Sebastian Wernicke: How to use data to make a hit TV show
Sebastian Wernicke - Data scientist
After making a splash in the field of bioinformatics, Sebastian Wernicke moved on to the corporate sphere, where he motivates and manages multidimensional projects. Full bio
have probably never heard about,
minutes of your life on April 19, 2013.
for 22 very entertaining minutes,
about three years ago.
is a senior executive with Amazon Studios.
company of Amazon.
as "movies, TV, technology, tacos."
because it's his responsibility
that Amazon is going to make.
a highly competitive space.
TV shows already out there,
that are really, really great.
of this curve here.
is the rating distribution
on the website IMDB,
how many shows get that rating.
of nine points or higher, that's a winner.
"Game of Thrones," "The Wire,"
your brain is basically like,
here on that end,
"Toddlers and Tiaras" --
on that end of the curve.
getting on the left end of the curve,
some serious brainpower
is this middle bulge here,
that aren't really good or really bad,
that he's really on the right end of this.
doing something like this,
to take any chances.
he holds a competition.
through an evaluation,
of each one of these shows
for everyone to watch.
is giving out free stuff,
are watching those episodes.
while they're watching their shows,
by Roy Price and his team,
when somebody presses pause,
what parts they watch again.
to have those data points
which show they should make.
so they collect all the data,
and an answer emerges,
about four Republican US Senators."
remember that show, actually,
the average of this curve here is at 7.4,
and his team were aiming for.
at about the same time,
to land a top show using data analysis,
the Chief Content Officer of Netflix,
he's on a constant mission
a little bit differently.
what he did -- and his team of course --
they already had about Netflix viewers,
they give their shows,
what shows people like, and so on.
about the audience:
what kind of actors.
all of these pieces together,
of course, nailed it with that show,
a 9.1 rating on this curve,
where they wanted it to be.
what happened here?
millions of data points,
beautifully for one of them,
that this should be working all the time.
millions of data points
to make a pretty good decision.
of statistics to rely on.
with very powerful computers.
is good TV, right?
does not work that way,
where we're turning to data more and more
that go far beyond TV.
is a software company,
with that software,
it means you're in prison.
and they apply for parole,
data analysis software from that company
whether to grant that parole.
as Amazon and Netflix,
a TV show is going to be good or bad,
is going to be good or bad.
that can be pretty bad,
I guess, even worse.
some evidence that this data analysis,
does not always produce optimum results.
like Multi-Health Systems
companies get it wrong.
that they were able, with data analysis,
the nasty kind of flu,
on their Google searches.
and it made a big splash in the news,
of scientific success:
for year after year after year,
from the journal "Nature."
Amazon and Google,
into real-life decision-making --
that data is helping.
a lot of this struggle with data myself,
where lots of very smart people
to make pretty serious decisions
or developing a drug.
I've noticed a sort of pattern
about the difference
decision-making with data
and it goes something like this.
solving a complex problem,
apart into its bits and pieces
those bits and pieces,
you do the second part.
back together again
have to do it over again,
back together again.
no matter how powerful,
and understanding its pieces.
back together again
and we all have it,
back together again,
that Netflix was so successful,
where they belong in the process.
lots of pieces about their audience
been able to understand at that depth,
to take all these bits and pieces
and make a show like "House of Cards,"
made that decision to license that show,
that they were taking
with that decision.
they did it the wrong way around.
to drive their decision-making,
their competition of TV ideas,
to make as a show.
a very safe decision for them,
point at the data, saying,
results that they were hoping for.
useful tool to make better decisions,
to drive those decisions.
data is just a tool,
I find this device here quite useful.
device to use.
a yes or no question,
and then you get an answer --
in this window in real time.
so I've made some decisions in my life
I should have just listened to the ball.
if you have the data available,
much more sophisticated,
to come to a better decision.
and smarter and smarter,
to make the decisions
message, in fact,
of huge amounts of data,
on the right end of the curve.
About the speaker:Sebastian Wernicke - Data scientist
After making a splash in the field of bioinformatics, Sebastian Wernicke moved on to the corporate sphere, where he motivates and manages multidimensional projects.
Why you should listen
Dr. Sebastian Wernicke heads the data science department at Solon, a Munich-based consultancy supporting companies and investors in media, entertainment, telecoms, and technology industries. Wernicke originally studied bioinformatics and previously led the strategy and growth of Seven Bridges Genomics, a Cambridge-based startup that builds platforms for genetic analysis.
Before his career in statistics began, Wernicke worked stints as both a paramedic and successful short animated filmmaker. He's also the author of the TEDPad app, an irreverent tool for creating an infinite number of "amazing and really bad" and mostly completely meaningless talks. He's the author of the statistically authoritative and yet completely ridiculous "How to Give the Perfect TEDTalk."
Sebastian Wernicke | Speaker | TED.com