A new pay equity auditing and analytics service
A Better Way
Our pay equity auditing and analytics service is multi-disciplinary, combining extensive domain knowledge and expertise in pay equity statutes across multiple jurisdictions, economics, statistics and statistical modeling, workforce data management, and knowledge of your regulatory landscape. Using our proprietary Data Quality Management platform and customized statistical modeling, our PayParitySM pay equity audit and analysis provides actionable intelligence for you to be able to demonstrate fairness in pay and minimize risks of investigation, enforcement, legal action, and reputation loss.
Contact us to review your options today.
It starts with establishing the attorney-client privilege through your internal or external counsel. Trusaic stringently adheres to clients’ privilege and work-product protocols. We have developed best practices for preserving and protecting workforce data and work-product through our extensive experience in handling sensitive data for thousands of our clients. We are certified as SOC Type II compliant.
After the privilege protocols are in place, Trusaic works with you to establish a PayParitySM Project Team. The Project Team includes multi-disciplinary experts from Trusaic and individuals designated by your counsel. Your team usually includes personnel who understand your organizational functions, data sources, hierarchies, and compensation structure and philosophy across departments. We work closely with you to determine the scope of the pay equity audit, including the compensation measures to be analyzed, workforce segments, the number of employees, locations, and lines of business.
Once the scope of the PayParitySM pay equity audit has been finalized, Trusaic and your designated human resources leadership will collaborate to identify employee groupings (Pay Analysis Groups or “PAGs”) and to identify business and economic factors for the analyses.
Trusaic employs its Data Quality Management platform to extract, aggregate, and consolidate the relevant data from your disparate data silos. We’ll identify any missing, incomplete or inaccurate data and work with you to reconcile those issues. Once the data has been cleansed and validated to ensure its accuracy, the data will be segmented for analysis.
TRUSAIC customizes the statistical modeling to fit your operations
There are multiple types of analysis that may be undertaken:
Average Wage Comparisons
Assess average percentage wage differences amongst employee classes by PAG for current and prior base wages and prior total compensation.
Quantile Wage Distribution Comparisons
Compare wage rate distributions across protected employee classes, providing a fuller picture of wage differences.
Statistical Model Building
Use multiple linear regression analyses to measure any remaining differences in average employee wages across protected classes after accounting for the legitimate business and economic factors you identified as tied to your compensation decisions.
Pay Analysis Group (“PAG”) Tests
Test the collaboratively defined PAGs to ensure that they are sufficiently distinct for analysis.
Cohort Wage Comparisons
Assess the consistency of audit findings among matched groups of employees, known as “cohorts,” and provide a more granular analysis of your workforce.
Age + Pay Comparisons
Measure the effect of age on pay rates, while controlling for business and economic factors.
Overtime Participation Tests
Measure overtime participation rates across Client’s workforce.
Affirmative Action Comparisons
Compare the protected class composition of your workforce relative to Census measures, based on EEO-1 job categories.
After performing the applicable analyses, Trusaic will generate a PayParitySM Report providing the following information:
Protected class breakout of client’s workforce.
Visual and narrative comparisons of pay rates within each pay analysis group, identifying compensation for employee protected classes before controlling for business and economic factors (“raw” or average wage comparisons).
Visual and narrative comparisons of pay rates within each pay analysis group, identifying compensation for employee protected classes after controlling for business and economic factors.
Overtime participation comparisons and average overtime hours comparisons by year, pay analysis group, and job type.
Current year pay disparity exposure and if applicable, calculate remediation costs for such potential exposure, controlling for business and economic factors.
Effects of age on pay for employees aged 40+, 50+, 60+, and 70+ as compared to employees under age 40.
Unusual observations in your firm’s data that may be data entry errors or misclassifications, and flag statistical anomalies in your compensation structure (i.e., very high or very low wage rates by pay analysis group).
Multiple, actionable, graduated, data-driven pay equity solutions based on Trusaic’s findings.