How to Care About Data When You Don’t Believe in Math
Here are the titles of seven TED Talks:
- “Own your body’s data”
- “Why you should love statistics”
- “The quantified self”
- “The Mathematics of Love”
- “What’s so sexy about math?”
- “Turning powerful stats into art”
- “How we can find ourselves in data.”
How we can find ourselves in data?
I imagine a precocious young student digging his way through a heap of numbers like it’s a pile of leaves. Late fall. The air is brisk. The student (let’s say he’s a college freshman because college is really when people start trusting this stuff) finds himself buried in a host of numbers — huge 5s, 6s, some heavy 0s — each of which fell from a grand oak tree shaped like a parabola. He was dared to jump in the pile. He hates the way the 6s feel, and the 7s scratch his glasses. His foot is lassoed by a 9. He’ll never get out of the data. He’s found himself in data.
If you, like me, shrug whenever someone says “The data suggests…” your shoulders might be getting tired. But don’t panic. There are small ways you can participate in the statistical conversations taking place in your office right now even if you don’t believe in math. You might even start to build positive relationships with other members of your team.
A few suggestions:
Use data to break creative ties.
Say you’re deciding between creating a video or a still image; a photography shoot or an illustration; a subject line with “You” or “We” in it. This could be a good time to connect with your team’s analysts or to look at those Mailchimp numbers you’ve been ignoring. What’s there to lose? You’re already deadlocked. Think of it as flipping a coin.
Plus, when you present your work to the team, you can defend the decisions you made by saying they were data-led.
Use data to create characters.
Demographic data is everyone’s wet dream (or nightmare – looking at you, Facebook!). But if quantifying the masses is disinteresting to you, a people person, consider applying demographics onto an imaginary consumer of your creation. Draw the character! Dress her up. Add characteristics. Name her!
Why do we obsess over polling data? Why do we worry about miniscule changes in stock prices? Why is data sometimes easier to conceive than people are?
You might not be inspired to know what percentage of your customers “engage with online applications 1-3 times per hour.” But what if that customer were a 40-something named Harold, and his back was so arched from looking at his phone 1-3 times per hour that his body formed a full circle? Would you be inspired to create a brilliant new campaign that depicts Harold rolling his circular body down the street?
Use data to understand how some people think.
If half the population is, in fact, left brain (that’s the analytical one), then understanding data is also about understanding the people who understand data.
Why do we obsess over polling data? Why do we worry about miniscule changes in stock prices? Why is data sometimes easier to conceive than people are? Perhaps the objectiveness, neatness, and universality of data can help to inspire better creative decision-making. Perhaps the project you’re working on right now could be more cohesive or its argument more overt. Perhaps the story you’re writing needs more structure. Is your copy causative or correlative? Can you defend why one sentence you’ve written leads to another?
The next time you must sit through a presentation about analytics, consider asking yourself how you would describe your work to the speaker. Could you conceive your art in terms they would understand? Would that help you reach broader audiences?
Perhaps the objectiveness, neatness, and universality of data can help to inspire better creative decision-making.
We right-brainers should try to do right by our analytical colleagues (if not just for the sake of our former math teachers). We should listen more, ask more questions, and research ideas that bore us.
In fact, I was one of millions who watched the “How we find ourselves in data” TED Talk. Lo and behold, the speaker actually advocates for less reliance on technology and more on human nature. She calls it, “data humanism”. The philosophy all about making sure humans are at the center of critical analysis, rather than trusting data as if it’s some all-knowing God. People first; numbers second. That sounds like a plan to me.
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