Ethnicity pay gap reporting is inevitably a more complex process than comparing pay by reference to sex. However, if an employer does not analyse its ethnicity pay gap data in a methodical way, it is much harder for it to identify inequalities within its workforce or take steps to remedy them.
The government guidance on ethnicity pay gap reporting is designed to help employers develop a consistent approach to voluntary reporting which they can use to take meaningful action to address barriers to fair pay and progression.
Which figures to report
The guidance suggests that employers should report the following measures, using 5 April as a snapshot date to be consistent with gender pay gap reporting:
- Percentage of each ethnic group in each hourly pay quarter;
- Mean ethnicity pay gap using hourly pay;
- Median ethnicity pay gap using hourly pay;
- The percentages of employees in different ethnic groups; and
- The percentage of employees whose ethnicity is not known.
If bonuses make up a large proportion of employee pay, the guidance recommends that employers also calculate the mean and median ethnicity bonus pay gap and the percentage of each ethnic group receiving bonus pay.
Collecting and reporting ethnicity data
To ensure consistency, the guidance recommends that employers ask employees about their ethnicity using the relevant questions from the 2021 census. These vary depending on the country within the UK in which the employee works and allow employees to identify their ethnicity in a reasonably granular way. Employees should have the option of responding “prefer not to say” or being able to respond without providing data.
As far as possible, pay gaps should be calculated and reported using the census ethnicity classifications. However, this may not be possible if the results will not be statistically robust because of a small sample size, or because it would be possible to identify individuals from information that is published. Employers should set a minimum category size to allow appropriate analysis to be carried out. If information is being collected for internal use only, the minimum category size will be smaller than if the information will be published. If information is published, the guidance recommends a minimum category size of 50.
This may mean that data for some ethnic groups has to be aggregated to reach the minimum size. How to do this is a question of judgment, but the guidance recognises that aggregation risks hiding pay differentials between different ethnic groups.
Understanding and reporting the results
Identifying the existence of a pay gap is obviously only a starting point. Until an employer has analysed the reasons for that pay disparity, it cannot take steps to address it. The guidance recommends that employers consider matters such as recruitment, promotion, retention, employee location and whether certain ethnic groups tend to be clustered in certain roles. This will help identify why ethnic groups may be underrepresented in an organisation as a whole or at certain levels within an organisation.
The employer should then prepare an action plan to remedy pay gaps, by reference to clear measurable targets that can be achieved within a specified time frame. These should address the issues that have been identified as causing the ethnicity pay gap, not simply provide an arbitrary target for reducing the extent of the gap.
Employers do not have to publish their ethnicity pay gap calculations or their action plan, but are encouraged to do so. The guidance indicates that it may be useful (as with gender pay gap reporting) to provide a supporting narrative explaining the figures, the reasons for any pay disparities where there is robust analysis to support this and the steps already taken to understand and address any pay disparities. Producing reports annually in a consistent form is an important way to identify how disparities change over time.
Next steps
If we can help you develop your approach to ethnicity pay gap reporting, please get in touch with one of the authors or your usual contact.
Authored by Anvita Sharma and Stefan Martin.
