{"id":11807,"date":"2025-05-09T15:39:45","date_gmt":"2025-05-09T15:39:45","guid":{"rendered":"https:\/\/www.brightmine.com\/uk\/?post_type=resources&p=11807"},"modified":"2025-12-16T12:31:27","modified_gmt":"2025-12-16T12:31:27","slug":"are-you-making-the-most-of-your-gender-pay-gap-data","status":"publish","type":"resources","link":"https:\/\/www.brightmine.com\/uk\/resources\/total-rewards\/pay-equity\/are-you-making-the-most-of-your-gender-pay-gap-data\/","title":{"rendered":"Are you making the most of your gender pay gap data?"},"content":{"rendered":"\n
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by Hannah Mason<\/strong>, Brightmine HR data insights analyst<\/p>\n\n\n\n

Now that the annual deadline has passed, it is a good time to analyse your organisation’s gender pay gap calculation in detail. Understanding your data is key to developing strategies to move forward and make progress.<\/p>\n\n\n\n

The requirement to record and monitor your gender pay gap is here to stay. The Employment Rights Bill will require organisations with 250 or more employees to publish equality action plans<\/a>. Similarly, the EU Pay Transparency Directive<\/a> introduces a variety of requirements for organisations based in EU member states and with which UK employers may choose to align themselves.<\/p>\n\n\n\n

In this article, we explore different ways of interpreting your organisation’s gender pay gap and the factors that may be unexpectedly impacting it, and emphasise the importance of understanding your workforce composition to make meaningful steps towards gender equality.<\/p>\n\n\n\n

Representation matters for your pay gap<\/h2>\n\n\n\n

Transparency in pay will inevitably lead to fairer compensation and will ensure that employees see that they are paid fairly relative to other employees in similar roles.<\/p>\n\n\n\n

However, even with clear pay scales<\/a>, a gender pay gap can still be present – as we see in many public-sector organisations. To understand the impact that defined pay scales could have on your gender pay gap, let’s take the example of an organisation that pays every employee within a job level the same amount. It has equal numbers of male and female employees in the two highest pay bands, despite there being fewer females in the organisation as a whole, and it thinks it is doing well with female representation. Highlighted in green in Table 1 is where the median pay for each gender group falls.<\/p>\n\n\n\n

Table 1<\/h2>\n\n\n\n
\n \n \n \n \n \n \n \n \n
<\/td>\n Hourly Pay<\/td>\n Number of males<\/td>\n Number of females<\/td>\n <\/tr>\n
Senior managers<\/td>\n \u00a330<\/td>\n 10<\/td>\n 10<\/td>\n <\/tr>\n
Managers<\/td>\n \u00a320<\/td>\n 30<\/td>\n 30<\/td>\n <\/tr>\n
Staff<\/td>\n \u00a315<\/td>\n 90 <\/td>\n 50<\/td>\n <\/tr>\n
Junior staff<\/td>\n \u00a312<\/td>\n 120<\/td>\n 100<\/td>\n <\/tr>\n
<\/td>\n Total<\/td>\n 250<\/td>\n 190<\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n<\/figure>\n\n\n\n

The organisation ends up with a gender pay gap of 20% in favour of males, which demonstrates that the gender pay gap calculation is highly dependent on the overall composition of the workforce.<\/p>\n\n\n\n

Table 2 shows that more than half the female employees are in the lowest-paid job level, which explains why the median hourly rate for women sits in the lowest pay band at \u00a312. In contrast, for males, the midpoint sits within the second-lowest pay band, making the median pay for men \u00a315 per hour.<\/p>\n\n\n\n

Table 2<\/h2>\n\n\n\n
\n \n \n \n \n \n \n \n
<\/td>\n Hourly Pay<\/td>\n Male representation<\/td>\n Female representation<\/td>\n <\/tr>\n
Senior managers<\/td>\n \u00a330<\/td>\n 4%<\/td>\n 5%<\/td>\n <\/tr>\n
Managers<\/td>\n \u00a320<\/td>\n 12%<\/td>\n 16%<\/td>\n <\/tr>\n
Staff<\/td>\n \u00a315<\/td>\n 36%<\/td>\n 26%<\/td>\n <\/tr>\n
Junior staff<\/td>\n \u00a312<\/td>\n 48%<\/td>\n 53%<\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n<\/figure>\n\n\n\n

With varying numbers of male and female employees in an organisation, understanding the distribution of the genders across job levels is key to interpreting the pay gap.<\/p>\n\n\n\n

In fact, it would be statistically possible for women to be paid more than men for the same role, yet for the organisation still to have a pay gap in favour of men, as shown in Table 3.<\/p>\n\n\n\n

If we change the pay rates in our hypothetical organisation so that women are paid 10% more in each job level, there would still be a gender pay gap of 12% in favour of men. This shows that the gender pay gap might solely reflect workforce composition, rather than differences in pay, for some organisations.<\/p>\n\n\n\n

Table 3<\/h2>\n\n\n\n
\n \n \n \n \n \n \n \n
<\/td>\n Male hourly pay<\/td>\n Male representation<\/td>\n Female hourly pay (10% increase)<\/td>\n Female representation<\/td>\n <\/tr>\n
Senior managers<\/td>\n \u00a330<\/td>\n 4%<\/td>\n \u00a333<\/td>\n 5%<\/td>\n <\/tr>\n
Managers<\/td>\n \u00a320<\/td>\n 12%<\/td>\n \u00a322<\/td>\n 16%<\/td>\n <\/tr>\n
Staff<\/td>\n \u00a315<\/td>\n 36%<\/td>\n \u00a316.50<\/td>\n 26%<\/td>\n <\/tr>\n
Junior staff<\/td>\n \u00a312<\/td>\n 48%<\/td>\n \u00a313.20<\/td>\n 53%<\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n<\/figure>\n\n\n\n

To reduce the gender pay gap, it’s crucial to understand why one group may be overrepresented in lower-paid roles and address any obstacles preventing them from accessing higher-paid positions, rather than focusing on pay in isolation.<\/p>\n\n\n\n

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Going beyond the standard stats<\/h2>\n\n\n\n

Some organisations monitor female representation in senior roles as a key diversity indicator. There are a couple of ways this can be done – and which can leave you with contrasting and contradictory findings.<\/p>\n\n\n\n

As part of mandatory gender pay gap reporting, organisations are required to calculate the percentage of men and women in each pay quartile. In our hypothetical example, the statistic would show that the top quartile is 46% women and 54% men, suggesting that women are underrepresented in the highest-paid roles. However, this doesn’t take into account of the fact that the organisation has fewer female employees overall.<\/p>\n\n\n\n

When we do an alternative calculation using the total number of men and women as the base populations (Table 4), we can see below that, of all female employees, slightly more (21%) sit in the two highest-paid job levels, compared to 16% of all male employees.<\/p>\n\n\n\n

Table 4<\/h2>\n\n\n\n
\n \n \n \n \n \n \n \n \n
<\/td>\n Hourly pay<\/td>\n Male representation<\/td>\n Female representation<\/td>\n <\/tr>\n
Senior managers<\/td>\n \u00a330<\/td>\n 4%<\/td>\n 5%<\/td>\n <\/tr>\n
Managers<\/td>\n \u00a320<\/td>\n 12%<\/td>\n 16%<\/td>\n <\/tr>\n
Staff<\/td>\n \u00a315<\/td>\n 36%<\/td>\n 26%<\/td>\n <\/tr>\n
Junior staff<\/td>\n \u00a312<\/td>\n 48%<\/td>\n 53%<\/td>\n <\/tr>\n
Total<\/td>\n <\/td>\n 100%<\/td>\n 100%<\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n<\/figure>\n\n\n\n

While this alternative statistic does not isolate the top quartile in the same manner as the mandatory reporting approach, the insights it offers may be important for your organisation. You may be more interested in understanding the gender differences across your most senior employees, which is likely to represent only a fraction of your workforce. Alternatively, you could be interested in the representation by gender of all employees with management responsibilities at your organisation. Both measures differ from the top-quartile measure, but may offer more valuable insights for leaders. What is important to understand is that the method you use to calculate representation can reveal different stories from the same data.<\/p>\n\n\n\n

The difference working arrangements can make<\/h2>\n\n\n\n

Flexible working arrangements can reduce barriers for women in the workforce, for instance by enabling those with childcare or caring responsibilities to remain in paid employment and seek career progression while fulfilling other personal duties. The opportunity to work flexibly is therefore important in promoting equality of opportunity for women.<\/p>\n\n\n\n

Employees who choose to work flexibly<\/a>, through arrangements such as part-time working or job sharing, are predominantly women, with the latest data from the Office for National Statistics (ONS) indicating that around three-quarters of part-time workers are female.<\/p>\n\n\n\n

Such flexibility is good for gender equality in the workplace. At the same time, it is important to consider the impact of such arrangements on your organisation’s gender pay gap. For instance, mandatory reporting calculations are based on all employees, not full-time equivalents (FTEs). This means that someone working two days a week counts the same in the statistics as an individual working full time. The increased number of employees working part time could influence the median pay, particularly as part-time working is more common in lower-paid positions.<\/p>\n\n\n\n

Table 5 shows an example of this, using our male data from earlier on. The median hourly pay for male employees was previously \u00a315. Let’s consider that 10% of those in the lowest-paid roles have opted to work part time at 0.5 FTE, and additional employees were hired to fill the gaps from this change to make the job level back to 120 FTEs. The impact of this sees the median hourly pay drop to \u00a312 per hour.<\/p>\n\n\n\n

Table 5<\/h2>\n\n\n\n
\n \n \n \n \n \n \n \n
<\/td>\n Hourly pay<\/td>\n Before: Number of males<\/td>\n Before: Proportion of males<\/td>\n After: Number of males<\/td>\n After: Proportion of males<\/td>\n <\/tr>\n
Senior managers<\/td>\n \u00a330<\/td>\n 10<\/td>\n 4%<\/td>\n 10<\/td>\n 4%<\/td>\n <\/tr>\n
Managers<\/td>\n \u00a320<\/td>\n 30<\/td>\n 12%<\/td>\n 30<\/td>\n 12%<\/td>\n <\/tr>\n
Staff<\/td>\n \u00a315<\/td>\n 90<\/td>\n 36%<\/td>\n 90<\/td>\n 35%<\/td>\n <\/tr>\n
Junior staff<\/td>\n \u00a312<\/td>\n 120<\/td>\n 48%<\/td>\n 132<\/td>\n 52%<\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n<\/figure>\n\n\n\n

On a related note, the mandatory bonus gap reporting requirements take into account only the total bonus awarded to employees. Bonuses are likely paid on a pro-rata basis, so it is understandable that organisations commonly have bonus gaps in favour of men, who are less likely to work part time. Bonus pay gaps may therefore be less useful for organisations as a pay equity measure, unless you account for differences in working patterns in your analysis.<\/p>\n\n\n\n

Taking your pay gap analysis further<\/h2>\n\n\n\n

Monitoring your gender pay statistics in a consistent manner year-on-year is a valuable way to identify changes as they occur and allows you to assess the impact of initiatives. However, positive steps towards gender equality could initially result in increased gender pay gaps. For example, hiring women in entry-level roles in industries in which women have not traditionally worked and which require initial training and experience, could widen the gap temporarily, even though it may result in higher long-term earnings in the future.<\/p>\n\n\n\n

Conversely, a reduced gender pay gap does not always reflect positive practices. For example, if an organisation with a gender pay gap favouring men stops hiring or replacing female workers in junior positions, the gap might narrow. This highlights how decisions unrelated to pay can impact the gender pay gap and that it can be artificially reduced without genuine progress having been made.<\/p>\n\n\n\n

In conclusion, by focusing solely on the headline gender pay gap statistics, you may be ignoring important aspects of what it takes to promote a genuinely diverse workforce. It’s essential to create statistics that are meaningful for your organisation. By understanding the factors that drive your statistics, you will put yourself in a position to drive meaningful change.<\/p>\n\n\n\n

Pay Equity Analytics<\/a> – part of the Brightmine portfolio – offers HR and reward professionals advanced pay equity solutions to provide actionable insights on existing pay gaps, using advanced statistical analysis to identify variables for employee demographics such as gender, ethnicity, sexual orientation and disability, identifying the causes of pay gaps, and proposing and tracking remedial actions.<\/p>\n\n\n\n

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About the author<\/h3>\n\n\n\n
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Hannah Mason<\/strong><\/p>\n\n\n\n

Hannah joined Brightmine as a HR data insights analyst following four years working in research and analytics in the Civil Service. She works on the development and delivery of surveys covering a variety of HR topics. These surveys provide data for both the Benchmarking – HR metrics tool, as well as survey analysis reports.<\/p>\n\n\n\n

Before joining Brightmine, she worked at the Office for National Statistics as a senior social researcher working on the development of a variety of surveys, data analysis and publications, focusing on topical issues facing society including the COVID-19 pandemic. Hannah holds a BSc in Psychology.<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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Now that the annual deadline has passed, it is a good time to analyse your organisation’s gender pay gap calculation in detail. 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