PayAnalytics - October 2025 Feature Release
This article lists the updates made available to users in the PayAnalytics platform in October 2025.
Pay Gap by Demographics - New section
We’ve added a new section to make it easier to see pay gaps across different demographic groups, as presented in the following pictures:
Pay gaps by demographics
Simplified graph: The new chart uses two bars for each demographic group—one for the unadjusted and one for the adjusted pay gap. This design makes it clearer and simpler to compare gaps.
Before/After raises toggle: User can now switch between viewing pay gaps before and after raises are applied, so you can see how these values change.
Unlike the Progression from Unadjusted to Adjusted Pay Gap chart, located just below the Pay Gaps by Demographics section within the Pay Gaps tab, this visualization does not display the contribution of compensation drivers. Instead, it simply shows the unadjusted and adjusted pay gaps for each demographic group included in the analysis, allowing users to quickly understand the overall differences between groups.
This section is available when you run an analysis with one or two demographic groups and, if configured, compute raises.
Pay gaps by group: New filters and a summary table
We’ve updated the Pay Gaps by Group section with several new features to help you better understand your results and take action, especially in line with the EU Pay Transparency Directive.
New filters
We’ve added new filters above the main table to help you quickly identify groups that may need attention:
Significant Focus Groups (Before Raises): Filters the main table to show only focus groups with statistically significant gaps (denoted by four black dots).
Moderately Significant Focus Groups (Before Raises): Filters the main table to show groups with moderately significant gaps (denoted by three black dots).
Pay Gap Exceeds the Target (After Raises): Filters for groups where the estimated adjusted pay gap after raises is greater than or equal to the user-defined target.
Summary table
A new Summary Table now highlights the top one, two, or three groups based on their focus group status (significant or moderately significant) and their highest estimated adjusted pay gaps before raises, as illustrated in the following image:
Summary table overview
This helps you quickly find where the largest pay disparities are and prioritize your next steps. This table is not displayed if there are no significant or moderately significant groups.
Enhanced table capabilities
To streamline the experience, we removed the drop-down list that previously enabled users to select which gender groups to compare against the reference group. Instead, the table now provides filtering options across most columns, giving users more flexibility to explore their data. For instance, in a gender analysis that includes Female, Male, and Non-Binary employees, users can filter by a specific job group and view all corresponding gender results for that group.
The main table now has new filtering and sorting options, as well as additional details for each group:
Number of employees
Average compensation (per group)
Reference group: The group you are comparing against, along with its headcount and average compensation.
Demographic group: The group being analyzed, along with its headcount and average compensation.
Unadjusted pay gap: The percentage difference in average pay between the demographic group and the reference group, shown both before and after raises.
Estimated adjusted pay gap: The percentage difference after adjusting for other factors in the analysis (like job role or grade), shown both before and after raises.
Target pay gap: The gap you set in your analysis and whether it was reached.
Focus group: Indicates whether the demographic group is driving the gap, shown both before and after raises.
All columns in this table can now be downloaded through the Excel download feature, and users can choose which columns to display or hide directly within the interface.
These updates give users more control and clarity when reviewing results, so you can focus on the groups that matter most.