Any digital inclusion project, programme or intervention is likely to have this question high on their agenda: “How do we know who is digitally excluded so that we can target our resources most effectively and efficiently to have the most impact?”
This chapter explains how we started doing this in Leeds, and how we’ve refined our approach over time. We’d like to hear your experiences and will add them to this article.
Barriers and personal indicators
Digital exclusion is an indicator of social exclusion. It’s a multi-faceted issue that cannot be easily defined and measured. National research over many years has identified the main barriers to digital inclusion. These include:
- Skills and confidence to use technology
- Access to, and accessibility of, equipment and connectivity
- Motivation to get online and an understanding of the benefits of digital inclusion
There are also personal indicators that suggest certain groups of people are more likely to be digitally excluded if they are:
- Homeless or at risk of homelessness
- Refugees, asylum seekers and anyone who has English as a Second Language
- Living in poverty or on a low income
- At risk of, or already experiencing, social isolation
- Living with long-term health conditions
- Older people
- Living with physical or learning disabilities
- Overcoming issues such as addictions and substance misuse, domestic abuse or mental health issues
These factors apply in combination with the barriers so that there is no single indicator that can predict accurately whether an individual or a community is digitally included or excluded. It also means that there is no single solution or intervention that will ‘solve’ digital exclusion for everyone.
We can use these high-level indicators to show the kinds of people who are more likely to be digitally excluded, we can add local data on areas of the city, town or region where digital exclusion is likely to be higher, and we can address the barriers to digital inclusion that are likely to be common across all of those people and places. 100% Digital Leeds has developed an approach to digital inclusion that is robust enough to tackle the barriers while being flexible enough to adapt to the needs of different groups and individuals in different areas of the city.
Mapping digital inclusion with national data
Any exercise to map digital inclusion needs to be clear on why the work is being done, how robust is the data and where does it come from, and what the mapping exercise will/ will not show.
Over the years that 100% Digital Leeds has reported to Leeds City Council’s Scrutiny Board inquiry into digital inclusion, we have been asked to “identify and target priority areas for support”. Initially, we used national indicators such as the Consumer Data Research Centre’s Internet User Classification map as well as commercial segmentation data from Experian Mosaic. Our report to Scrutiny Board in 2017 included the warning that:
“These results must be used with caution. The analysis has relied on commercial segmentation data from Experian Mosaic representing just 11.5% of Leeds households. The analysis is not derived from real-world data; it is derived information from a third party source that provides a modelled view of the criteria.
“These caveats mean that the figures should not be directly quoted as a statement of fact such as, ‘Ward XXXX has 36% of residential households that are digitally excluded’. Instead, we can state that, ‘According to modelled socio-demographic data, Ward XXXX shows a high proportion of households that could be considered digitally excluded’.
“Despite these warnings, the data analysis is robust enough to help us focus our digital inclusion work in the areas of the city with the greatest need.”
We also used data from the Tech Partnership Digital Exclusion Heatmap to calculate the number of adults in Leeds who are likely to be digitally excluded. The heatmap combined a range of digital metrics on connectivity to Broadband, 4G and digital usage, together with open source social metrics on age, education, income and health. In combination, this created a tiered, 9-point scale measuring likelihood of overall digital exclusion (or inclusion).
More recently, the Lloyds Bank Consumer Digital Index has become the UK’s largest study of transactional, behavioural and attitudinal research including the Essential Digital Skills measure.
Mapping digital inclusion with local data
We had been set a specific task by the Leeds Scrutiny Board to identify and target priority areas for support. The data we used gave us some broad understanding of the number of people in Leeds who were likely to be digitally excluded and the areas of the city where digital exclusion was likely to be higher. But we wanted to add some certainty to those likelihoods.
For our 2018 Scrutiny Board report, we collected and analysed a range of real-world data to give a more accurate picture of digital inclusion/ exclusion in Leeds. This basket of indicators included transactional data for Leeds citizens using council services and a survey of Housing tenants in Leeds. All of the data was arranged by wards.
The six datasets that we used for our mapping exercise were:
- Number of Primary School Admissions applications undertaken in paper format
- Number of Secondary School Admissions applications undertaken in paper format
- Number of citizen contacts via the Council Contact Centre rather than the online portal
- Number of uses of the council’s bin app
- Number of housing tenants reporting no confidence to make a benefit claim online
- Number of housing tenants without internet access
For each dataset we listed the wards that were above or below the average for that indicator. This gave us six lists that illustrated the likelihood of digital exclusion, with some wards appearing multiple times across those six lists. We used this as the measure to give us our aggregated view of digital inclusion/ exclusion.
The 11 wards that appeared four or more times were listed in the report and these became the wards where the Board agreed that we would focus our digital inclusion activity. After discussions with colleagues in Housing and further analysis of data from their Annual Home Visits survey we added one additional ward plus three of the Council’s six priority neighbourhood areas.
This was agreed in our 2019 report to the Scrutiny Board, however we added the following caveat: “We are taking an 80/20 approach to our targeted work. 80% of our work will be in these priority geographic areas but we retain 20% flexibility to work outside of these areas if we identify priority groups who are at high risk of digital exclusion”.
Even after three years of looking at data from national and local indicators, we wanted to retain some flexibility in our approach. We used the evidence to establish our remit and focus for 100% Digital Leeds at a programme level.
We know who we are focusing on and where we are targeting our work. We also have the flexibility to adapt and respond as we work with partners across the city because we recognise that digital inclusion is a multi-faceted issue that changes as people’s life circumstances change or as society changes around them.
Our latest work in this area is with Communities of Interest and colleagues in Health and Care to better understand digital inclusion through the prism of health inequalities and Population Health Management.