Collecting and comparing pay data to identify any significant equal pay gaps
Once you have determined where employees in those groups within the scope of your audit are doing equal work - men and women, disabled and non-disabled and so on - you need to collate and compare pay information to identify any significant gaps.
Advice on compiling your data has already been given in step one (see Data required). It is essential that your raw data has been thoroughly checked. For more tips see Data cleansing.
Before analysing pay it is useful to have a statistical picture of the workforce covered by your audit. This provides a context for your pay audit and may guide you concerning where to focus your audit.See information concerning workforce composition, all of which can be obtained from the input data specified in step one.
Equal work groups
Many organisations use their grades to determine who is doing equal work as the basis of their equal pay audit (work rated as equivalent). To be confident that your grading structure is free from bias, and that the grades reflect equal work, the grading structure should be based on analytical job evaluation which has been equality proofed. See detailed guidance on equality proofing job evaluation schemes.
Given the potential volume of data in your equal pay audit, we recommend you analyse the relative pay of one protected group at a time, starting with a comparison of the pay of men and women doing equal work. The steps in the analysis are similar for all protected groups. We deal with the special features of analysing pay by ethnicity and disability later.
As a first step for men and women each equal work group:
1. Calculate average basic pay and total average pay. Then calculate the gap between average pay and total pay for each equal work group
2. Compare access to and amounts received of each element of pay.
Unless there is a genuine reason for the difference in pay that has nothing to do with the sex of the jobholder, men and women doing equal work are entitled to equal pay.
It may not be feasible to conduct meaningful statistical comparisons of pay when the numbers of, say, minority ethnic and/or disabled employees are very small. In that situation you could ‘spot check’ the pay of minority ethnic and/or disabled employees against appropriate white/non-disabled comparators doing equal work.
See also: Step 3 - additional information
This section contains more information on: