Grounding Numbers | DogDogFish
Grounding Numbers | DogDogFish
There are a bunch of different types of work that are broadly called “data<br>science” but today I’d like to talk about insights. For me,<br>insights work is all about changing minds. Perhaps ‘changing’ is too strong and<br>adversarial a term: if we give a decision maker extra confidence, that’s<br>probably still OK. But the gold-standard of a good insight is that it leads to<br>somebody changing what they were going to do.
It’s much less certain than a bunch of other data work because it deeply<br>involves people and people are deeply unpredictable. If you can sit and work<br>closely with the person you’re trying to influence, it’s much easier to<br>understand what they’re motivated by, what they believe the key facts are, and<br>then how you can fit into their process and offer them value.
But so much of very senior insights work isn’t like that at all, and much more<br>closely resembles research work in nature. You spend a while working on an area<br>and building expertise, then you take a chance. You find something that you<br>think is interesting and should change minds, but are you right? Have you<br>distilled it perfectly into just the right bite-sized chunk? Have you packaged<br>it in just the right way? And then when you launch it, do you hit the right<br>people at the right time?
In my experience, senior executives have a few key<br>grounding numbers: snippets that help shape (and explain) their position on<br>topics.
“I know that the average person on Facebook has 372 friends”
or, every data scientist’s least favourite example:
“People with 10 friends within their first 24 hours are 75% more likely to be<br>retained”
Good insights-based data science work is creating those snippets and getting<br>them to land. I imagine it’s fairly similar to a lot of work in politics, where<br>you’re trying to get a slogan or a data point out into the general<br>consciousness.
However, even after all that work, and even if you got everything right, you can still sometimes<br>miss the mark. Maybe your stakeholder’s priorities have shifted, or they’re<br>getting pressure from elsewhere that they can’t ignore, or they didn’t even<br>read what you shared. You necessarily have<br>less information than them, and so while you might think your thing is<br>critically important, they might disagree.
If all of this doesn’t sound like data work…maybe that’s because it’s not.<br>At senior levels across so many careers, influence becomes the mark of<br>success and your skillset is just the tool you lean upon to have that<br>influence. A senior engineer, designer, user researcher, or data scientist at a tech company has to be technically strong.<br>But they need to know how to have an impact as well, and having an impact means<br>being able to influence whoever makes the decisions. I once read somewhere that<br>by the time you’re a “Senior X” you should be able to pick up anything<br>technically required. To be Staff+, it’s all about how you manage to apply it.
Anyway, I just launched a bit of work and I’ve got no idea if it’s going to<br>land or not. I agonised over it for a few days and polished it as best I could,<br>but now it’s in the lap of the Gods. God-speed, little insight. Land well, and<br>let’s see what tomorrow brings.