Eg. if I guess NYC population is 10M, with every 100th household having a piano, I can guess there are 100k pianos in NYC. If each of them needs tuning once every two years, that's 50k tunes each year. That's roughly 1k tunes each week, which, if a tuner can do 2 a day (5 work days per week), is 100 tuners.
And then it'd be worth comparing to tuning of venue pianos which are tuned more frequently: let's say 10k venues with pianos requiring tuning every month, or 2k tunes a week. So another 200 tuners.
You can also talk about pattern of work instead of market demands (eg most tuners only get 1 tune a week, so we can multiply the number of tuners by 10), just to show off you are ignoring other variables knowingly.
Obviously, each of the guesses has a large error margin, and errors multiply, so you can be off by way more than a single order of magnitude.
But just coming up with things to include in your calculation, and not being scared of exploring such random situations with little data you know, signals some generic problem solving ability.
Eg for a better answer, I now know I need exact number of people and venues in NYC, I need to ask tuners how often are pianos tuned, get some data on how frequent are pianos in homes, how long does a tune take, etc.
While I think I am decent at these questions, and I do believe they signal a very generic problem solving ability, I agree they are terrible interview questions for most software engineering roles, since you rarely hire for such generic ability, and might even get more out of a more specific question/test..