Collecting and comparing pay data to identify any gaps
Once you’ve identified which employees are doing equal work, you need to compare pay information to identify any pay gaps. Before you start analysing your data, however, it’s essential it is checked thoroughly for completeness and accuracy.
It’s also useful to have a statistical picture of the workforce covered by your audit before you begin the analysis. This may guide you on where to focus the audit. Typical information would include:
- gender distribution by grade/equal work groups
- male and female staff by age and length of service, and
- part-time staff by gender by grade.
Next, you need to analyse the pay for the male and female employees in each equal work category.
To do this:
1. Calculate average basic pay and total average pay, then calculate the difference between average pay and total pay of women and men for each equal work group.
2. Compare access to and amounts received of each element of pay.
There are a number of different ways of calculating average earnings. Using the median as a measure of average earnings tends to be less affected by a small number of extremely high earners (which can skew the distribution of earnings). However, using the mean can help to capture differences across the distribution (for example, showing lots of women in the low earning extreme or lots of men in the high earning extreme). In practice, there are benefits in presenting both the median and the mean together when describing average pay, though this should be accompanied by clear commentary that explains how this has been calculated
Remember, unless there is a genuine justification for a 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.
While every effort has been made to ensure that this advice is accurate and up to date, it does not guarantee that you could successfully defend an equal pay claim. Only the courts or tribunals can give authoritative interpretations of the law.
Last updated: 19 Feb 2019