Data engagement through light clownery
you too can be a lookolympian!
I am not sure how any organization expects to get through hiring someone who is too online without them being annoying in Slack. I’m not joking when I say I’ve had to mute non-critical Slack channels at work to stop myself from posting random stuff in them too often.
In my defense, Slack is a glorified instant messaging platform. If anyone thinks that it’s reasonable to expect humans to not write with IM slang and some level of leetspeak in a LITERAL IMing PLATFORM, they’re absolutely delusional1.
That said—sometimes innocent clownery can actually lead to some helpful exposure that improves corporate engagement with your company’s data. This is how I stumbled on that idea and have been formalizing and re-structuring it ever since.
🍎🍎 What’s cookin’, good lookin?
I am a nosy person who has administrator access to my company’s Looker instance2. I love this part of my job. Looker is an excellent BI platform, and in my humble opinion, is among the most non-technical user-friendly BI platforms out there.
One day, on a lark, I downloaded the top 10 users from the previous week and posted it in our company’s #data slack. I added some playful banter about the top users (it’s not always data team members), tagged the top 3 users and gave them emoji medals, and went on about my day. The following week, I decided to do it again. What the hell, right? It’s fun to see if the rankings change.
Several of my business users started to catch on to and become competitive in this weekly competition, known as the LookOlympics. Competitive banter ensued! Some coworkers tried to outdo each other the following week! LookOlympics was starting to get fun.
I figured I’d start by including a fun fact from the data in this weekly post. Why not learn something about the data as well while we’re ribbing each other about most or least queries sent? Some weeks, the fun fact got completely ignored. Some weeks, it sparked interesting conversations about the data. It’s a shot in the dark what will spark interest, but I try anyways. Why not?
The LookOlympics is now a (mostly) weekly staple of the #data channel at work, and is a reasonably consistent source of getting engagement with our data. On a practical note as well, it helps us track user engagement with Looker. Looker is very expensive, so it’s good to track the percentage of users querying on a rolling 30-day basis to make sure we’re getting our money’s worth.
Beyond all the practical reasons, it’s just an easy way to keep data fun at work.
🍎🍎 The points don’t matter
One day in the #data channel, a sister competition to the LookOlympics was born. Another data team member was sifting through the mountains of data we have to our name and found an interesting fun fact. They posed it to the #data channel as a game show-style question and offered 1,000 points to whoever got the correct answer.
This garnered terrific engagement. Who doesn’t want to compete for fake points that you can then lord over your coworkers’ heads? Beyond that, it also revealed interesting assumptions that my coworkers made about our data.
We work in a really data-intensive field. The whole point of my job is trying to reduce supply chain waste through data, so it’s very much a central part of what we do. I took my teammate’s idea and started occasionally posting my own game show-style questions about the data whenever I came across something interesting.
It’s been very illuminating so far to see that what I thought was perhaps intuitive or common knowledge about our data is not common knowledge at all. I wish I could be more specific, but just project your own company’s data onto this idea and forgive my lack of ability to talk about proprietary stuff3. It turns out my business users have their own ideas about what’s common in the data because they interact with a certain facet of it on a regular basis, but not the data set as a whole.
This is a side of analytical work that I find really interesting and am trying to formulate coherent thoughts around. Currently, all I have are questions.
🍎 What do my business users think is a common problem in our data? Is it actually a problem?
🍎 Are my business users encountering issues that I haven’t been exposed to yet, simply because we have a lot of data to work with?
🍎 Do my business users understand which chunks of our data are very strong and very much ready to support our goals as a company?
People’s perception is pretty much their reality, so I think it’s important to understand where perception might be getting in the way of the reality of your data. Posting silly game show-style questions is actually quite helpful in surfacing some of these disconnects.
Plus, I just like to have fun on Slack. Not everything needs to be serious4.
I’ll die on this hill. You want me to communicate in a professional way with you? Email me. Book a meeting with me. I’ll be professional as hell. But Slack isn’t the place.
I also advocated for Looker to be our BI platform, so I had better be good at it and be comfortable with anyone having a problem coming to me. This has really made me get good at Looker and I’m grateful for that.
I know corporate secrets exist for a reason but boy do they make it hard to break into the tech sector.
not to get morbid but everyone dies eventually so why not frequent your org’s pet channel.