How much are you currently underpaying women?

Gender equality and transparency in pay is a political issue, and we will shortly have new legislation. In less than a year, every UK enterprise will be required to publish how much (more) their men earn compared to their female counterparts.

How straightforward is it for your organisation to obtain that data?

What I love most about new legislation in the HR world, are the faces made by HR directors when I ask that question. They range from the statuesque, the chewing of a wasp, the contorted face of someone struggling with the a Times Friday Sudoku, and finally, there is the cheery face that I’ll return to later.

I’m fortunate that the overlap between people, technology and analytics is always strong in HR; it makes my life more varied and ensures that follow-up questions come thick and fast.

The prominent questions are: What defines pay? How do I split my employee base in to earning quartiles? How up to date does the snapshot need to be?

You can glean an understanding of how progressive an HR department is by assessing to whom these questions are being asked. Is the HR Director asking their team, an IT specialist, a systems support team or even a third party salary benchmarking company? Of course, I am focusing on the mere practicalities of reporting the data here (I am a mathematician after all), but naturally the HR Director has even more pressing questions around The Equality Act 2010 Regulations 2016. I fully support the equality issues behind the legislation (are you watching Muirfield?) and efforts to close these gaps should certainly be top of the to-do list. But, returning to the original question, how straightforward is it to actually obtain this data?

The gender pay reporting regulations will require all enterprises to divide their pay distribution into four bands and work out the number of men and women in each quartile.  This is a fantastic test for your payroll service, whether in-house or outsourced.  If you have an ERP system like Oracle Payroll, then this should be a simple exercise! You should have a balance that reflects the Office for National Statistics (ONS) definition of ‘Pay’, and slicing this into quartiles should be simple whether using any of the modern technologies – from Discoverer, to Qlik, Hubble, Splash and OBIEE (There are a lot to choose from today, and please read a related blog here). NB. I’m assuming no-one still attempts these things in a spreadsheet?

So, here are my 3 top tips to this process:

1. Ensure that you have a clear understanding of defined pay per contracted hour before starting anything else.

The definition of such “pay” includes basic pay, paid leave, maternity pay, sick pay, area allowances, shift premium pay, bonus pay and other pay (including the following: car allowances paid through the payroll, on call and standby allowances, clothing, first aider or fire warden allowances). It does not include overtime pay, expenses, the value of salary sacrifice schemes, benefits in kind, redundancy pay, arrears of pay and tax credits.  Employers will need to calculate an hourly pay rate for each relevant employee, based on the period of 12 months preceding the relevant date.

2. Challenge your data supplier now.

From the in-house team, to 3rd party payroll provider.  How and when will they be giving you this information – and how confident are you in the data quality and are they proactively driving these conversations?  The rules are expected to come into force on 1st October 2016. This will give employers six months before they have to take their first snapshot in April 2017.

3. Plan what you want to do next.

Are you looking to meet the statutory minimum reporting, or to interrogate this data to discover transformational findings?  Which departments have the biggest gap, how does length-of-service, geography or age impact the analysis?  What is the trend on the gap over time?  In short, what data do you need to help you close this gap?  (Another time we can discuss predictive analytics and the introduction of the National Living Wage impact.)

So going back to the cheery face – naturally that is the HR Director with Oracle Payroll and Claremont‘s Payroll Control Centre. Happily, sat using a tablet to visually interrogate the data over and above the minimum requirements – to achieve the insight they need – from real-time data, without having to ask anyone else to prepare their statistics.

We know men are paid more, now we need to know by how much and why.  In my mind, this single reporting dashboard will soon be every HR Director’s new corporate KPI – and they will be measured in their success in reducing this gap.  As the Prime Minister has said, you cannot have true opportunity without real equality.  From my side, you can’t have true analysis without ‘real analytics’.  Hopefully these come from inside your organisation or your incumbent provider.  If not, you know where I am.

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