In Hackney, our ambition is to be evidence-led in everything we do – this includes ensuring that our strategies, services plans and key decisions are informed by what we know about the borough and the people who live and work here. The Strategy team are currently developing two key strategies around poverty reduction and fostering an inclusive economy and HackIT have joined forces with them to help build a picture of poverty in Hackney today.
The go-to data source on poverty for small areas is the Index of Multiple Deprivation (IMD) which combines 37 different indicators across 7 ‘domains’ of deprivation (income, employment, education, health, crime, barriers to housing and services, and living environment). Whilst this data offers valuable insight, it has limitations and doesn’t always tell the full story:
The first key limitation highlighted above is that the IMD is good for understanding how deprived an area is in relation to others, but not how deprived an area is in absolute terms. This means that if nothing changed in Hackney but other areas got worse, Hackney would appear less deprived even though the experiences of our residents had not improved.
This relates to the second key limitation of the IMD: its relative nature does not enable us to see change over time, and this data is only published every 4-5 years. On top of that, the underlying data behind the index is generally 2-3 years old by the time it is released. We know that Hackney is changing quickly, so we need to make sure we have up-to-date information. We also need to be able to see whether poverty is increasing or decreasing to better understand whether our approach is working.
Over the past 6 weeks we’ve worked on a short data project to build a prototype of a Hackney Poverty Index in an attempt to fill this gap. We wanted to learn from the concept and methodology of the IMD to build our own index that combine open data alongside data we hold within the Council.
We aimed to identify at least one good indicator from each of the 7 IMD ‘domains’ to include in our prototype. We compiled a list of possible indicators and evaluated these in terms of:
- data quality – can we trust this data?
- granularity – is it available for small areas below borough level?
- frequency – is it up-to-date and refreshed regularly?
- coverage – is the data missing key sections of our population?
- access – is it easily accessible from our systems, or openly available?
We were able to go above and beyond the 7 indicators we set out to include in our prototype, and in the end included 13 different datasets. These ranged from an indicator which identified the proportion of households who were in debt to the council, emergency admissions to hospital, and air quality. We did, however, face challenges identifying good datasets for some areas (education in particular) and had to be pragmatic with our choices.
We brought together these datasets in Qlik, our business intelligence tool to transform, analyse and visualise data. The Hackney Poverty Index dashboard is now available for officers across the council to test out and give feedback on.
Our prototype is already generating insights that we didn’t have before. The maps below show that our local data is able to provide a much more granular picture than is available in the IMD (this data can be mapped at Output Area level). Our local data also shows a different pattern of income deprivation than the IMD 2015, with more poverty in the north of the borough. It is difficult to say whether this is due to changes over time (the underlying IMD data is likely to be from 2012-13) or for methodological reasons. We’ll be exploring this more when a new release of IMD data is available in October.
This prototype is just the beginning of a Hackney Poverty Index. We know that there is a lot more work to do! We expect to start the next phase of this project in late September when we’ll be:
- further refining the themes and indicators we use to measure poverty
- bringing together these indicators into an index which provides a single measure of poverty in Hackney
- researching what functionality users need to understand and analyse the data
- making the next iteration of the Index available to the public
- providing more analysis alongside the data to tell a story