Ethnicity pay reporting: A guide for UK employers

Guidance on navigating voluntary ethnicity pay reporting

Brown D |   | CIPD | Sep 2021

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The moral case for pay fairness across all ethnic groups should be as self-evident to any people professional as equal pay regardless of gender. Yet while unequal pay for men and women has been illegal in the UK since 1975, that is not the case for people from ethnic minority backgrounds.

Despite the Office for National Statistics’ 2019 annual review finding that ‘most of the minority ethnic groups analysed continue to earn less than White British employees in 2019’, many are unaware of the scale of the pay gap.

This new CIPD ethnicity pay reporting guide is written by IES and is designed to help encourage and facilitate publication and to support employers who wish to take advantage of the opportunities reporting presents and improve inclusion in their organisation through voluntary ethnicity pay reporting.

In the absence of legislative compulsion, both IES and the CIPD believes that employers should aim to voluntarily compile ethnicity pay reports as part of their organisation’s approach to improve inclusion and tackle inequality in the workplace. This guide aims to:

  • Encourage more employers to publish their ethnicity pay data voluntarily
  • Facilitate this process by recommending the most appropriate and effective approach to categorising and reporting their data
  • Encourage internal and comparative analysis and use of the resulting information to produce effective action plans to address the ethnicity pay gaps revealed.

To maximise the opportunities and minimise the challenges of ethnicity pay reporting, there are six principles the guide recommends employers follow:

  • Align ethnicity pay reporting with gender pay reporting, but recognise the differences.
  • Remember ethnicity representation is as important as, and strongly linked to, ethnicity pay gaps.
  • Recognise the value of simplicity and clarity.
  • Focus on action.
  • Start and improve.
  • Combine comparability in data with tailoring of analysis and actions.

This guide also contains recommended formats and methods, tools and case examples.