The missing feedback loop from performance review back to the hiring process means that the hiring process can't get fixed. Until companies start adding that process back in, hiring will never get better.
Perhaps though if one looks at the performance review weighted to a review date as soon after the hiring, and sort of tail off how much weight is given over the coming years it'd make sense.
I've just seen a lot of bad hires get better with time. And some good hires lose steam or become jaded and perform worse over time.
Thus, as messed up as it is, one of the keenest signals is tenacity in the end. And ironically tenacity in preparation for interviews (that Leetcode grind) is somewhat correlated with performance reviews in the long run and perhaps correlated with utility to the company.
That said, "decent" engineers in the long run that don't think outside the box but check their performance review boxes slowly bleed a company's ability to disrupt. I.e., performance reviews need to be expanded a bit to think about the health of the overall company and not just the employee performing their function.
As a large tech organization, I'd prefer a complex distribution of performances over an even distribution any day - because value to tech companies is still influenced by more black swan event type of innovation. But then I have a high "beta" (variation) in terms of what I'm looking for. Companies with more of a utility emphasis perhaps are better served by a hiring process that is "reliable" with a lot of false negatives.
If they widen their expectations, and hire people that they believe they can mentor into net contributors, then their hiring practices should reflect this.
There are many ways a company can make hiring more scientific, including A/B testing (ie. hiring people they normally wouldn't, have more data around how productive new hires are, etc) but I've never seen it over than "copy Google and we should be good."
Because of that, you inevitably get "weird" results like seeing that your best employees often did relatively poorly on interviews (Google did a study that produced exactly that result—their best employees often were those that failed 1 or 2 of their interviews).
But this is just selection bias: these are candidates that got hired! Which just means that they were so spectacular in some other respect that they were able to get an offer /despite/ poor interview performance. It tells you nothing actionable about your interview process.
Really you need to take an experimental approach where you randomly give offers to people who failed the interview, and see how they turn out.
Fundamentally, hiring is simply not an easy problem. There's a small cohort of candidates who can be reasonably confident will perform well in a job (mostly people who have performed a similar job at a competitor) that everyone competes over and a marge larger group of candidates whose possible performance is very hard to judge.