I’m combining two closely-related but separate skills here. One is the ability to simple calculations. The other is the ability to know what to calculate, how to do so-called Fermi problems. These problems are named after Enrico Fermi, someone who was known for being able to make rough estimates with little or no data.
A famous example of a Fermi problem is “How many piano tuners are there in New York?” I don’t know whether this goes back to Fermi himself, but it’s the kind of question he would ask. Of course nobody knows exactly how many piano tuners there are in New York, but you could guess about how many piano ownersthere are, how often a piano needs to be tuned, and how many tuners it would take to service this demand.
The piano tuner example is more complicated than the kinds of calculations I have to do on Zoom calls, but it may be the most well-known Fermi problem.
In my work with data privacy, for example, I often have to estimate how common some combination of personal characteristics is. Of course nobody should bet their company on guesses I pull out of the air, but it does help keep a conversation going if I can say on the spot whether something sounds like a privacy risk or not. If a project sounds feasible, then I go back and make things more precise.