I was asked to speak at a conference for data analysts yesterday. Of course, the big question on their minds was “what happens to our jobs?” followed by “what should we learn/teach?”
These are good questions, and many different specialties are asking them. I always reach back to the idea that, 150 years ago, 2% of the world population wasn’t working in agriculture, and now 2% are. That’s a huge shift! It would almost certainly have been impossible to explain to a farm worker back then what jobs would look like now - so much of what we do is built up on other capabilities and needs.
But thinking about data analysis specifically, it occurred to me that I’ve never had a team say “gee, we have so much analytical capability, we don’t know what to do with it!” In fact, the opposite is of course always true: we always want more. And analysis is kind of funny in that questions beget more questions: as a manager, you often have to hold back because the team can only do so much.
But now we are in a world where “everyone” can do some aspect of this role. That’s actually great! Cheap experiments are the heart of innovation (and cheap questions are the same thing, every experiment is just a question in a different form). Why? Because the good ideas are usually surprising and counterintuitive - if they’re also costly to explore, it makes it very hard to look at them. Cheap, easy, fast experiments are vital. So, it’s really great that we have more capacity now.
So what you you learn, and what’s the value of professional analysts? Well, think about the most basic bit of statistical understanding: mean vs median. If you don’t understand this, you can’t really ask meaningful questions. “Look at that room! Everyone is a billionaire on average! (actually, it’s Bill Gates and 5 other random people - you want to look at median, not mean).
So even though the tools are more available, and the mechanics are easier to drive (so things like R are less valuable to memorize), knowing what to ask and how to understand it are going to be more and more important - not just in this field, but in all of them.
Regarding the 2% argument I'm just a bit concerned about the speed at which the change will happen. But ofc we won't run out ot things to do anytime soon 😅
For the median argument, looking for a mentor could be the right move for who really has run out of ideas/questions :).
What's your take on the topic?