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‘Left behind?’ Understanding communities on the edge


The term ‘left behind’ has featured increasingly in social policy discussions in recent years. Here, Stefan Noble from OCSI shares how they have been working with Local Trust to develop a quantitative measure of left-behind areas using open data.

As part of this, for the first time, a Community Needs Index has been created, including economic aspects of deprivation and the social and cultural factors that can contribute to poorer outcomes, such as the levels of grant funding going to different communities.

Image of a dark alley.

‘Three pillars’ of challenges – poor connectedness, a lack of places to meet and low levels of participation – may lead to communities being ‘left behind’. Photo: Štěpán Vraný

At Oxford Consultants for Social Inclusion (OCSI), we focus on providing insight about local communities using data. We have worked with Local Trust on a few bespoke projects over the years, to better understand the context of areas they focus on in their Big Local programme. They also use our Local Insight platform to provide instant access to up-to-date data for the groups they work with about their communities.

Our project to better understand ‘left-behind’ communities was born out of conversations between Local Trust and the people in Big Local communities, about the challenges they face.

Over time, a lot of the same themes kept coming up: people were experiencing challenges such as i) poor connectedness, ii) a lack of places to meet, and iii) low levels of participation. This led to a theoretical idea that having these ‘three pillars’ of challenges – especially when they interact with deprivation – could represent a meaningful left-behindness that could have a real negative impact on communities.

Our task at OCSI was then to see whether it was possible to produce a robust and quantitative measure of these challenges using open data (data made open in the 360 Data Standard, and from elsewhere) at a small area level. The Index of Multiple Deprivation (IMD) – which we updated on behalf of the Ministry for Housing, Communities and Local Government (MHCLG) in 2015 and 2019 – already provides the data on deprivation. Alongside this, in order to better understand the social and cultural elements, we produced for the first time a Community Needs Index, which brings together various sources of information into one single index. The full set of indicators is available below, and the Community Needs Index is available in Local Insight for subscribers to explore.

‘Left-behind’ areas are defined as the areas that fall in the bottom 10% on both the IMD and the Community Needs Index.

The resulting report ‘Left behind? Understanding communities on the edge’ suggests that multiply deprived areas – when combined with the absence of places to meet, the lack of an engaged community and poor connectivity – fare worse than other deprived areas.

We hope the research will be useful for practitioners working on resource allocation, particularly around social infrastructure. More generally, we hope that it will shine a light on the importance of social and cultural issues, as well as the economic issues, when it comes to designing and delivering public services.

So far, the research has been cited by the Government’s Industrial Strategy Council, made an appearance on Sky News, and featured in The Economist.

Grant funding and the Community Needs Index

As part of developing the Community Needs Index, we included data on the level of grant funding for each local area using data published in the 360Giving Data Standard.

We contained our analysis to only include:

  • National funders: We wanted to avoid bias that might result from particular regions or local authorities happening to have a higher proportion of organisations including their data in the 360Giving Data Standard.
  • Grants with a local geographic identifier associated with it: We needed to be able to attribute the grant to a local area, so the grant needed to include a beneficiary postcode or Lower Layer Super Output Area (LSOA), for example.
  • Locally focused grants: Grants over £1 million were excluded, so we weren’t including large national programmes such as large housing or infrastructure grants.

We also looked at local government core funding levels in left-behind areas, other deprived areas and England as a whole. The results were surprising: we found that the left-behind areas, despite having greater needs, were getting less funding than other deprived areas. And both were getting less funding than the national average.

Our data wish list

This part of the research would have been really difficult and nowhere near as robust without access to the goldmine that is 360Giving data. Of course, it would be ideal if every grant funder published their data openly, as we would then have an easily accessible and comprehensive national dataset. We would love to see every large national funder on 360Giving, as well as the entire network of Community Foundations whose grants would be really instrumental in better understanding local giving at a national scale.

Most of our work is focused around understanding small communities, and so being able to access grants data with geographic signifiers is invaluable to us. Although many of the grants shared in the 360Giving Data Standard may include data on wards, postcodes or local authorities, including standard statistical geographies such as LSOAs and Middle-Layer Super Output Areas (MSOAs) would be really useful for researchers (take a look at our blog for an introduction to these terms).

Although these standard geographies may not be meaningful in terms of a ‘community’ boundary, they are more easily comparable as they are fairly homogeneous in size. Equally, it means we can more easily compare grantmaking data with other socio-economic datasets (such as crime, unemployment, health conditions), which are usually published at these standard geographies.

What’s next

We are now moving into the next phase of our project on left-behind areas. This will include updating some of the data (for example, including IMD 2019), looking for additional data sources (for example, engaging with grantmakers not currently publishing data in the 360Giving Data Standard) and a methodological review.


If you have any questions on the left-behind areas project, please get in touch with Jeremy Yung at Local Trust at To explore the data for yourself in Local Insight, sign up for a demo.