The Importance of the Average
When talking about pay data, the term average appears time and time again, but what does it actually mean?
Put simply, an average salary gives us one figure to help describe pay across a group of employees. It takes all the salary values from that group and calculates a figure that would represent a ‘typical’ employee in that group.
This is useful because it allows us to compare pay between different employee groups without having to look at every individual salary.
The average can become an even more powerful metric when we begin to understand and analyse the different ways it’s calculated.
It might seem counterintuitive that a figure like the average can be calculated in different ways and possibly provide different answers. After all, how can the same set of salaries produce different averages?
The key is that each method looks at the data differently, helping us bring a different part of the picture into focus.
There are two types of average that are particularly important when it comes to understanding pay: the mean and the median. So, how do they work, and what can each tell us about pay? Let's introduce them using a simple example company, PeopleTech Ltd.
The Mean: What would everyone earn if pay were shared equally?
The mean is what many people think of when they hear the word average. It shows us what each employee would earn if the company's total pay were shared equally among everyone.
In everyday conversation, the terms mean and average are often used interchangeably. However, this isn't technically accurate, as the mean is just one of the ways to calculate an average, as we'll explore later on.
To calculate the mean, we simply add together all the salaries and divide the total by the number of employees.
Let's look at the example company, PeopleTech Ltd.
Imagine the five employees earn the following annual salaries:
€30,000 + €40,000 + €40,000 + €50,000 + €100,000 = €260,000
PeopleTech Ltd. has a total annual salary bill of €260,000 across its five employees. To calculate the mean, we divide this total by five:
€260,000 ÷ 5 = €52,000
So, the mean salary at PeopleTech Ltd. is €52,000.
In other words, if the company's total salary bill were shared equally between all five employees, each person would receive €52,000.
The mean is useful because it gives us an overall picture of pay across the company. However, as we'll see, it doesn't always reflect what most employees actually earn, particularly when there are significant differences between the highest and lowest salaries.
The Median: What is the salary in the middle?
But what happens when one or two employees earn significantly more than everyone else? This is where the median can give us a different perspective.
While the mean looks at the total of all salaries, the median looks directly at the middle of the data. Imagine arranging all our employees in a straight line, from the lowest-paid to the highest-paid. The salary of the person standing in the middle would represent our median salary.
Let's look at PeopleTech Ltd. again.
Using the same salaries as before, we arrange them from lowest to highest:
€30,000 | €40,000 | €40,000 | €50,000 | €100,000
The middle salary is €40,000, making this the median salary for PeopleTech Ltd.
What makes the median particularly useful is that it is not affected by unusually high or low salaries, often referred to as outliers.
In our example, let's assume the €100,000 salary belongs to the CEO, which is double the next highest salary. This unusually high salary pulls the mean upwards, making the average salary appear higher than what most employees actually earn.
The median, however, is not affected by this unusually high salary. At €40,000, it gives us a different perspective on what a typical employee earns in PeopleTech Ltd.
This is particularly useful for HR professionals because it helps us understand what employees typically earn, without the results being skewed by a small number of particularly high or low salaries.
Neither figure is wrong. They simply tell us different things about how pay is distributed across the company. Looking at both together gives us a more complete picture than relying on either one alone.
One thing to note: when there is an even number of employees, there won't be one person sitting exactly in the middle. In this case, we take the two middle salaries and calculate their average to find the median.
How does this all relate to the EU Pay Transparency Directive?
The EU Pay Transparency Directive requires employers to report on both the mean and median gender pay gap. These gaps are calculated by finding the average pay for male employees and the average pay for female employees, and then measuring the difference between them. The difference is expressed as a percentage of men's average pay. For example, a gender pay gap of +10% means that women's average pay is 10% lower than men's average pay.
But why does the Directive want to look at both figures?
The size of a company's mean gender pay gap and median gender pay gap can tell us different things about how pay is distributed across the organisation.
If a company's mean gender pay gap is larger than its median gender pay gap, this could suggest that higher-paid employees are having a greater influence on the overall gap. Think back to our PeopleTech Ltd. example, where the CEO's €100,000 salary pulled the mean upwards. A similar effect could occur in an organisation where the pay gap between most male and female employees is relatively small, but a highly paid position, such as the CEO role, is occupied by a man. Even though the difference in pay across the wider workforce may be relatively modest, this one high salary could pull the mean upwards and result in a much larger overall gender pay gap.
On the other hand, if a company's median gender pay gap is larger than its mean gender pay gap, this could suggest that the difference in pay is more evident across the wider workforce, rather than being driven primarily by a small number of highly or lower paid positions. In other words, the gap may be more noticeable among employees around the middle of the pay distribution, rather than being concentrated at the top. This could highlight wider differences in how men and women are paid across the organisation, and may warrant further investigation.
It is important to remember that neither the mean nor the median tells us exactly why a gender pay gap exists. They are indicators that help us identify patterns and differences in pay, rather than explanations in themselves.
By looking at both measures together, HR professionals can begin to build a clearer picture of pay within their organisation, identify areas that may need further investigation and take a more informed approach to understanding and addressing any gaps.
