The **Department for Work & Pensions (DWP)** says for every **£1** paid to the median man in March 2022, the median woman was also paid **£1.** In other words, their 2022 median gender pay gap using hourly pay was** 0%**. However, their Gender Swap Number per 1,000 employees for this date was **+26 **which immediately raises the question “*Have the DWP made an error in their calculations like Cleveland Police did in 2017?*” This was my first reaction which seems remarkable for an employer with **91,006** full pay relevant employees on a public sector pay scale and the largest pool of statisticians of any government department.

**Equality Now! in action**

The truth is the **DWP** did do their calculations correctly but they are an unusual exception to the normal rule of “*median pay gap of zero = swap number of zero*“. They are in fact a perfect case study of the “*Equality Now!*” method of eliminating a pay gap between the median man and median woman which I first explained in my article “*10 Quick & Easy ways to close your pay gap tomorrow!*“.

This article explains how this happened and why it is another example of the median gender pay gap statistic being misleading for some employers. It reinforces yet again my constant exhortation to employers to always start their gender pay gap narratives with their Pay Quarter Breakdowns (**PQB**) by gender and to abide the mantra of “*People not Percentages*” coined by my colleague Anthony Horrigan of Spktral.

In writing this article, **I am in no way whatsoever suggesting the DWP have deliberately sought to mislead the public** over how they present their pay gap data. On the contrary, their 2022 gender pay gap narrative makes it clear the lack of a pay gap between the median man and median woman is a statistical quirk. Indeed it is only through their openness in their narrative which I consider to be a good example to other employers that I am able to write this article.

**Where to find the DWP gender pay gap data**

- Download my gender pay gap data spreadsheet and look up Department for Work & Pensions.
- Visit the Government Equalities Office (GEO) Gender Pay Gap Data site and search for Department for Work & Pensions
- See a list of all gender pay gap data submissions made by the DWP between 2017 & 2022 on the GEO site
- See the DWP gender pay gap site
- Read the
**2022 Gender Pay Gap report published by the DWP**which is the document I will be using & referring to in this article

**DWP in 2022**

For every £1 paid per hour to the median man as of 31st March 2022, the median woman was also paid £1. At the same time, the average (mean) woman was paid 94p for every £1 paid to the average man. These figures have remained stable between 2017 & 2022.

What has not remained stable is the **GSN1k** (Gender Swap Number per 1,000 employees). This was near **0** for the 1st 3 years before jumping to around **25** for the next 3 years. In other words, for every 1,000 employees at DWP in 2022, **26** women from the lower pay half need to move into the upper pay half (with **26** men going the other way) to make the number of women in the upper pay half equal to the number of women in the lower pay half (and similarly for men).

*A quick reminder, the GSN1k is the difference between the number of women in the lower pay half and the number of women in the upper pay half which is then divided by 2 and then pro-rated assuming the DWP has 1,000 employees instead of 91,006. By treating the percentages shown in the pay quarter breakdowns as number of employees instead, it is easy to see that ((66+74)-(59+60))/2 *1000/400 = +26. *

**Identifying the median man and median woman at DWP in 2022**

On page 7 of the DWP’s 2022 narrative, this table is given which shows how many men and women work in the five main job grades used in the DWP.

*Image source – Department of Work & Pensions 2022 gender pay gap report page 7*

The total headcount on 31st March 2022 was 92,369 (*see page 3*). Of these, 91,006 employees were deemed to be full pay relevant (**FPRE**) for the purposes of the gender pay gap calculations based on hourly pay and the above table only refers to FPREs. The DWP do not explicitly make this clear but I understand there is no crossover between the 5 pay grades when it comes to hourly pay e.g. the top of the SEO/HEO pay scale is not higher than the bottom of the Grade 6/7 pay scale, etc.

In which job grade will you find the **median man** and the **median woman**?

- If the
**32,260**men were to stand in a line in order of their hourly pay, the median man would be the man standing in the middle of this line. Since there is an even number of men, the median man is the average of the**16,130**th man and**16,131**st man in the line. Starting from the bottom, there are**9,578**men in**AA/AO**grades and**16,215**in the**EO**grades. Therefore, both men are**EO**grade which makes**the median man an Executive Officer (EO)**. - If the
**58,746**women were to stand in a line in order of their hourly pay, the median woman would be the woman standing in the middle of this line. Since there is an even number of women, the median woman is the average of the**29,373**rd woman and**29,374**th woman in the line. Starting from the bottom, there are**19,094**women in**AA/AO**grades and**31,483**in the**EO**grades. Therefore, both women are**EO**grade which makes**the median woman an Executive Officer (EO)**.

**Equality Now! at DWP**

Just because both the median man and median woman are Executive Officers doesn’t automatically mean they are paid the same … except it does at the DWP! See this paragraph from page 10 of their 2022 narrative.

Virtually all Executive Officers at DWP are on a spot rate i.e. they are (nearly) all paid the same hourly pay rate. Hence the median man and median woman are paid the same and the median gender pay gap is zero.

The DWP also tell you that you didn’t even need to look at the workforce breakdown table on page 7. Straight out, they tell you over **50%** of men and **54%** of women are EOs which is all you need to know to immediately work out both the median man and the median woman are Executive Officers. This was the point of my “*Equality Now!*” method of closing your median pay gap whereby you pay the majority of your men and the majority of your women the same hourly pay rate which is what the DWP have done. By doing this, you guarantee the median man and median woman will always come from these majorities as shown by this chart.

The thick vertical black line represents the middle of the lines for men and woman. This line is guaranteed to cut through any category of men/women which accounts for 50% or more of men/women.

**So does the DWP have a gender pay gap?**

The above chart immediately tells you the answer is yes despite the median gender pay gap being zero. The underlying premise of my swap number concept is that in order to truly close a gender pay gap, one has to see the same gender ratio wherever you look in an employer. The corollary of this concept is the breakdown by job grade should be identical within the separate lines of men and women.

This is not the case in the above chart. The bars for the two highest pay grades of SCS & Grade 6/7 are almost twice as large for men as they are for women i.e. a man is twice as likely as a woman to end up in the highest pay grades. At the same time, women are slightly more likely than men to end up in the lowest pay grade of AA/AO. To close this pay gap, the above chart needs to look like the one below at some point in the future.

The exact percentages for each job grade need not be identical to what is shown here. What is important is the percentage is the same for men and women. If so, one can say the **probability** of an individual ending up in any job grade is **independent** of their gender. That is the formal definition of “*no gender pay gap*” to a professional statistician like me and is why I prefer the term “*no gender representation gap*” or perhaps more strictly “*no gender likelihood gap*“.

*Note – I first talked about the concept of likelihood as applied to gender pay gap analysis in my article “Has pay reporting narrowed the gender pay gap between 2017 & 2021?“*

**How does the DWP close its gender pay gap?**

Swap numbers can be used in a number of ways and one way is as a measure of what needs to change to get to the above blue chart from the green chart that came before it. The full calculation is demonstrated in the table below. This starts by showing what percentage of employees within each job grade were women in 2022. I noted women made up 65% of all FPRE employees in 2022 and I then set a target of achieving that percentage in each of the 5 job grades at some point in the future. This results in the required number of men and women as shown in the No Representation Gap columns. The total number of men and women is unchanged in this scenario, what changes is in which job grade they are working in. The amount of change required is shown in the Change Needed column which shows how many more women (and fewer men) are needed in each of the 5 job grades.

Overall, the DWP needs to recruit **1279** more men to replace **1279** jobs currently undertaken by women in AA/AO & EO grades and **1279** more women who will replace **1279** jobs currently undertaken by men in the three highest paid job grades. Thus the actual DWP swap number is **+1279**. When I look at the changes needed as a percentage of the total number of employees within each of the five job grades, Grade 6/7 roles look like being the toughest nut for DWP to crack since the **621** additional women amounts to** 17.5%** of the total Grade 6/7 workforce.

**My thoughts on DWP’s 2022 narrative**

I hope you found this an illuminating case study which shows yet again why the median gender pay gap statistic is misleading and can be ignored. It also demonstrates why the Gender Swap Number is a more meaningful statistic to use instead.

Greatly to the DWP’s credit, they make almost no reference to the median gender pay gap in their 2022 gender pay gap narrative apart from a small table on page 6 and the paragraph I referred earlier on page 10. They start their narrative by stating they do have a gender pay gap based on the difference between the average man and the average woman rather than the median man/woman. I am no fan of the mean gender pay gap statistic but it is the more relevant of the two statistics available in this instance. The DWP stand in contrast to Novartis UK who failed to point out their gender pay gap favouring women in 2019 was the result of a statistical phenomenon known as **Simpsons Paradox**, an omission I took them to task with in my article “*What is the Gender Pay Gap at Novartis UK?*”

Most of all, what I like about the DWP narrative is it is an in-depth analysis of the **distribution of men and women** across the 5 job grades and whether or not they are on the latest terms & conditions or on legacy T&Cs. They do a decent job of fulfilling the “*People not Percentages*” mantra I referred to at the start. This is what employers should be doing all the time and the Pay Quarter Breakdown is one of the best ways to present your gender representation gaps at the start of your narrative. By doing this, employers like the Department for Work & Pensions are more likely to identify the areas where they need to focus their efforts and are more likely to make progress going forward.

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**— Why I write these case studies —**

My case studies explore good and bad practice with gender pay gap analysis and highlights what can be learned from them. Closing a national pay gap can only happen if change happens within individual employers in the first place. In the front line of such change will be the HR department who in my experience find basic statistics a struggle and so I hope they find these case studies illuminating.

- “
“, – I work out how much variation in gender pay gaps can be expected by chance. I then show that the variation in pay gaps across the 4 UK subsidiaries of my former employer*Life on Mars***Mars UK**was within the bounds of chance and that in effect they had no gender pay gap. Based on my experience of working there, I explored some of the reasons why Mars did not have a pay gap. - “
“. I looked at the two legal entities of*The good, the bad and the Unilever***Unilever**who are required to report their gender pay gap and noticed that the year on year changes between 2017 & 2018 looked odd. I used them as an inspiration to explain how one can spot if year on year changes are plausible or not. - The effect of
**Samira Ahmed winning her equal pay claim against the BBC**and what impact it would have on their gender pay gap. Confusion abounds over the difference between unequal pay and gender pay gaps and I showed that the impact of Samira winning the case could be to widen the pay gap instead. - “
“.**What is the gender pay gap at Novartis UK****Novartis**perfectly illustrate the hazard of Simpson’s paradox when analysing pay gaps where employees simultaneously work for an employer with a gender pay gap favouring women and a gender pay gap favouring men. - “
“. I explore the 6 purposes of an employer’s pay gap report and show how Ryanair mostly fulfill these in less than half a page despite having the largest verified gender pay gap of all employers and a dodgy bar chart!**Why Ryanair’s gender pay gap report is my favourite** - “
“. I look at how the Conservatives went from having no ethnicity minority MPs and almost no female MPs to having the UK’s first non-white minority Prime Minister and why I consider them an important public case study for employers who wish to do the same.*How the Conservatives eliminated their gender & ethnicity pay gaps*

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