I confess, I am one of those people who religiously checks daily COVID-19 reporting, hoping for some, any, sort of signal that things are improving. With my obsession with pandemic data, has come frustrations and reminders for how we interact with data in our professional lives:
Keep it simple.
The attempts at complex data visualisation for the pandemic have been jaw dropping. Google “bad covid data visualisation” and you will get pages of results. As Alex Selby-Boothroyd, Head of Data Journalism at The Economist, writes, “You should always learn something interesting from the chart in just a few seconds.” I’d like to stop there to make a point, but will share the rest of that quote to keep to my own principles: “But you will gain even more by exploring the graphic and spending time with it, just as you would with a full page of text.”
Don’t mislead.
Tableau’s blog explains Alice Casey’s tweet that called out the BBC for its fearmongering visualisation of COVID death rates. And an LSE study found that people don’t understand logarithmic graphs. We’re all tempted to make the data “look good/bad” and take shortcuts, but take a step back to be honest with yourself and your audience.
Sanity check your work.
Do you recall seeing facts like “60% of people being admitted to UK hospitals had two COVID jabs”? Thankfully this was a misstatement and the number was actually 60% are unvaccinated. But STILL that could be alarming if you don’t think through the denominators, per this post from The Guardian.
Manage expectations.
“Data won’t get you a standing ovation; stories will.” That’s Carmine Gallo’s assessment of a success factor behind the likes of Brene Brown and Sheryl Sandberg. Because expectations and context around breakthrough infections weren’t properly set, sensational headlines like the one in my third point above fuel anti-vaxxer “logic”.
Be grateful for what you have.
In the early days of the pandemic, and still today, we remain data poor. From low testing at the beginning, certain countries covering up their data, to the wide definition applied to determine a COVID hospitalisation or death, as this Atlantic article, which inspired me to write this, explains. However, I don’t think I’ve ever met a client that hasn’t claimed their business isn’t “data rich and insight poor”. Now’s a great time to be grateful for what you have. Embark on a data engineering project that’s been at the bottom of your to-do list for months, clean your data, take another look at what is really meaningful to inform business decisions, or take the time to create reporting that actually works for analysts and business leaders.
[ STAGE ]