-: So how do we actually do it?
How do we get from numbers to narrative, from a pile of data
to this visual impactful narrative that we're talking about?
Basic idea, it's a four-step process, okay.
So step number four is execution,
actually creating data visualizations
and all this other stuff in tools, right,
building something in Tableau
or creating a really compelling web-based story
using JavaScript and HTML and all kinds of crazy stuff,
or making some sexy video and editing in After Effects
and doing some 3-D stuff in Maya, whatever.
This class, we're not here
to talk about execution very much at all.
So we're really focusing
on the first three steps, all right.
Step number one is a series of acronyms that I came up with
that are terrible, okay.
They're bad acronyms, but they have a good shorthand,
the KWYs, rhymes with why, my favorite word,
and they're three very, very important ideas.
So bad acronyms, important ideas.
Let me explain what they are, okay.
So the first of the three KWYs,
and you can see it's a bad acronym, right,
Like what is that even, how do you pronounce that?
This is by the way the best of them
in terms of pronunciation.
So it stands, KWYDIS is how you say it,
and it stands for a very obvious, very important idea.
You need to know what your data is saying
if you're gonna communicate your data, right.
Pretty straightforward.
I'm not gonna linger on this one at all.
You need to understand your data to communicate your data.
Now I will say, by the way, it's on a spectrum, right.
You have data scientists on one end,
how well they understand data.
You have a first grader at the other end,
how well they understand their data.
You know, you're somewhere in the middle probably,
and that's okay.
Wherever you are in that spectrum,
obviously you want to get closer to here,
but wherever you are, you can only communicate your data
based on your data literacy,
whatever level of understanding you do have.
So just bear that in mind.
Now the second of our KWYs is,
terrible acronym, okay, KWYANTH, very awkward,
but it stands for a very important idea.
And this one is worth mentioning
from a couple different directions.
One is this.
Most people understand this idea
at a high level.
They give it lip service,
but do they actually really think deeply about this?
I say, no. Most people sort of skip past this one, okay.
But I cannot overstate how important this is
because, listen, the fact of the matter is
communications is not about you.
Communications is about your audience.
KWYANTH stands for
you have to know what your audience needs to hear.
It is all about them, okay.
And the key word there is needs.
What do they actually need from you?
And the example that I always like to use is this.
In a work setting, your boss might ask you,
"Hey, gimme the sales figures for last quarter."
So you give 'em the sales figures.
Then they say, "Oh, whoa, whoa, whoa.
"I said sales, but you know, I really meant profits.
"What we care about is profits here, not sales."
"Okay, here, boss. Here's the profits."
"Well, I know I said last quarter, but you know,
"I can't think about last quarter at all effectively
"without comparing to the prior year's quarter also."
"Oh, gotcha." So I'm supposed to read your mind, right?
Yeah, that's it. You have to read their mind.
Or better yet, maybe talk to them.
Data storytelling, like really in a lot of communications,
it's like therapy, okay.
They don't know what they want.
They don't know what they need.
Your job is to tease the truth out of them.
Tease the truth out of the data, tease the truth
out of your audience about what they need from the data,
what they're supposed to be doing with that data,
and based on that need, that will drive you
to what you really need to provide them in your data story.
So as an example of that, there's this video.
How would you design an ice cream cone if you knew
they were gonna eat it with their toes, right.
Audience need can be a little bit weird,
a little bit unpredictable,
but it affects how you do things.
And yes, it is about design as well as communications, okay.
So I just love that video.
All right, last but not least of the three KWYs
is this one, the worst one.
You definitely don't know how to pronounce this.
It does have a pronunciation, KWYRWTS, okay.
So I know what my data's saying,
I know what my audience needs to hear. And there's this one.
This is another one that people skip,
and it makes absolutely no sense.
You cannot communicate
unless you know what you really want to say.
Now one thing I haven't said yet is this.
These three KWYS are equally important,
and they must be aligned.
Obviously, communicating data,
it's all about the truth in the data.
Yes, I am a truth teller.
I consider myself a data fiduciary, okay.
My primary responsibility is to the truth in the data. Yes.
I also really care what my audience needs to hear.
Yes, it's about them, but I'm not gonna tell them
what they want to hear that is the opposite
of what the truth in the data's saying.
These have to be aligned.
And the same thing with what I really want to say about it.
What I want to say better align with what the audience needs
and also better align with the truth in the data.
They're equally important. They must be in alignment.
But what does this mean then, what I really want to say?
It means like, all right,
so let's take the example of boss asked me for sales,
but it was really about
the year over year comparison of profits, fine.
But I noticed that the year over year comparison
of profits, which they asked for, says X, Y, or Z,
but I noticed that, the third month in the quarter,
something interesting happened.
So I'm gonna make sure I bring that up.
I really want to point that out to them.
Or that the past two years, the year over year comparison
is X, Y, or Z, but I looked at 10 years ago,
and we're down 50% from there.
There's something I really wanna say about it
that I think they need to hear, and that is in the data,
I'm gonna say it.
I make sure that that comes across in my story.
Otherwise, I'm not doing my job, okay.
So they're all aligned; they're all very important.
If you get these wrong, whether KWYRWTS
or any of the three, honestly, this is your audience, okay.
They will be confused, annoyed,
questioning your credibility.
We don't want that. So really nail the KWYs.
They are critically important ideas.
They must be in alignment, and here's the thing.
Every single decision you make from here forward,
once you have your KWYs, will be guided by those KWYs.
So by the way, and they happen at all levels
in your data communications.
So I have my broad KWYs
about why am I doing this data analysis?
What's the big picture story that I just found in this data?
Then I will have slide-by-slide KWYs.
What do I really need to say at this moment
in the presentation, at this moment, at this moment?
And I will have individual chart
and/or content elements KWYs at every moment throughout.
The point is that, and you don't have to figure out
all your KWYs from the get-go,
but at any moment when your data communicate,
working on a data communications piece,
at any moment you're gonna ask yourself,
oh, I wonder what chart I should use here?
Or how should I design this? Or what should be emphasized?
Or which notes should I add on the page?
Or should I be adding any,
you know, annotations or anything else?
All of those questions, every decision you need to make,
you can then say, oh, the way I can answer that?
The KWYs. What's the data saying here?
What does my audience need from me,
specifically, in a nuanced way?
And what do I really want to say?
These help you make every decision,
so seriously I beg of you,
think of your KWYs always, always, always.