coming on board thank
you Mike so first tell us a little bit
about Lumosity so velocity is an online
training program for your brain it's an
exercise program to help you improve
your memory attention and other
cognitive abilities we launched the site
in 2007 but had been working on it since
2005 the ideas that you know by training
with the right types of exercises you
can develop certain abilities that are
useful throughout the rest of your life
so we launched 2007 and have been
growing the site and also mobile
applications since then this all sort of
emerged further back I started to study
neuroscience about 15 years ago now when
both of my grandmother's were diagnosed
with Alzheimer's disease it's really
lousy disease and realized that we
actually didn't know very much about how
brains work so started to learn more
about it went to grad school was
studying brain plasticity so this is how
your brain changes in response to the
environment and after a few years there
I started to get excited about the
possibility of leveraging your brains
plasticity and the way it changes to
make a product that people could use and
to really become more empowered about
taking control of your own brain so it's
around 2005 or left grad school joined
up with my old friend from college Kunal
Sarkar and Dave Drescher a new friend at
the time has to start the what
eventually became Amasa day that's
awesome and fast-forward to today
I mean eight years later yeah so we were
I mean very humble for those first few
years there were the two or three of us
at a time working either in my apartment
or in cafe we after launching we started
to grow two to three times each year and
so today we're at about 85 people in the
office forty million members of the site
now one of the really interesting things
I think with Lumosity despite this to
aerate and focus thing on is your
linkage into the academic academic realm
I'd love to hear from you a little bit
about what does that relationship look
like and you know how can some of the
audience learn from your experience is
just linking universities to building a
company yeah so that's it's sort of an
interesting story gone through several
stages so coming out of grad school I
was still very tied to the science and
that whole community and I wanted to
make sure that you know the things that
we were releasing were really nicely and
closely translated from the academic
research that was emerging on how to
make really good cognitive training and
so started there built a board of
science advisors to help us to think
about and to identify new areas of work
and we started to use the sort of what
we knew about the basic neuroscience and
cognition to build better exercises
fast-forward a year or two after we
started to get real users on the site
we're collecting all the data from each
person that's using the site so
eventually it's what by you know a
couple years in we have a few million
people that are using the site and we're
tracking everything that they do we know
about their education their age and then
everything about their cognitive
performance how they learn over time
what their good and bad at and so you
can start to do some really novel
research on human cognition now we're
looking at a group of about forty
million people which is the largest
database of human cognitive performance
that's in existence probably by a couple
orders of magnitude so that's really
ends up being really useful for us to
then share back with the research
community so that they can do new
research to better understand the brain
which turns into a virtuous cycle our
mission is really to provide better
training and better tools for improving
yourself one of the the challenges I
know that I certainly had when I was
starting composite is obviously you're
very limited on time I think every
founder is you're trying to recruit and
do all these different avast
the company building I kind of be
curious to hear from you about the time
investment you took to get that outreach
to these various universities with this
data and was the return on that it was a
primarily just goodwill for the
community or did you also end up
recruiting and hiring a lot of the folks
from from the field yeah it's good
question because this ended up being a
total win in terms of efficiency
most of the research collaborators that
are you know people at universities
across the country and other parts of
the world also and found the site first
and then they reached out to us because
they recognized it as potentially
helpful in their research you can run
studies more efficiently when everything
is online and we're saving all the data
for you
so there you know then a probably 100 to
150 research collaborations that began
that way where they reached out to us
and want to run the study fairly
independently so it was actually most of
that research we couldn't have done
without the sort of support of the
research community so that ended up
being actually very efficient you can do
a lot of things at once with just a
small number of people it also creates
the independent veracity it is not you
know this bias or you know conflict of
interest of us publishing our own work
so that ended up being very efficient
from an R&D standpoint and then over
time we have also built a much bigger
internal science team of people that are
coming from academic research and are
working full-time now I'm just coming up
with new and better cognitive training
in ways of testing its effectiveness I'd
love to hear a little more about that
that science team and the engineering
team we had you know those teams Twitter
and it was always obviously really
important to us to make sure that work
that was going on in the research side
you know was directly applied on the
product side yeah which we did you step
back and look at other companies that
doesn't always happen when they have
large research arms sometimes those
effort to don't make it into the product
how how does that work out
today yeah so it's a moving target it
changes over time especially as we've
grown in the earliest days you know if
there was they're up to three but
usually just a couple of us working on
these problems at once and then you're
really sort of bringing together all of
the the science the engineering the
product vision all in - it's pretty
simple then it's getting harder over
time as we try to scale up these efforts
and be able to make a lot more and
better exercises it's the current system
is we have an R&D team that sits right
next to game development team and so
there's certain pretty constant contact
and through iteration cycles so Rd will
usually come up with a basic first idea
here's a training mechanism that we
believe will be beneficial for XYZ then
we'll go you know that idea will be
brought to the game production team and
together it's a sort of a needs to work
very closely together you'll go back and
forth on how to make this really
engaging and a good experience while
maintaining what is so useful about it
one of the things is there's often some
flexibility and the early stages of what
the how the training tasks could evolve
so what Rd brings to the games team
might not end up being exactly what we
produce at the end of the day but in
those cases it's because we can although
something along during the process that
we think will work even better as the
company is kind of grown up and
oftentimes you reach a point we start
saying okay ours or kind of key goals by
team and I'm wondering as the leader on
the research side of the science team
Alou masa T what are the kind of areas
that you're held accountable before from
the CEO so it the Rd metrics are tricky
yeah because you're you're sort of
things often take a very long time they
might be really speculative and may not
work out yeah they want to be taking
risks yeah you want to get the right
balance of actually producing things in
the near-term
but then also sure taking the big swings
for something awesome that might come
mm-hmm couple years down the road so our
right now we're still sort of developing
what are some good metrics to help the
team sort of orient around him and
measure but some of them include so
we've built this set of tests that we
can use to evaluate how well the
training is working it measures a bunch
of basic cognitive abilities and so we
can now in intersperse that into the
training every few months the customers
will take this test
mm-hm and this is a measure of how much
the training is benefitting them more
broadly than just doing the training
itself so that's a great measure of
exactly what it's supposed to do which
is to help people improve their
cognition so we're trying to orient the
metrics around improving your outcomes
on these tests now that ends up being a
very broad mandate because you could
imagine improving metrics on these
cognitive tests either through getting
you know making something that works
better
mm-hm where you could make something
that people like more so they train
longer and if they train longer on
something that twice as long on
something that works half as well you
getting the same result we think this is
a good way to think about it then you're
not sort of too narrowly focused on I
got to do it this way because this is
the vo mean that your calculator about
we like to orient get things oriented a
little bit broader perspective on what
the the real goal is have a question on
culture because I mean I can greatly
empathize with the research efforts that
you're describing of kind of long term
you know big high risk efforts that
you're that you're leading you have this
other engineering team that has
deadlines and you know trying to make
sure they keep the trains kind of
running on time and you know I've seen
scenarios or sometimes there could be
tension between anyway those guys are on
a 12 month horizon and we're on you know
a weekly two-week horizon yeah have you
run into that and if so like what did
you do you found that that kind of
really helped with a potential cultural
challenge we've seen some things like
that there the world as part of the rdrd
team that's looking at much more into
the future for longer-term speculative
work is fairly removed from the
engineering and production side because
you're not delivering products on these
really speculative stuff where it gets a
little bit more interesting as at the
interface where you know the next game
that you want to release and then how
does that kind of get passed through and
they're definitely you know challenges
there I think that the one key thing
that has really helped to resolve a lot
of those challenges is that everyone has
the same mission at the end of the day I
think everyone at our company is in part
there because they believe in the
mission of improving people's brain
health and so you can resolve a lot of
conflict by taking a stepping back to
that Senator point I think that's
fantastic Mike thanks so much for coming
coming Don today a federal or ease and
thank you all for watching and we'll see
you next time