ELBA Demographics and pay gap data

ELBA is committed to publishing on an annual basis data about the protected characteristics of staff and our Board, and both gender and ethnicity pay gaps.

Each year we conduct a data collection exercise, normally in July. It is a snapshot of our team at that moment in time. Responding to the request for personal data is voluntary, but we normally have a 100% response rate.

We have a series of actions we are taking to try and reduce our pay gaps and to have diversity which reflects East London at all levels in the organisation.

Our Actions:

1. We have set a target to close both our Gender and Ethnic pay gaps by 2025.
2. We will measure our progress annually and publish the results on the ELBA website.
3. We will get beneath the surface of the pay gap data and identify if there are clusters at different levels in the organisation, or in different teams. From a better understanding of our data we will be able to take actions to narrow the gaps. Pay gaps may be an indication of changes in recruitment to build a pipeline for future managers and leaders.
4. ELBA has an internal equalities group – ELBA Inclusion Group – set up at the instigation of the staff team and led by them. We will continue to encourage and support EIG and the action plans they develop.
5. All ELBA posts will openly advertised to encourage people from all backgrounds to apply. Only in rare or urgent circumstances will there be exceptions for business reasons.
6. We aim to have all our recruitment panels made up from the diversity of our staff team.
7. We will take targeted action, including training to assist progression where we can see there is under-representation at certain levels, or in certain job roles. We aim to support progression of all staff. At the last time of measuring (2023) 57% of our people have been promoted while at ELBA, which rises to 71% for those who have been with us for over 12 months.

ELBA follows the Government guidance for calculating the gender and ethnicity pay gap. You will see that two measures of the gap are reported – the mean and median. Both values tell us slightly different things about pay discrepancies. This is a general explanation (ie not specific to ELBA) of the differences in the how the measure are calculated and how they can help understand pay gaps.

Mean:

• Calculation: The average of all individual salaries within a group. It’s found by adding all salaries and dividing by the number of individuals.
• Sensitivity to outliers: Highly susceptible to outliers, especially a few individuals with significantly higher or lower salaries. These extremes can skew the average and misrepresent the “typical” pay within the group.
• Pay gap interpretation: A high mean pay gap often indicates a large discrepancy between the average salaries of men and women, with men typically earning more. However, it doesn’t necessarily represent the “middle ground” of earnings for most individuals.

Median:

• Calculation: The middle value in a set of salaries arranged in ascending or descending order. If there’s an even number of salaries, the median is the average of the two middle values.
• Sensitivity to outliers: Less affected by outliers compared to the mean. It provides a better picture of the “typical” salary within the group, as it’s not skewed by extreme values.
• Pay gap interpretation: A high median pay gap suggests a significant difference in the salaries of individuals at the middle of the earnings distribution for men and women. This might indicate systemic issues related to promotions, job assignments, or pay structures.

Key differences in reporting:

• Overall picture: Mean reveals the overall distribution of salaries, including the influence of high earners. Median focuses on the central tendency of salaries, representing the typical worker’s experience.
• Impact of outliers: Mean can be significantly distorted by a few outliers, whereas median is more robust.
• Interpretation: Mean pay gap might seem larger and highlight the extent of the disparity, while median pay gap portrays the situation for the majority of individuals.

This table shows the trends in our pay gap data:

We looked into the differences between 2022 and 2023. For gender, the changes were mainly a result of a senior colleague who was on maternity leave. Employees on Maternity Leave are excluded from the calculations under the government guidance. As a smaller organisation, changes to a small number of staff can make a make a big difference in the % outcome.

The ethnicity changes were accounted for recruitment of more non-white people to build a talent pipeline for our future promotions.