But I think as you indicate, qualitative generally paints the picture, and quantitative validates it.
This is circular logic. If you measure that "coding contribution" nonsense, people's "performance" will be perceived based on that, _especially_ by their direct managers.
I agree that it’s something a manager could over-index on. I’m not sure how to avoid that beyond adopting a mindset of “this is noisy data that sometimes gives you important insights.”
Of course we've all seen varying degrees of this - but these kind of people can only exist because of terrible management. Throwing metrics at the problem just introduces a more insidious version of this individual, one that knows how to game whatever metrics are used (managers especially will do this). I've been on teams where such an individual could thrive for years, even with promotions, and on teams where such an individual would be outed within a week.
In another case, I knew the manager well, having been on his team before. He was effective, empathetic, and inspirational. He was also overworked and perhaps a bit naively assumed good intent from everyone. The data let me explain to him that the coworker was not contributing and he had a real problem.
Detecting slackers efficiently is simply never going to be a top priority. You have to trust your people. Usually it’s incredibly rewarding.
This is called "broken clock shows the right time twice a day."
Also c'mon, fooling commit metrics is silly easy, just _also_ one of the most burn-out and check-out inducing things ever. And at senior level you _HAVE_ to do that these days. You _have_ to inflate them.
Your broken clock isn't free.
For top performers it's more nuanced. In general they will be top of the contribution stats but sometimes if they're doing R&D or hard work then the stats are not very meaningful. But that's why we don't rely on them.
So metrics have their place to inform and color existing perception. But they will rarely change perception completely.