← HR Metrics·Regulatory Compliance
Pay-Floor Annualized Dollar Exposure
Sum of annualized discrepancy across all noncompliant workers — i.e., the total annual underpayment if every "fail" worker received exactly the required minimum for the next 12 months. Hours assumption is the per-worker annualHoursAssumption passed at evaluate-time (default 2080).
How it’s computed
SUM( (required_hourly_wage - worker_hourly_wage) * annual_hours_assumption ) FOR worker IN fails
What the evidence shows
Evidence (effect sizes, priors, validity) is syncing from Principia.
- wage-compliance spoke contract types (PAT-79): ComplianceEvaluationResult.discrepancyAmount
- FLSA recordkeeping requirements 29 CFR Part 516 — 3-year retention of records used to calculate wages
What this metric can show you
Pay-Floor Annualized Dollar Exposure can tell roughly 23 pre-built stories — each a designed scene the data either confirms or it doesn’t. Bring your numbers and the Story Finder runs every one of these shapes against them.
specific to regulatory compliance
One group sits apart on a decision that should be neutral
fairness-equity · T1
One population, well-behaved
measurement-health · T1
The differences aren't the story
measurement-health · T1
The system isn't differentiating
measurement-health · T1
Two clusters wearing one chart
measurement-health · T1
universal shapes — any single metric can take these
A few large values are doing the talking
any focus · T1
A one-time event, not a trend
any focus · T1
It doesn't track — the premise is false
any focus · T1
It's concentrated — one group stands apart
any focus · T1
Scenes are pre-built; your data is the toggle. Browse the full deck or watch one play end-to-end in The Quiet Exodus.
Run it on your data
This metric is computed in the People Analytics Toolbox on your own numbers. See pricing — posted, no quotes.
sources: toolbox:metrics-catalog
What the literature says
The measurement literature behind this signal — sourced, so you can defend it.
“Assume, for example, that base pay is recorded in terms of an annual amount (hours multiplied by hourly pay rate) for a group of full-time and part-time employees, as shown in Table 4-3 .Table 4-3.Hypothetical Pay Rates for Full-Time and Part-Time EmployeesID#SexStatusJob…”
— Compensating Employees Fairlymatch 59%
“If the employer is investigating claims of discriminatory pay-setting practices, then the base rate of pay may be the appropriate choice.NoteThere is no reason the same compensation metrics must be studied across similarly situated employee groupings. Different compensation…”
— Compensating Employees Fairlymatch 57%
“For example, if date of birth is missing for some employees, and age at hire is to be used in the multiple regression analysis, the missing date of birth information should be collected and integrated. Entering 0 for those individuals with missing dates of birth can potentially…”
— Compensating Employees Fairlymatch 54%
Resources: Compensating Employees Fairly