Comment by grayfaced
5 months ago
Hate it in concept (I can't speak to Pave specifically). Metrics are useful if the manager doesn't make hard targets, the data is good and the model is good. How do you model compensation packages? how does 20 days leave compare to unlimited leave? Are two companies with unlimited leave equivalent? When the managers have targets, they're incentivized to massage the data in their favor. So even if you're doing it right, that makes every other companies data suspect.
This also sounds like it will reinforce some negative behaviors. If the data shows that other companies are paying women 80% of their male peers, shouldn't this recommend I also pay women 80%? But I doubt the output will spell it out that way, will I even know it's influencing me this way?
No, you don't set salary bands based on race or sex. That sounds like it would be illegal. The way that bias creeps in is not from data gathering and setting salary ranges, it's from managers bias when they choose from the ranges for candidates.
Setting company wide salary bands actually HELPS fairness in pay by providing objective ways employees can argue that they are underpaid if that's the case.
> it's from managers bias when they choose from the ranges for candidates.
It also comes in from how / if they choose to promote. If they take too long or if they just don't put you up for promotion / reject you, overall earning potential is weakened.
Do this enough times and it becomes a substantial reduction in life-long earnings, life-long title, respect, etc.