"Show me compensation by occupation broken out by gender and ethnicity. flag roles where gaps are statistically significant."

Pay equity by occupation. comp gaps with statistical confidence

Most tools punt on pay equity because the data is sensitive. This dashboard surfaces it cleanly. with the caveats your legal team expects.

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Methodology note: Gaps shown are unadjusted (raw) differences in median compensation within the same SOC occupation. Statistical significance is assessed at the 95% confidence level using Mann-Whitney U for gender and Kruskal-Wallis for ethnicity groups. Unadjusted gaps do not control for tenure, performance tier, or geographic location. Recommended action: share flagged roles with legal counsel before any remediation decisions. Data shown is illustrative sample data only.

Roles Analyzed

SOC occupations

Statistically Flagged

Gender or ethnicity gap ≥ 95% CI

Largest Gender Gap

-11.4%

Software Developers

Est. Remediation Cost

$187K

To close flagged gaps

Gender pay gap by occupation. median comp, women vs men (same SOC, same org)

Sample data. illustrative only. Negative = women earn less within same occupation.

Software Developers (15-1252): -11.4% gender gap. statistically significant at 99% CI. 8 women, 40 men in the group. Estimated remediation: $94K/yr.
Sales Reps, Wholesale (41-3099): -9.1% gap, significant at 95% CI. Likely driven by commission structure; adjusted analysis recommended before remediation.
Registered Nurses (29-1141): +1.2% gap (women earn more) . significant. Largest occupation by headcount; equity is solid.
Accountants (13-2011): -3.4% gap, not significant at 95% CI. Flag for monitoring at next compensation review.

AI-generated report (sample)

Four occupations carry statistically significant pay gaps on the unadjusted basis. Software Developers and Sales Reps are the primary concerns. The Software Developer gap ($94K estimated remediation) is likely structural. the cohort shows a clear tenure-and-level distribution imbalance, not just pay difference. Recommendation: conduct an adjusted regression analysis controlling for level, tenure, and performance rating before determining the true gap. Bring legal counsel into that analysis before sharing findings broadly.

Why this matters for HR leaders

Most HRIS tools won't show this at all because it's politically sensitive . But HR leaders who can't quantify it can't defend the org if a claim is filed.
Statistical confidence intervals separate "noise" from real gaps. so you're not remediation-chasing random variance.
The dashboard flags but doesn't prescribe. legal review before action is built into the workflow, not bolted on.

Pay equity detail by occupation

Occupation	SOC	N	Gender Gap	Significance	Ethnicity Gap	Significance	Est. Remediation
Software Developers	15-1252	48	-11.4%	Significant	-6.2%	Marginal	$94,200
Sales Reps, Wholesale	41-3099	27	-9.1%	Significant	-2.1%	Not Sig.	$62,400
First-Line Supv, Prod	51-1011	14	-5.8%	Marginal	-8.3%	Significant	$30,600
Market Research Analyst	13-1161	8	-7.2%	Marginal	-1.4%	Not Sig.	$18,400 (if confirmed)
Accountants	13-2011	9	-3.4%	Not Sig.	-2.8%	Not Sig.	Monitor
Registered Nurses	29-1141	62	+1.2%	Not Sig.	-1.1%	Not Sig.	:
Customer Service Reps	43-4051	34	-2.1%	Not Sig.	-0.8%	Not Sig.	:
HR Specialists	13-1071	7	-1.8%	Not Sig.	-1.2%	Not Sig.	:

Sample data. illustrative only. Gaps < 5% with N < 15 have low statistical power; interpret with caution. Consult legal counsel before any remediation action.

Other HR dashboards: ← HR Hub Headcount Turnover Cost Time-to-Fill EEO-1 Rollup Safety Claims Comp vs Market Workforce Forecast Internal Mobility

Surface the gaps before a claim does.

Pay equity analysis runs from your existing HRIS data. Role-based access ensures only authorized HR and legal personnel see this dashboard.

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