WHAT DAN LEVY TAUGHT ME ABOUT DATA STORYTELLING
It finally happened. In the summer of 2018, I became insta-famous in Canada for about 25 minutes. I was living a bi-coastal shuffle and spending a lot of time on airplanes while traveling between Seattle and Philadelphia. To pass the hours, I began re-watching Schitt’s Creek, a beloved television show that recently rocked the entertainment scene. While I watched and chuckled in my airplane seat, I started doodling elements of the show as a way to better appreciate the characters and savor the humor. Moira’s outlandish wigs and David’s high-fashion sweaters were of particular note. As each scene and episode unfolded, I doodled.
I got really interested in this exercise. It helped those plane hours fly by, but also became an analytical challenge. At some point I even made a spreadsheet to check my work and fill in any unseen gaps. I recorded the season, the episode, a character quote while wearing the item, and an image. I wanted them all and I wanted them in order. The analytical side of my mind wouldn’t have it any other way.
My whisper of insta-fame arrived when the multi-talented Lucky Bromhead, a member of the Schitt’s makeup team, shared some of my doodles and caught the attention of Schitt’s fans, including the marvelous Dan Levy. I made some posters. I sold a few. I considered it an accomplishment that my Wix site and web domain were no longer a black hole of money. It was my first ever break-even hobby.
In case you missed the sarcasm, my insta handle – “@TheDataArtist” – is not famous. I have a little more than a thousand followers. They’re mostly queer Canadian folks, which I love, but none of them know or care about me. The interesting thing about social media in this context is exposing yourself to other peoples’ ideas and opinions about whatever you’re posting. In this case, I got some flak for claiming “data” relative to these Schitt’s Creek doodles. “This isn’t data,” they’d say.
Let me start by saying I understand this feedback. My spreadsheet doesn’t have what we normally categorize as “data,” or “metrics.” And even if it did, any quantifiable data in my spreadsheet certainly did not make it into my final poster design. In response to these fan-fair critiques, I decided, “I guess it’s just information.” I was unconcerned and sleeping fine at night.
The creators of Schitt’s Creek and a book publisher decided to include my doodles in an official tie-in coffee table book. This was pretty fun and a new experience for me. Entertainment Weekly featured a preview of the project complete with notes from those that worked on the show. And that’s when Dan Levy lit up my mind a little.
"DAVID'S SWEATERS TELL INTERESTING STORIES ABOUT HIS CHARACTER OVER THE SIX SEASONS OF OUR SHOW. During Season one he wore a lot more button-up shirts and his aesthetic was a little more tightly wound. Then Over the course of the series, we very consciously unwound him. he stopped wearing button-up shirts and the aesthetic got softer. We were using softer knits, we were using fuzzier textures, anything we could do to show that he was becoming more and more comfortable with himself and that he has less and less to prove."
Creator of Schitt's Creek
When I read Dan's story, I saw data. More specifically, I saw how chronology and comprehensiveness are key pieces to telling this story. Let’s roll back to some basics to see if I can explain what’s bouncing around my head.
Data exists because we collect it. And to have any confidence in data, we need to feel good about the way it was collected. Across most natural and social science disciplines, this means applying the scientific method to ensure biases are checked and confirm the data justly represents the topic at hand. In business, it might mean ensuring that all available data is present and accounted for, as well as insuring that our apps and websites are set up correctly to gather the data we need. In the case of my Schitt’s Creek doodles, this meant watching every episode and making a diligent record of every wig and sweater. If I showed you my poster of David’s sweaters and you learned I only watched three- quarters of the episodes, you’d rightfully call me out on my claim of having a comprehensive display of all the sweaters. My data collection method would be highly suspect and undermine the integrity of the project. What if there were sweaters in the episodes I failed to watch? What if I missed some? In short, the way we collect data matters.
When I think about data and the way we store it, prepare it, and analyze it, it highlights a few very important end goals like accuracy, access, and comprehensiveness. Achieving these goals is made possible because of the way we structure data, or the way we build data models. Good data models position humans, for all our limitations, to wield massive amounts of information that lay beyond what our minds can handle.
DERIVING INFORMATION FROM DATA
With that data model foundation, we can conduct analysis and extract pieces of information. Those learnings, when combined with narrative and maybe some visuals, are the building blocks of the stories we tell. Or they should be.
There’s been a lot of conversation recently about information, disinformation, and misinformation. And while a deep dive into those terms is out of the scope of this post, one point is relevant: the stories we tell each other should reflect accurate information. Deriving accurate information requires a well-governed dataset that was collected using rigorous methods. It also requires sound analytical judgement about what the data suggests is true. The process of deriving information from data is an important step because a single data set doesn’t hold just one story.
THE STORIES WE TELL
There is a relationship between data, information, and stories. There might even be a moral imperative to understanding and embracing this relationship, if only to ensure we’re telling each other true, fact-based stories when it’s important we do so. How do we know if a story is true? We think critically about the information we’ve heard. If there are questions, we dig deeper to investigate the data, the way it was collected, and the information it allegedly supports. Telling stories with integrity is important and from what I can tell, it starts with the analytical rigor that data and data collection methods provide.
At the risk of exposing how small and limited my brain is, I’ll tell you that’s exactly what my Schitt’s Creek spreadsheet provided me: a little analytical rigor. It held an accurate and complete chronology of David’s wardrobe in a way my brain couldn’t. When I think about Dan’s wardrobe commentary relative to data, something clicks. Data helps me understand the story. It helps me notice things I otherwise wouldn’t have. It helps me see and understand the meaning behind this curated wardrobe. To fully appreciate the story, I rely on what my spreadsheet provides: an accurate, chronological, comprehensive record of David’s sweaters.
If we take a closer look, data can help us better understand what Dan Levy created with this layered, inspiring, and mold-breaking character.