Yeah, I get that and name narrower ranges in a business context (trying to keep the upper bound from getting too much lower) because most biz-school types don't get that, and tend to think you're full of shit, being passive-aggressive or otherwise deliberately obtuse, or else it doesn't actually matter and they just wanted a happy number to put on a powerpoint and now you're making their life more difficult for no reason.
For that matter they tend to be pretty bad at anything even adjacent to experimental design, but god help you if you point out that the data they're so proud to present to the C-suite next week is, actually, meaningless (rare is the C-suite that'll catch it and call them on it, anyway, so from the perspective of the presenter it's almost beside the point; a disturbing amount of "data driven" leadership is pure fairy dust).
For a good proportion of programmers I'd expect education and professional work experience to have them comfortable with wide estimate ranges being typical and honest for many "90%" estimates, but business-social experience having convinced them, correctly, that honest estimates aren't what a hell of a lot of people actually want and do, "make us appear ignorant or incompetent" (from the book), in actual fact from the perspectives of people who control our budgets and wages.
Yeah, I definitely agree that the business types just don't get it. If you give a wide range, they either think you're messing with them, or are incompetent.
Personally I tend to try to narrow the range as much as possible while keeping my upper bound as fixed as possible, but that doesn't always work either, and I think I still unconsciously try to go too far toward making everyone happy, and underestimate.
I think part of it is just our collective feelings of powerlessness that keeps us in this uncomfortable position. If a significant number of developers were to put their foot down and give real estimates that actually express uncertainty properly, and stick with them, management would start to understand, or at least accept, what's going on. But "getting a bunch of random people to change their behavior all at once" isn't a reliable strategy, so here we are, and here we'll continue to be.
To make things a bit more fair I'd definitely allow that plenty of business-types do get it, but I think enough don't that treating them all like they do before you know them fairly well is probably a bad move, career-wise, especially if you're not senior and important-enough to thrive despite pissing some of them off. Enough either don't understand or don't want honest estimating that the best you can really do is play the game wisely and hope it goes OK, until/unless you develop a rapport with a "good" one. I'd further admit that being one of the "good" ones may not actually be that useful in a business-type, overall, especially so far as their personal career prospects. They're just... to be approached differently.
For that matter they tend to be pretty bad at anything even adjacent to experimental design, but god help you if you point out that the data they're so proud to present to the C-suite next week is, actually, meaningless (rare is the C-suite that'll catch it and call them on it, anyway, so from the perspective of the presenter it's almost beside the point; a disturbing amount of "data driven" leadership is pure fairy dust).
For a good proportion of programmers I'd expect education and professional work experience to have them comfortable with wide estimate ranges being typical and honest for many "90%" estimates, but business-social experience having convinced them, correctly, that honest estimates aren't what a hell of a lot of people actually want and do, "make us appear ignorant or incompetent" (from the book), in actual fact from the perspectives of people who control our budgets and wages.