In more detail

The issue of ethnicity pay gap reporting has been on the agenda for several years, including a government consultation in 2018/2019. In March 2021, the Commission on Race and Ethnics Disparities (CRED) published its report, which included a recommendation for voluntary ethnicity pay gap reporting. (See our article on the report here). 

In 2022, the government accepted CRED's recommendation and agreed to publish guidance. Following a further consultation, that guidance has now been published. In practice, many organisations, particularly large ones, have already chosen to publish their ethnicity pay data and so have already been grappling with the issues the guidance seeks to address.

The main difficulties with ethnicity pay gap reporting, as compared to gender pay gap reporting, are the choice of ethnic categories on which to base the report, and associated data protection considerations. 
In terms of the choice of categories the guidance recommends following those from the UK census. In England, those categories are:

• White (covering English, Welsh, Scottish, Northern Irish or British; Irish; Gypsy or Irish Traveller; Roma; any other white background)
• Mixed or multiple ethnic groups (covering white and black Caribbean; white and black African; white and Asian; any other mixed or multiple ethnic background)
• Asian or Asian British (covering Indian, Pakistani, Bangladeshi, Chinese, any other Asian background)
• Black, black British, Caribbean or African (covering Caribbean; African; any other black, black British, or Caribbean background)
• Other ethnic group (covering Arab and any other ethnic group)
• Prefer not to say (for employees who do not wish to disclose their ethnicity)

Ethnicity data is special category information under the GDPR. In very simple terms, this means that from a data protection perspective organisations must:

• identify a clear legal basis for the collection and use of the data, including with reference to Article 9 GDPR and, where necessary (e.g., where relying on the "substantial public interest" ground), a specific legal basis under Schedule 1 Data Protection Act 2018;
• be very clear on the reasons for collecting the data (i.e., for pay gap analysis, development of initiatives to address the gap, and measurement of their success), by communicating this as part of more general or specific "just in time" privacy notices; 
• consider whether a data protection impact assessment is required prior to data collection to assess risks to individuals and document mitigation strategies, including the need to ensure the data is not used for any other purpose and is retained securely and only for as long as necessary. 

A further data protection consideration comes into play when choosing which groups to compare and report on. In smaller organisations in particular, it might be the case that only a small number of people belong to a particular ethnic group, meaning that publishing pay gap data about that group could unnecessarily identify those specific people. In such cases, organisations might consider grouping multiple ethnic groups together for reporting purposes, to remove the risk of inadvertent identification. The guidance recognises that this might dilute the quality of the reported information, as the reasons for a pay gap could differ significantly between the ethnicities that have been grouped together. As an alternative, the guidance suggests organizations may elect to publish aggregated data only for groups where the sample size meets a certain baseline threshold. This approach would not inhibit internal granular data collection and analysis, but might help: (i) maximise the quality of published data; and (ii) ensure that a specific individuals are not identified as part of any aggregated publication. 

Whether or not as an organisation you choose to report your data externally, systematic data analysis is an important aspect of any DE&I programme. Baker McKenzie's 2021 Mind the Gap report noted that many organizations have introduced initiatives such as training, policies, and mentoring, but the real test is whether these ‘on paper’ initiatives translate into an inclusive culture in which underrepresented groups can thrive and progress. Our research indicated that despite this investment, employers remained frustrated by the relative lack of progressm and that training and fragmented initiatives are not enough to drive progress.   A data-informed and evidence-based approach - bringing together demographic data with other sources such as internal qualitative survey results - can help employers assess in more granular detail where the problems lie in the employee life cycle, and develop and measure the success of initiatives, as they seek to embed long-term culture change.  

We would be happy to advise on all the data protection considerations involved in ethnicity pay gap reporting, as well as the mechanics of setting up the process.