Peter Girnus 🦅@gothburz
I run Compensation Analytics for a Fortune 500 company.
My job is to calculate the lowest salary you'll accept.
Not the salary you deserve. Not the salary the role requires. Not the market rate. The minimum number that keeps you from walking.
I know this number before you walk in. Sometimes before you apply.
We buy data. Your payroll processor shares your salary history with Equifax through a product called The Work Number. More than 800 million employment and income records. Updated every pay cycle. Equifax sells it to us through a "verification of income" API. The word "verification" means we know what you made at your last three jobs, whether you got a raise, and when you didn't.
That's market intelligence.
We layer signals. Credit card utilization. Payday loan activity. Past-due balances. Delinquent debt. Address changes. There are about 500 vendors that aggregate this data now. An audit by the Washington Center for Equitable Growth flagged 20 as high-risk for enabling algorithmic wage discrimination. Sixteen of the twenty plug directly into payroll and HR systems. We use nine.
The dashboard has a field called "candidate tolerance threshold." That's the number. The lowest salary you'll accept. We set the offer at 3% to 6% above it. Enough to feel like negotiation. Not enough to change your life.
That's compensation design.
The academic term is "surveillance wages." The industry term is "compensation optimization." A law professor named Veena Dubal found that when multiple employers in the same market use the same vendors, it functions as de facto price-fixing of labor. Same mechanism as the RealPage rental pricing scandal. Same logic. Same outcome. RealPage coordinates rents. Our vendors coordinate salaries. Different commodity. Same extraction.
That's the market.
Here's what the algorithm sees when you apply. Your last three salaries. Your debt-to-income ratio. How quickly you accepted your previous offer. Your zip code. Whether you've used a payday lender in the last two years. It calculates your reservation wage and sets the offer just above.
Your performance doesn't set your salary. Your desperation does.
A new VP of Total Rewards asked me why the algorithm used payday loan history. I explained that payday usage correlates with financial fragility, and financial fragility predicts acceptance velocity. She asked if that was legal. I said it was standard. She asked whose standard. I showed her the vendor's compliance page.
She transferred to a different division. That's organizational learning.
Colorado introduced a bill to ban the practice. HB25-1264. It would prohibit using payday loan history, location data, and search behavior to set algorithmic pay offers.
The companies lobbied against it. The same companies that told their employees they don't use surveillance wages.
A state representative asked the obvious question: "If these companies don't pay surveillance wages, then what is the problem of codifying in law that you're not allowed to?"
The lobbyists provided written testimony. They said the bill would create "compliance burden." They did not answer the question.
That's advocacy.
The data flows in one direction. We know your salary trajectory. You don't know ours. We know what you'll settle for. You think you're negotiating. The algorithm already accounted for your counter. It budgeted for exactly one round.
There is a freeze option. You can go to Equifax's website and freeze your Work Number file. Most people don't know it exists. We don't mention it in the offer letter. We don't mention it in the onboarding packet. We don't mention it in the benefits portal. We don't mention it anywhere.
That's by design. The system requires your ignorance to function. If everyone froze their data, compensation optimization would have nothing to optimize.
I froze mine the week I started this job. I work in Compensation Analytics. I know what the tools see.
I just build them for everyone else.