We co-hosted an interactive session on equalities data, together with Christine Goodall, Network Coordinator of HEAR Equality and Human Rights Network, as part of the Data4Good festival.

Increasingly, charities and social enterprises need to collect equalities data about their service users, beneficiaries, staff, Trustees and volunteers – it may be required by funders, but it is important to use this data to improve inclusivity, service delivery and recruitment practice. The aim of this session was to challenge participants to think about why and how we collect equalities data, especially to ensure that this isn’t just a tick box exercise.

We had over 70 people join this session, and we started by asking people to share in the chat something about their own unique identity – some have shared their gender identities, sexuality, and other what are termed ‘protected characteristics’ in the EqualityAct, but many also shared their hobbies, passions and jobs. We wanted the participants to really understand the importance of self-identification, by providing them opportunities to self-identify – hence the session’s topic, “I am Me”. 

We then had participants  play an assumptions game, where they were asked to share verbally the assumptions they formed about  each other. Participants shared some reflections from the game:

• People felt it was really uncomfortable and were worried about saying the ‘wrong things’
• but also some reflected on the assumptions we may make based on names or physical characteristics
• and some intentionally tried not to make assumptions
• Uncomfortable verbalizing assumptions before hearing how people would like to identify

And this discomfort is what we may inadvertently subject our stakeholders to, when we seek to collect equalities data from them. How can we therefore overcome this challenge?

First and foremost, we need to critically assess the purpose of collecting equalities data, and be transparent about it. Collecting equalities data is a great way for the voluntary sector to achieve its mission: To increase impact on the most marginalized; to ensure everyone is reached; and to identify gaps or needs in service provision. But often we collect data without asking why, or even if we do know why, we do not clearly communicate it to the people we collect the data from.

There is always the balance to strike between the need for harmonised and structured data, and allowing for self-identification, and that balance constantly needs calibrating. Our advice is that organisations should look to follow standards such as DEI Data Standards, which are currently being adopted by funders, while including fields for self-identification.

However, some participants suggested that if people do choose that option of self-identification, it could give a sense of ‘Othering’. There is also a point made that classifications can cause offence and reinforce the biases of the ones collecting the data. We acknowledge these two potential risks, and to mitigate these risks, our advice is that stakeholders should be involved in the design of equalities data collection processes. This includes reviewing or designing the questions, deciding how the questionnaires should be administered, and deciding how the data can be shared. Collecting equalities data should never be an extractive exercise and should be in line with the ethos of equity and inclusion – the very reason why we want to collect equalities data in the first place.

The assumptions game also showed that we all have many facets to our identity, and we introduced the concept of intersectionality – the interconnected nature of social categorizations such as race, class, and gender as they apply to a given individual or group, which create overlapping and interdependent systems of discrimination or disadvantage. How best can we capture that? As more organisations start collecting equalities data, analysing data across multiple identities, and sharing their results and learnings, we will start to get a better picture on this. But at least the session started us off on some practical tips and we hope to see more learnings in equalities data collection in the next Data4Good festival!

If you are interested to talk about this, please contact TSIC at [email protected] or Christine at [email protected]