Knowing me, knowing you: there’s a lot we can do… on equality data

Alicja writes a piece for WHQ on the importance of equality data analysis, and how it should form a key part of assurance and service improvement for housing organisations (original article published in Welsh Housing Quarterly Issue 134: Summer 2024) 

Next year will mark 20 years of Tai Pawb, 12 years since I joined this wonderful organisation and 18 years since I started working in the so called ‘equalities’ field. As I reflect on equality in housing in this period, I think about the wins, the losses and the ever-present, wicked problems we need to deal with –  equality data is one of them. 

Housing sector has certainly got strong equality values and a recognition that data is important to what we’re doing. Most people understand the importance of equality data to developing equitable services, making fair decisions, meeting diverse needs and so on, but we just don’t seem to be able to crack it.  

At times we find ourselves going round in vicious circles which look like this: we cannot use our equality data because we haven’t got enough of it but in the next year or two we are going to collect it, after which we will be able to carry out equality analysis we will then embed it into our ways of working and, together with great engagement, we will be a much better, more diverse and equitable organisation.  

At times organisations will do a fantastic job on step one – collection –  but stop there, for multiple reasons. At times they will get to step two – doing some analysis. Sometimes the analysis will reveal very different housing experiences amongst some groups and it will actually have impact on service change – that’s where we in Tai Pawb get really excited and there are certainly some great examples out there! But, most of the time, this is where things stop. After a few years the data gets out of date, other priorities take hold, staff and capacity changes and we are back to square one.  

 It is still relatively rare for organisations to have embedded the usage of equality data in their processes and over the years we have had some insights into why this might be. Of course, it is easier said than done and we are not here to point fingers and pretend that the above is easy, but below are some insights from our work. 

Leadership and strategic oversight: Collecting and, more importantly, using equality data needs commitment from the top. Resourcing, understanding the importance, using and monitoring at the highest level is critically important. Good equality data is a fundamental part of board assurance in the area of equality, diversity and inclusion. Lack of strategic commitment and oversight of this area will undermine the importance of using equality data and lead to data development projects being dropped after initial enthusiastic collection or analysis. Consequently, reliance, meaning and use of equality data will be undermined and mostly depend on the commitment or goodwill of operational staff, and as staff, systems and priorities change – the use of equality data disappears. 

In the past 18 months or so, we have been running a QED Leaders pilot with the kind assistance of Melin Homes. QED Leaders is the next level of our award-winning EDI accreditation, and strategic focus and use of equality data and evidence is a key component of the standard we are developing.  

In the process, Melin Homes have developed strategic KPI’s related to equality, diversity and inclusion overseen by the SMT and board. Their KPI’s include: % of equality data collected for tenants and for staff (a fundamental and continuous one); EIA completions (to keep equality impact on the agenda) and Gender Pay Gap. In 2024/25 Melin will focus on developing equality KPI’s on repairs and complaints. 

 I imagine that every SMT and board oversee one or two KPI’s which tell them how well the organisation is doing with its repairs – be it average number of reports, completion times or satisfaction, but what do these figures look like for different groups? Does everyone have equal access to reporting? Are any groups less satisfied than others? What does stock condition look like for different groups of tenants? (our 2023 survey showed that only ca.50% of social landlords had the ability to break stock condition data down by household characteristics, and for some, this revealed that e.g. ethnic minority tenants did live in poorer conditions, for various reasons) 

Such analysis should no longer be seen as a side project but a core part of assurance and service improvement: I wonder whether this sort of data, presented clearly and flagged for issues might have revealed something to the organisation which housed Awaab Ishak. Arguably issues related to stereotyping certain groups of tenants might have come out in differences in satisfaction between different groups or numbers of complaints? Naturally, statistics are not everything and conversations with diverse tenants are equally important.  

Invariably, I have ran out of space to delve into other challenges and how to overcome them but here is a short summary of other things to think about:  

Awareness: collecting equality data is only the start and it is clever use of such data where the real value transpires. Sadly, we often find that large proportions of staff and tenants do not know why equality data is collected and how it is used (probably because sometimes it isn’t). This results in high proportions of non-returns. Good news is, that the more awareness you raise around this, the more likely it is that people will trust you and share their data (but you need to do something with it of course). Check out slide 10 in our QED impact tracker which shows that awareness can improve data returns two fold – this also builds trust.  

Privacy: GDPR can sometimes be perceived as a stumbling block to collecting equality data, but it shouldn’t be. Check out this quick Tai Pawb guide to GDPR and equality data.  

Comparisons: Some diversity related data needs to be comparable to wider population data. Check our Census 2021 pages where we have pulled out ready population diversity data, including maps. For guidance on what categories to use – refer to Tai Pawb template monitoring forms and guidance.  

Alicja Zalesinska, CEO of Tai Pawb