With the 4 April deadline for gender pay gap reporting now fast approaching, organisations are running out of time to report their gender pay gaps says Mark Crail, Content Director, XpertHR.
At XpertHR, we are still working with a large number of employers, helping them to get their data in order so that they can meet the demands of the Regulations – and more are contacting us every day.
At the moment, there are 1,720 company reports live on the government website (https://gender-pay-gap.service.gov.uk/Viewing/search-results). The number is growing rapidly – on some days we have seen a couple of hundred newly published sets of data. But it is still difficult to believe that all 9,000 companies covered by the Regulations will meet the deadline.
A number of organisations have clearly not read the Regulations properly or, at least, have published data that very clearly looks wrong.
As a reminder, reports must be authorised by a company director or the equivalent to meet the legal requirement – there are examples where reports appear to have been signed off by payroll managers or project managers.
Organisations which publish potentially dubious data are getting emails from the Government Equalities Office warning them that they must publish accurate data that meets the legal requirements. These emails appear to be triggered automatically when someone reports a gender pay gap of zero or gives the same figure for both the mean and median pay gaps.
Any organisation which receives one of these emails should check that they are satisfied that their figures are correct. Despite a warning in the email that their data appears “statistically unlikely”, it is not necessarily the case that the numbers are wrong – and while a zero mean pay gap would be extraordinary, a zero median pay gap is actually not that odd or unusual.
Our message to anyone receiving one of these warning emails is: check your data. It is not too late to edit and correct the data you have published on the government website. But equally, if you are confident that your figures are correct, don’t panic: “statistically unlikely” does not necessarily mean “wrong.”