Pay Equity Analysis System Using Segmented Data Harmonization
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Solution Overview
Problem
Employers face challenges in understanding and addressing pay gaps between genders and races due to the complexity of evaluating pay equity and opportunity equity within their organizations, which requires real-time data analysis and compliance with various laws, but existing methods often fail to provide actionable insights in a timely and compliant manner.
Innovation Solution
A computer-implemented method and system for analyzing pay policies, which includes receiving pay data, determining controls, calculating equitable pay ranges, and providing insights on pay equity and opportunity equity, using robust statistical analysis to identify issues and prevent future disparities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If real-time data analysis is performed to evaluate pay equity and opportunity equity, then actionable insights are provided in a timely manner, but the complexity of data aggregation, harmonization, and consolidation increases
Solution Approach 1:
The system segments the complex data aggregation process into distinct modules: individual level data collection, group level data collection, and policy level data collection. Each module handles specific data types separately before integrating them through standardized harmonization protocols, reducing the overall complexity of real-time analysis.
Solution Approach 2:
The system introduces an intermediary data harmonization layer that standardizes diverse data formats from multiple sources (HRIS, compensation systems, external datasets) into a unified structure. This intermediary layer abstracts the complexity of data aggregation from the analysis layer, enabling real-time processing without exposing users to underlying data complexity.
2Reliability
If comprehensive statistical analysis is performed to ensure compliance with pay equity laws, then legal compliance is improved, but the time required for analysis increases
Solution Approach 1:
The system performs preliminary data preparation and control determination before formal statistical analysis. By pre-aggregating data, pre-harmonizing formats, and pre-identifying relevant controls (such as job level, location, and experience factors), the system reduces the time required for actual compliance analysis while maintaining comprehensive statistical rigor.
Solution Approach 2:
The system implements feedback loops that continuously monitor analysis results against legal compliance thresholds. When potential non-compliance is detected, the system automatically triggers remediation workflows and updates controls in real-time, ensuring ongoing compliance without requiring repeated manual analysis cycles.
3Productivity
If dynamic evaluation of pay policies is performed to identify bias and inconsistency, then actionable insights are improved, but the computational resources and processing time increase
Solution Approach 1:
The system applies local quality analysis by evaluating pay policies at multiple granular levels (individual employee level, department level, job level) with differentiated computational intensity. Simple descriptive statistics are applied at higher levels where data volume is large, while detailed bias analysis is applied at lower levels where sample sizes are smaller, optimizing the balance between insight quality and computational resource consumption.
Data Source
AI summary
Disclosed are example embodiments of a methods and systems for analyzing and determining impact (or lack thereof) on any selected group or groups of employees of selected pay policies. An example includes a computer-implemented method for analyzing and determining impact on selected group of employees of selected pay policies. The method including receiving a first pay data for the selected group of employees. The method also including determining one or more controls for the selected group of employees. Additionally, the method including calculating an equitable pay range for the selected group of employees based on the one or more controls. The method also including receiving a user input, wherein the user input requests a second pay data relates to an employee, and is based on a selected control. The method also including calculating the second pay data; and sending the second pay data for display.