Data Literacy Struggles

"I help make numbers less scary" was my catchphrase for years. Dashboards and analytics probably aren't the stuff of nightmares for most people, but I've set to see an organization that doesn't struggle with glazed eyes when dashboards show up on screen.

Data is complicated- anyone who's ever tried to make a clean pivot table can tell you that. But making sense of data is even harder- partly because it feels like it uses a different part of our brain, but mostly because it's a skill; one that takes time, and about 30+ cold brew breaks to master.

Data as a Skill

There's no “secret” to being data-literate- yeah, you can take a bootcamp and binge countless videos on YouTube, but like anything, it's a skill you master a little at a time. In practice, this means things like:

• Picking one metric and looking at it weekly, or even daily. Gather a handful of coworkers, set a 2pm meeting, and discuss over a snack. The key here is discuss- it should be a conversation, not a presentation, so “I think this number is interesting but haven’t done anything with it” is a perfectly fine answer. 
• Picking something cool you saw in your industry, explore it a bit, and share it with your team. Maybe your competitor dropped a new announcement on YouTube, and it has about as many views as a little league soccer game recap. Might be it has a crazy number of views- either way, dawn your inner reporter and take a guess as to why, and share it with the team. FWIW, I recommend clients start by looking at their competitor's mistakes, rather than their successes. 

Share the Spotlight

You're having a productive afternoon of clearing Slack reminders, and then BAM- data presentation. Your colleague runs through a series of charts, goes into detail on the finds, asks if there are any questions (to a room of silence) and the meeting's over. Almost every organization has them at one point or another, and I shamelessly raise my hand that I've run a few of them myself.

The reason they fall flat is that data shouldn't be a one-and-done deal, nor should it be perfectly manicured, only to be seen when the analysts hop down from their perch with a new preaching. In practice, getting around this could include:

• Setting a weekly roundtable with at least one person from each team, and every week asking a different one of those people to make a simple presentation on something they thought is interesting. It could be how social for a new product is going, or even how HBO has been advertising their new bingeworthy addition. The focus here is that the meeting should be roughly split between presentation and discussion, without the explicit need for takeaways. You want folks to get experience talking about numbers (after all the best way to learn is to teach) and you want a conversation to happen, even if it means comparing 2 HBO shows that have nothing to do with your industry.
• Finding the most data-savvy people on your team, and having them do a coffee hour. Or better yet, cater from a local donut shop and make it a conference-room event that would make Homer Simpson proud.
• Support from the top by having leads gather and share interesting tidbits themselves- show that data is part of everyone's role, and that time isn't an excuse for not trying. 

A Little Every Day

Going from couch potato to trying to work out 2 hours a day is a recipe for disappointment, right? Similar to how going from an organization that hardly touches data to doing 90 min presentations once a month is the fastest way for a team to lose interest. In practice, better options could be:

• Including one metric (or a different one every week if you're feeling bold) to include in your team's daily standup.
• Subscribing to a news outlet or creator in your industry that mentions data in their article, and including that in your morning scrolling binge.
• If you're in-office, have a TV in a prime spot that rotates between metrics. It could be right near the coffee, and talk about why certain metrics were chosen at your all-hands.

Embrace the Mistakes

Arguably the toughest brick wall to making data a part of your culture is intuition. Or in other words, "I have 10 years experience in my work, and if my experience will set me right 90% of the time, why should I spend hours proving what I already know?" Or in other cases I’ve seen, “why do I need to show data to say what I already know- don’t you trust me?”

Add in the chicken and the egg problem where understanding what data is telling you takes time, and it means that getting insights becomes a full-on chore. 

There's no easy fix here, but an important step is starting with mistakes. This absolutely needs a culture that puts learning over being right, and a team where doing so won't dampen the next office happy hour. The focus here isn't to show off mistakes by itself (it's a lot to ask of people when promotions come into play) but rather that we're all human, and data improves our work. Not because it has all the answers, but because combining talent with numbers means now you're cooking with gas.