One of the more uncomfortable, well-replicated findings in judgment research is that simple statistical formulas — combining a small number of clearly defined variables in a fixed way — routinely match or outperform expert human judgment on prediction tasks the experts consider their specialty. This isn't a claim that expertise is worthless; it's a claim that human judgment introduces inconsistency (the same expert judging the same case differently on different days) that a formula, by definition, never does.
The resistance to this finding tends to be strong and personal, since it can feel like being told expertise itself doesn't matter — but the actual implication is narrower and more useful: for well-defined, repeatable prediction tasks, a validated formula is a genuine improvement, freeing genuine human judgment for the messier, less-structured problems formulas can't handle at all.
Psychologist Paul Meehl reviewed roughly 20 studies comparing expert clinicians' subjective predictions — about things like college grades or parole outcomes — against simple statistical formulas using the exact same input data. In the large majority of these studies, the formula matched or outperformed the human expert, a finding that provoked strong resistance from clinicians who felt their professional expertise was being dismissed. Decades later, economist Orley Ashenfelter developed a formula predicting the eventual market price of a vintage Bordeaux wine years in advance, using only summer temperature and total rainfall data — and it substantially outperformed the subjective early judgments of expert wine critics tasting the young wine, provoking real outrage from wine-tasting traditionalists.