We teach means as something somehow fundamental and commonly useful; but they're rarely useful and highly derivative.
But I just finished the book a couple days ago and I’m still trying to wrap my head around how on earth you’d pull that off in software. Doesn’t work with Scrum at all, and management has to be 100% on board or the betrayal when people get punished for “bad” estimates will destroy the company. I’ve only had that kind of trust one time. And maybe half of that level a couple others.
Among other things the reasoning is this: if you give someone two weeks to finish something that takes “about a week” they will start it a week later and chew up all their safety. And if they complete 4 day tasks in three days they’ll delay delivery because they get punished for asking for more time than they need. And further that a lot of these delays aren’t just procrastination, or funny accounting to work on tech debt off the books (though that does happen IME). Instead it’s the consequence of multiple chains having steps that require the same constrained individual or machine. And trying to reserve that resource when the start dates are up in the air.
Forecasting with uncertainty - https://news.ycombinator.com/item?id=22842847 - April 2020 (20 comments)
I think in reality the inputs to these models are a lot less independent than they would like. Even in the example at the start of the article, I suspect that for most folks income from a side hustle and investment rate of return are both highly correlated to the overall economic conditions. Attempting to add statistical rigor to something as open ended as predicting the future feels quixotic.
A few years ago when I met my now-wife, I was paying a mortgage and she was paying rent, and we wanted to get an idea of what we could afford if we wanted to stick with the budget were were already comfortable with. So the inputs were the possible sale price of my house, the possible interest rate of the new mortgage, etc. We experienced what the article describes; while we were quite conservative about each of all of those elements, the 99th percentile was a lot less conservative than the worst-case scenario of each and every input we plugged in, and it gave us an accurate target of what kind of home price we felt we could actually afford.