In this blog Mahdy Alraie, Senior Project Officer, digs around in the Indices of Multiple Deprivation to see what it can tell us about the places we deliver employment support.

We support people into sustainable jobs by giving them one-to-one support with an employment advisor. This often means helping them overcome barriers to employment such as lack of experience, language skills and low confidence but there are many other reasons why participants may not be in employment.

We know that 72% of participants on our programme, Refugees Into Sustainable Employment (RISE)  have reported four or more barriers to employment and that a recurring barrier reported to our employment advisors is housing.

In recent years we have sought to adapt our support to help participants with housing issues.

“We opened housing advice slots on top of our regular employment support appointments but supporting participants into employment while they have complex housing issues is a challenge.”

Faisal Ahmed, RISE adviser

Of all the barriers to employment, our experience tells us that housing issues can be some of the hardest to overcome.

“The need for housing advice and support has become more prevalent with each passing quarter… We created links with housing associations and homeless charities for additional support, but housing issues can take several months to solve. Unfortunately there is no easy or quick solution to this.”

Gerrar Ahmed, RISE Programme manager

So, given we know from our experience and our data that housing is a major barrier to employment, can we build a better understanding of why that is by interrogating the IMD data?

The Indices of Multiple Deprivation (IMD) 2019 were released in September, and I took this opportunity to triangulate the data with what we know.

What is IMD?

The Indices of Mass Deprivation, or IMD, is a relative measure: it doesn’t tell you how deprived a place is, rather it tells you how areas are more or less deprived than others (you can read more on that in this Statistical Release, which provides some insights comparing ranks of local authorities between 2015 and 2019). The IMD is based on 39 indicators, organised across seven ‘domains’. The domains are income; employment; education, skills and training; health and disability; crime; barriers to housing and services; living environment, and they are combined and weighted to calculate IMD.

It’s important to know that the domains are not weighted equally – some are given greater importance than others. For instance, employment deprivation is weighted by 22.5%, while barriers to housing and services is weighted by 9.3%.

Weighting of the IMD domains

The weighting of each IMD Domain.

Get the full picture on weighting of the domains here in Appendix G of the Technical Report.

Why does the weighting of domains matter?

Looking at the IMD breakdown scores of the places we are interested in, helps us to understand what domains are influencing the overall deprivation score. By delving into the IMD data, I realised that areas with similar overall IMD scores may score very differently in each domain. As a result, areas ranked as ‘the most deprived’ in certain domains, may not be ranked as ‘the most deprived’ at an overall IMD level.

overlapping IMD with domains
Overlap of 30% most deprived areas by overall IMD and 30% most deprived areas by each domain.

The overlap is greatest for the income domain while it is smallest for barriers to housing and services, which shares only a third of the most overall deprived areas. That means barriers to housing and services is the most unrepresented IMD domain when considering the 30% most deprived areas, followed by living environment which includes indicators such as housing in poor condition, and houses without central heating.

What can this tell us about the people we support?

I selected a sample of recent participants on Renaisi’s RISE programme to find out more. RISE operates across 10 North and East London boroughs, some of which are the more deprived local authorities such as Hackney, Haringey, and Barking & Dagenham.

This analysis is interesting but it only tells us so much about the places participants come from. By delving into the breakdown of IMD scores by domain, we can get more of an understanding of the key drivers of deprivation in an area, and consider if these may be significant barriers to employment.

Most deprived (1-3) IMD domains breakdown758 RISE participants
Overall IMD61%
Education and Skills23%
Health and disability18%
Barriers to Housing92%
Living environment67%

When looking at the overall IMD, 61% of RISE participants live in the 30% most deprived areas. When looking at the IMD sub-domains, 92% of participants on RISE are in the 30% most deprived areas relating to barriers to housing and services.

In contrast, 47% of RISE participants live in the 30% most deprived areas relating to employment. This suggests that the issues of deprivation that are most dominant in the places our participants live relate more to housing than employment.

What should we do?

You can draw lots from the data, not least that without some digging, the IMD won’t tell the whole story of the deprivation of an area.

Nearly three quarters of RISE participants have four or more barriers to employment, which is why we’ve taken steps to provide and sign post to support but a more joined-up approach, with other support services, is needed to help people facing multiple barriers to work.

In the areas we deliver RISE t’s clear that to successfully support people into employment, then housing and homelessness issues must be taken into account by those providing and funding the services. We’ve also got early findings that the same applies to other areas we deliver.

We urge funders of employment services to embed housing support into future project outcomes to give more people the opportunity to overcome a key barrier to sustainable employment.

Next I’ll be comparing this data with that of another of our programmes, Southwark Works to build a fuller picture of how housing can impact on a person’s employability.