Wait But Why?



Before we get started, let me reassure you: this is neither a year in review, nor a "my goals for 2018" post. As a person who still feels a little awkward about being his own advocate (despite multiple social media presences as evidence to the contrary), and who openly expresses his fear of thinking out loud, I am reluctant to drag the public along on a tour of my personal points of pride from the last year, nor to let people in on my half-formed ambitions and ideas for the next. When I'm ready for the crowd to hold me responsible for things I say I'm going to do--and when I have specific and measurable milestones to meet--then I'll reveal these ideas to the world, and use the potential shame of falling short serve as additional motivation.

Until then, and today, I want to talk about Why.

Discovering, a few years back, that a worldwide community of Tableau-focused data visualization practitioners existed was a wonderful revelation. Gaining enough professional and personal experience with the tool, getting more confident in the principles of data visualization, and becoming comfortable calling the people who play in the Public space colleagues--and eventually, friends--has been invaluable to me as a human being, living in the world.

It's glorious to see--on what seems like multiple days in a week--an unexpected work of genius from one Tableaunaut or another pop up in my internet feed, cutting through the dreck and banality. Maybe it's art based on math. Maybe it's biting, data-driven social activism. Maybe it's a head-spinning technical achievement. Maybe it's an engagement magnet. Or maybe it's just flat-out beauty.

We all have reasons for participating in our public community, and I'm not unaware that for many participants, the goal is to get better at Tableau because it's part of their job requirements, or their professional ambitions. The fact that many people in our world use Tableau to create infographic-style designs, or artwork, or unsupported visualization types, is wonderful; but it is clearly an off-label use of the software. Other than as a demonstration of what one *can* do with Tableau, it's certainly not how the vast majority of practitioners would ever need to or want to use it for.

So back to Why.

Why are we, as individuals, doing what we're doing in this community?

I can only speak accurately about my own Why. Let me start by going back to 2016. That's when I started participating, occasionally, in the Makeover Monday project. If the topic or the source visualization inspired me (by being interesting or terrible, respectively), then I would download the data and start working on it.

On several occasions, I did not complete a visualization of my own to share with the world; at the time, I was holding myself to a too-high standard, which was, "If I can't teach someone something new about the data or about Tableau, I'm not going to bother posting it publicly."

I certainly learned things on my own from datasets that I didn't complete visualizations for. I learned what I could and couldn't do; I learned what things were harder to achieve than others; and I learned that I wasn't very fast.

But my ego was an obstacle: in hindsight, I realize that I was acting as though I had to be 0% student and 100% teacher. That's not the point of the Makeover Monday project!

Ten years ago, my colleague and friend Melissa was talking about relationships. I don't know where she first heard this phrase, and maybe it isn't uncommon, but I had never heard it before and ever since it has stuck with me. She said, "People say that in a marriage or a relationship everything has to be 50/50. But that's not right. Successful relationships aren't 50/50. They're 100/100."


This advice is applicable not just to relationships, but to many other things in life. I'm going to apply it to participating in public initiatives as well. I was treating MM like it was 0/100, or at best 25/75, where all my learning was done in secret and everything I put out in front of people was teaching.

This was dumb. Who the hell was I to think I couldn't learn in public?

Unfortunately in almost every respect, November 2016 brought with it a horrific disappointment and unbelievably massive professional embarrassment for me. One of the only tiny upsides to being gut-punched by the world was that I was administered prescription-level doses of humility, and found myself with a much different professional profile, come November 9, than I had expected to have on November 7.

Much introspection and recalibration followed. As 2017 dawned, I found that I had, consciously or unconsciously, changed my internal Why.

It was less about "look what I can do," and more about, "let's find out what can be done."

This is why I was much more diligent in completing Makeovers in 2017. (Not 100% of them, though. Somehow, leaving a few of them undone is my way of retaining agency over the project. If I did them all I'd feel like the project was running my life; by doing, like, 48 or 49 of them, but intentionally NOT finishing the remainder, it's my way of saying, "Every week I actively choose to do this," instead of every week being obligated to do it.)

I tried to give some unique looks at whatever the project was for that week. Whether it was interrogating and building on the provided data, or picking a distinctive aesthetic and/or visual metaphor, or even occasionally using a nonstandard chart type, my secondary goal was still to demonstrate options for approaching the challenge that others might not have seen. (I also got on my own little kicks here and there. Like, for awhile I only used Times New Roman; for many weeks, I only did 1000x1000 dashboards; I got bored of infographic style for awhile and made businessy dashboards a few consecutive projects.)

BUT. One thing I NEVER did was download the data and then NOT put something out in public. Whether I was satisfied with what I came up with or not, I forced myself to put it all out to the world. Even when I hated it. And I really did hate some of them.

A funny thing happens when you wince, grit your teeth, and put your work out in public. You find out that it's not as bad as you thought as it was.

(And, in many cases--with equal value to your development--you find out that the "great" thing you put out was not as awesome as you thought it was.) Over time, though, your "bad" work gets better, your "great" work becomes "amazing," your viz muscles gain definition, you gain confidence in your own ability, you take more risks in your designs...and suddenly, without even realizing it, you're there.

You're 100/100.

Now it's 2018. I have a new big-picture Why that is a topic for another time. But in thinking about all of the big and little Whys, I realize that in big projects like Makeover Monday, we only see the Whats. We see what people post as their final visualizations; we can download them and maybe figure out the Hows. But we don't know WHY people make the decisions they make. It's a hidden element of design that can be extraordinarily illuminating.

How do we know why someone chose to pick chart type A over chart type B? How do we know what options they considered? How do we know what parts of a design the creator agonized over, and which parts they never even thought or cared about? We see the result, but not the process; and it's the dozens of Whys throughout the creation process that lead to the result.

What can I do to reveal the Why behind the What and the How?

In many cases, getting true insight into every Why intrinsic to a single design is impractical. Are we going to stand over each others' shoulders and watch them design? Have them explain all their thoughts and concerns as they go? Of course not. However, at least this week, an opportunity seemed to present itself.

I looked briefly at the dataset on data.world and thought it seemed relatively sparse. So, before going any deeper, I decided that I was going to (as I often chose to last year) set myself a secondary goal or two. In this case, I chose a design goal: build a mobile-first viz, and try to figure out if there's any way that such a viz could provide value to a theoretical customer. I also chose a technical goal: go back to the original "rules" of the game and timebox myself to one hour, using only the provided data.

Once I had these parameters in mind, I realized I could actually do a behind-the-scenes video of my design process. I had no idea at the outset what I would actually do with the data (remember, I hadn't done any analysis), but that's part of the fun. I set up my workstation with a visible stopwatch, connected Tableau to the data.world dataset, loaded Photoshop in the background (just in case I was going to do some external graphics), and started recording.

By the end of the hour, I had a completed viz. In all honesty, it's one of my least favorite. I don't think there's a lot of insight to it and there's not a ton of designy elements--partially because of the one-hour restriction, and partially because of the 400px-wide restriction. (And partially, because it's about chickens and isn't silly.) But this goes back to the Why of 2017: post it even if you're not happy with it. Warts and all.


After recording the video, I sped it up so that it fit into three minutes instead of an hour, and annotated it with the thoughts and concerns running through my head while I was making the viz. Plenty of times, it's kind of embarrassing, to see how long I get stuck on something relatively simple, or how much time I waste on things that give very little return. But at the same time, even in its mundanity, it's a pretty good representation of what it actually is like to create a viz. It's not smooth and breezy; it's always a kind of struggle. There's always moments of fits and starts and un-doing and what-was-I-thinking. In fact, it's kind of fun to look at it and realize how it tells the generic story of creative life: nothing is accidental, except the happy accidents; nothing is perfect, it's just finished; nothing goes according to plan, except the part that remains; nothing is magic, but practice can make it seem so.


If the opportunity to do more of these process videos comes up, I intend to do more of them, and probably spend a little more time on the production values next time around (I am by no means a video producer). If other people do their own, I'll watch theirs eagerly. Which people start by making 20 charts and then throw away 18? Which people know what their plan is immediately and never deviate? Which people use the "Analysis" tab? Who likes float and who likes fixed? Who creates their own custom dates? Who immediately jumps to LODs and who sticks with classic Table Calculations? Who starts with a dashboard canvas and fits things into it? Who cares about color? And what tips will we find organically just through watching someone else work? (I am one of one Tableau developers at my office. To those of you in a CoE, congratulations--you don't know how fortunate you are to have other people to learn from in an ad hoc fashion.)

Here's to a 2018 where we learn about each other's little Whys, and where each of us takes the time to consider our individual big-picture Whys.

#why #process #Tableau #MakeoverMonday

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