Telling Stories with Data in 3 Steps


SCOTT BERINATO: With data. Everybody’s doing it, right? You’re not doing it? You should be doing it. You’ve been told you
should be doing it. Storytelling with
data is the big thing. [MUSIC PLAYING] Well, it turns out you should
be doing storytelling with data, but it’s a lot easier than
you probably think it is. Once you know the three elements
of a story, setup, conflict, resolution, you can start
telling stories with your data. Setup conflict resolution. Every story ever told
from the beginning of time follows this structure. It’s really that simple. Setup. Charlie Brown runs
toward the ball. Conflict. Lucy takes the ball
away at the last second. Resolution? Ah! And a setup is
just some reality. And by reality, we
just mean a situation. It could be fictional,
but it’s a reality you’ve created for the story. And then you have conflict,
which has changed that reality. Without change,
there is no story. You just have a bored audience. The resolution is
just the new reality that the change creates. So with that in place,
we can now take a chart, and we’re going to break it
down, pull it apart, find the stories in it,
find the setups, the conflicts, the
resolutions, and we’re going to rebuild it as
a storytelling device. [MUSIC PLAYING] OK. Now we’re back with a chart. This is Global Real
Home Price Index. The index is 100 and you see a
bunch of lines for countries. There’s a gray line in there. That’s the aggregate as well. This chart is really
showing home prices in a lot of different
places in the world, and that’s where I’m starting. So, I want to find
the stories in here. And the first thing I
start to notice, really, are a couple of things. I obviously noticed that big
hump on the green line there. That’s Japan. And I noticed that point where
everything comes together. To me, that immediately
says those are probably two places where
there’s conflict, but I realized something
as I’m looking at this, and I’m glad I did,
because otherwise, I would have had
the wrong story. And that is that these home
prices are indexed to 2005. So, the fact they come
together there at 2005 doesn’t mean the
prices came together. That just means
those are the dollars that the people
who made the chart used to show the change
in house prices over time. So, there’s really
no conflict there. And in fact, I think
that’s my setup. That’s where we start, because
that’s where they started. I can still tell those
two stories on the left and on the right,
but I start there instead of at the
beginning of the chart. I can look backward and say,
home prices rose steadily in most places in the
world for 30 years except for in Japan,
which experienced a three decade long bubble, and
that is a perfectly good story. The setup is home prices
rose steadily in most places, except in Japan,
which is the conflict. And the resolution? It experienced this
30 year bubble. And then working from
2005 to the right, I have another story, which is
that there was a smaller house bubble, housing price bubble
in most places except Japan. So now, the story has flipped,
but something different happened this time, and that is
that the market’s bifurcated. And you ended up with three
markets, Australia, Canada, and New Zealand
rising again, looking much like a bubble,
and the rest falling and then rising back
to about 2005 levels. So, I’ve really started to see
a couple of stories emerge here. One, both starting in
2005, because that’s where our prices
start, and one sort of working backward in time,
and one working forward in time. [MUSIC PLAYING] OK, so I’m going to spare
you most of my sketching because it’s so
messy and chaotic, it probably would just
give you a headache. But I did a bunch
of sketching, and I arrived at these final charts. And I’ve split the chart
up into a couple of states. It really helps
your audience focus. So, here’s my setup. You can see it. Prices rose steadily in
most places in the world. I try to use my titles to
actually reflect the story and hear. The steady increase
reflects that setup. Instead of just using a generic
title about global real home prices, which is
boring and not helpful, the title can really do
some work for me here. And then, I want to add
the conflict and resolution state, too. There it is. You can see we’ve added Japan,
Except in Japan in the title, and that conflict and
resolution becomes clear that Japan was this bubble
that lasted 30 years that was different than everywhere else. And you can see as I present
this, it almost looks seamless, as if I’m just showing you
one chart that changes state. So then I’m just going to repeat
this process for going forward. And you see here, I’ve
included my setup, conflict, and resolution
altogether in one state. You see that little
bubble and then you see the bifurcation
of the market. But the most important
thing is, I’ve really highlighted the
elements of the story in both cases and nothing else. I’ve left out any information
that might distract from telling that story. I’ve not focused
on anything that doesn’t matter to telling
that simple story of setup, conflict, and resolution. Narrative is the most
powerful, most human tool we have to communicate. If you can apply
storytelling to your data, it creates an emotional
connection with the audience. They’re not only going to
believe what you show them, they’re going to feel it. [MUSIC PLAYING]

8 Comments

  1. ⚡ Thank you, for the invitation Scott LaPierre from LinkedIn's Harvard Business Review Group.

    What I know for sure is: Data Storytelling is an oxymoron. Data generates from the Left Brain, and Storytelling brews from the Right Brain. However, Story Structure is a bridge to combining both cerebral hemispheres. That's why only the Ambidextrous can turn it into a skill, become a Master, and teach it well like Scott Berinato.

    Again, merci, for always paving a simpler way for us in #Leadership.

  2. Great video! Excellent way to illustrate what's meant by storytelling with data! On the chart and data used in the example here, would it make more sense to use a log scale? The percentage change matters, but a straight index scale with a 2005 reference point distorts that. For example, the change from 0.2 to 1.0 is a huge 5x (400%) increase but is visually represented the same as a 1.0 to 1.8 (80%) increase in the scaling choice here.

    I've read Berinato's "Good Charts" book many times, it's excellent and I highly recommend it.

  3. Great explanation Scott. (We've assigned Good Charts to our Master of Science in Marketing students. It's essential reading for ANYONE who wants to visualize data.)

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