Ask HN: Why is Pave legal?

Experian also sells a similar product

An interesting artifact of the information disparity between the startup executives (who have access to this benchmark data) and the employees (who don't) is that the employee is often wildly off the mark in their expectations, either too low or too high.

There are so many variables at play too that it turns into a negotiation like everything else. Say an employee wants a big raise because they are having their first child are heading towards a higher cost base at home. Say the employer simply says "the salary data shows that your current pay is at the market average".

Well, is the employee truly "average"? Perhaps they're a high performer. Does the average number take into account not only the company dynamics (stage, domain, funding, revenue level, etc)? Not perfectly.

But then on the other side, just because an employee wants a higher salary due to a higher cost structure at home doesn't mean they are automatically entitled to it, right?

Then on the startup side again, the manager is looking at the data and thinking about all the time and cost of replacing this person and realizing it's likely more than the cost of just granting the raise.

Then the HR person comes in and says the salary grid -- whose whole purpose is to provide in theory tight constraints on these conversations -- rules this all out, there's no budget or wiggle room. When the Manager suggests the grid hasn't been updated in a few years, HR takes it personally and tells the person to take it up with the CEO.

So then the CEO gets involved. She knows the employee has a unique view on the technology and market direction and considers them Tier 1 can't-lose-them. She knows the grid is out of date. She looks at the data and thinks that she can justify to herself and the financial plan that it'll be OK to do it, with fingers crossed that this doesn't happen across the board because then their runway will shorten considerably.

So the raise happens.

My point is just that the salary information asymmetry is just one relatively minor aspect to this whole negotiation and in the end I'm not sure it advantages the company all that much.

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?

Uber and AirBnb are essentially illegal taxi and illegal hotel services. Remember taxi medallions? Remember zoning laws? Being illegal is not a showstopper for a startup because they are under a radar, being illegal is not a problem for a large business because they have enough power to not get prosecuted.