Roy Price uses data from viewers watching pilot episodes of shows to find really great shows for Amazon Studios. Ted Sarandos at Netflix also uses viewer data like ratings and watch histories to discover what kinds of shows audiences like. However, relying too heavily on data analysis can be problematic as even large companies sometimes get the analysis wrong, so human judgment is still important.

2.  No matter how
powerful, data is just
a tool
 Data is of course a
massively useful tool to
make better
decisions, but things
go wrong when data
starts to drive those
decisions.

3. IMDB Ratings Graph
Everyone wants to be
on the right end,
No one likes the left.
No one wants to end
up in the middle- as
an average show!

4.  Roy Price is a senior
executive with Amazon
Studios. So he can't just
choose any show. He has
to find shows that are
really, really great. So in
other words, he has to find
shows that are on the very
right end of the curve.

So he takes a bunch of
ideas forTV shows, and
from those ideas, through
an evaluation, they select
eight candidates forTV
shows, and then he just
makes the first episode of
each one of these shows
and puts them online for
free for everyone to
watch. So millions of
viewers are watching those
episodes.

5. Result Is?
Who saw this?

7.  Ted Sarandos, who is the Chief
Content Officer of Netflix, was
on a mission to find that great
TV show, and he uses data as
well to do that, except he does
it a little bit differently. So
instead of holding a
competition, what he did -- --
was they looked at all the data
they already had about Netflix
viewers, the ratings they give
their shows, the viewing
histories, what shows people
like, and so on.
 And then they use that
data to discover all of these
little bits and pieces about
the audience: what kinds of
shows they like, what kind
of producers, what kind of
actors.

8. Result is?
Who hasent seen this!!

10.  But if data analysis does not
work correctly, then it actually
gets a little scary, because we
live in a time where we're
turning to data more and
more to make very serious
decisions that go far beyond
TV.

11.  And unfortunately, there is actually some
evidence that this data analysis, despite
having lots of data, does not always produce
optimum results. Even the most data-savvy
companies get it wrong.Yes, even Google
gets it wrong sometimes.

12. Despite all those failures, data is
moving rapidly into real-life
decision-making -- into the
workplace, law
enforcement, medicine. So we
should better make sure that
data is helping.

13.  It's always those two things: taking apart and
putting back together again.
 Data analysis is only good for the first part.
no matter how powerful, can only help you
taking a problem apart and understanding its
pieces. It's not suited to put those pieces back
together again to come to a
conclusion.There's another tool that can do
that, and we all have it, and that tool is the
brain

15. Keep taking risks.