Are salary transparency tools actually helping people make better career decisions?
Over the last few months, I've been building salary calculators and researching compensation data across different industries.
One thing surprised me.
People often say they want "more salary transparency," but in practice, raw salary numbers rarely answer the questions people actually have.
For example:
Is a $120k salary in one state actually better than $95k somewhere else?
How much will taxes really change take-home pay?
Is hourly work, salaried work, or contract work the better financial choice?
How much does overtime actually add over a year?
It made me wonder whether we've been solving the wrong problem.
Maybe people don't just need more salary data.
Maybe they need better tools that help them understand what those numbers actually mean.
I'm curious how everyone here thinks about this.
If you've negotiated compensation, changed jobs, or relocated, what information do you wish you had before making the decision?
Replies
Have you thought about including total compensation, like bonuses, equity, and retirement benefits, instead of just base salary?
@tom_nick1 That's a great point, and it's something I've been thinking about.
Base salary is usually where people start, but it's often not the biggest factor in the overall package. Bonuses, RSUs/equity, retirement matching, healthcare, PTO, and even location can significantly change the real value of an offer.
One challenge is that those components vary a lot between companies, so it's harder to build a calculator that's both accurate and simple to use. I think there's room for a "total compensation" calculator in the future, but I'd want it to help people compare offers realistically instead of just adding everything together.
Hedy AI
I like that you're questioning the problem itself instead of just collecting more salary data. That's a thoughtful approach. 👏
@kate_sleeman Thank you, I really appreciate that.
Building these tools has actually changed how I think about salary transparency. I started out assuming people mainly needed more salary data, but I kept finding that the harder questions were about interpreting that data in real-world situations.
That's why I've become more interested in building tools that help people answer practical questions rather than simply presenting more numbers.