BIG DATA! ANALYTICS! THE NEW OIL!
We’ve been saying this stuff for 5–10 years or more now, and the sheer reality is that most people inside most offices have absolutely no idea what the hell they’re doing when it comes to data. I just went and Googled “How many data experts are there?” and while I can’t find a specific number, in previous articles I’ve seen that about 15,000–20,000 actually exist, and that’s a global number. For context, I think about 1.3 billion people globally have a job. Not a high percentage there in terms of actual data expertise.
There are more issues around data than I could list in a single blog post, so I want to focus on some of the bigger ones quickly, then get to what I would say is the big one. Let’s go through some of the others fast.
Execs and data nerds don’t speak the same language
At most organizations, there are 7–10 people who can legitimately make a decision or advance something forward. You can call them “executives” or “senior leaders” or just “buffoons.” That’s up to you. But a lot of guys in the middle think they move the ball down the field all week. Really they just run around in a circle waiting for one of those 7–10 people to say “OK, you can do this” or “Alright, you can spend money on that.” That’s how work actually works; most people just ignore this fact and tout their own relevance to get through their life. Awesome.
These 7–10 people who can make decisions have a very specific language they are comfortable with, usually around buzzwords from their industry and financial acronyms. They are also pretty busy, and/or their calendar is full. They don’t really have time to learn every nuance of how data was collected and analyzed and what correlations are. Data nerds that I’ve met fucking love data. They want to explain all these formulas they put together. Execs don’t have time for that. Show me the outcome and show me what decision to make. What does this stuff mean? (Now, a good executive would want to know how things were arrived at, but … I mean … time is a precious commodity.)
What businesses actually need are data translators. At most places, tho, the solution is still “Hire some dude with a pedigree education and hope he’s not lying about his data background.”
Gut feel vs. data
As I noted here — yep, I’m pull-quoting myself, ya wrecks →
Work is a very psychological place, although we often forget this and try to drown everything in “logical” processes. (Most processes are just invented to make a middle manager feel as if they’ve controlled a situation properly.) Stephen Dubner, who is smarter and more famous than I am, has also noted that a major problem with “data-driven decisions” is that executives want to believe in their gut. In the mind of some of these guys, they arrived at their perch for a specific set of reasons. If “Big Data” removes some of these reasons, how relevant are they anymore? (Not much.) Work is largely a quest for relevance towards self-worth, so who wants 750 rows of information if guesswork makes you feel better?
That’s the essence of it. No one is going to use data if it makes them less relevant or contradicts their “gut feels” and “instincts about their industry.” I mean, that’s just human psychology.
The very notion of the term “Big Data” implies large and scary data sets that most people would struggle with. Also, the model for organizations around virtually every topic is “Get more of this thing,” and that’s creeped into data too. More data just means more to analyze // more to mess up analyzing, and that’s actually slowing down decision-making. The promise of data was to speed up effective decision-making. We’re regressing, guys.
And now the big one: Fear
Saw this article this morning from Wharton on “digital illiteracy” and I thought it would be interesting. The article actually sucks and basically tells you to make sure you hire people who have used Excel before, but there’s a cool link in there to an American Express (?) article about how Big Data scares and overwhelms people. I actually have two stories about this!
Big Data fear at the agency
Worked at this agency for part of 2018 and 2019. Their hiring and development model was such that about five women became pregnant all at the same time (late 20s), so they were all going on leave at about the same time, and people were scrambling. Within that arc of time, they also laid off 12 people. I was one of those. Hell of a time to be alive, I tell you.
One of the pregnant women was “a data person” at this agency, and you could easily argue she was the only one. So, since she was pregnant for the first time and it was twins, which tend to come early, she had to set up processes for when she’d be gone. We have this big meeting about “data” one morning at 8am. It was decently well-attended and look, the presentation was good and had fun GIFs and all that shit.
But she’s also up there talking about calculations and formulas and cross-tabs and what some of these clients expect and external vendors and this and that, and honestly, just look around this room. 2–3 people were still engaged. Everyone else was (a) terrified or (b) on Instagram. This is the whole deal with data. It’s gotten this religious importance at the leadership level, even though most leaders have no idea what any of it represents — so now it feels big and massive and if I didn’t go to MIT or do well in Pre-Calc, could I possibly contribute to these projects? Fear.
A data story from another gig I had
Had a job a while back where I sent Analytics reports every Friday. Website, apps, etc. Performance stuff. There’s a concept called “the tyranny of old metrics,” meaning that business changes but people cling to old numbers that used to matter. That idea was big-time in play on these emails. Most people had no clue what I was writing about, so I put some jokes and pop culture references in the emails. Eventually that rubbed a few people the wrong way, my boss snarled at me, and a few months later, I was shit-canned out the door two weeks before Thanksgiving. Hierarchy, baby!
So when I’m dead and buried at this joint, another kid takes over the Friday analytics emails. The first one he sends, he’s got about 700 rows of data in it. Mine were just images and text with some numbers sprinkled in. What happens? People go nuts. They’re forwarding his boss. “What is this? I am swamped! No time to read this!” Of course, most people could have deleted it — but people love to bitch, and bitch they did.
This illustrates (to me) a key point about the implementation of big data. It’s not about collecting the data or having it to show. That’s what most companies think. It’s about (a) empathy for how other people want to interact with it and (b) using it for better decisions. That’s it.
And look at that fear around the 700 rows email … the rebuttal emails came in hot and fast to his boss. People were livid. And why? Well, email is sacrosanct for one. And №2? They were scared shitless because they knew this stuff mattered, but they didn’t understand what it meant, so … there goes relevance.
“The data revolution”
We can only get to this if we reduce fear, which means →
- Let employees work on small data projects
- Let them block one hour/day to take an online class about data or processing information
- Let everyone be associated with 1–2 surveys that go out across a year
- Ask actual data-driven questions when you interview
- Include small data projects in hiring assessments if you want to see people’s ability to mess around with stuff
- Make the projects small, guided, and step-by-step so that people don’t feel overwhelmed
- Don’t let the hardcore data people make it scarier for everyone else, especially if you view data as a future competitive advantage
- Don’t let hardcore data people do presentations that showcase massive data sets and cross-tabs and whatever … this scares others
- Slow and steady gets you more people who can contribute.
Those would be my steps. What you got?