As part of the work exploring the charity data eco-system I wanted to have a look at who funds what when it comes to data. Ok so that is probably too broad a question to answer and an almost impossible task with current available data. Without workforce data (to understand roles/salaries) and detailed funding data for all UK charities I will have narrow my search to
Which grant-making organisations have funded ‘data’ work in the UK over the past 5 years and how much have they invested into the eco-system via grants?
I was also interested in how funding for ‘data’ compared to funding for ‘digital’ and if there had been a change over the 5 year period. So I took a look at Grantnav and had a ponder.
You can read about how I went about this at the bottom of the page. All steps and rational explained. Note, this is not an extensive study
Who funds ‘data’ work in the charitable sector?
You can explore the chart here
Who funds ‘digital’ work in the charitable sector?
You can explore the chart here
How does funding for ‘data’ compare to funding for ‘digital’?
And so, this is where I ended up. A chart showing grants for UK organisations for ‘data’ work vs ’digital’ work .
You can explore the chart here
A warning and an idea
I was warned to be careful with trends over time from 360 Giving data. This is because funders are brought on at different times and there may be incomplete data for some years, or completely missing for some funders for some years. I therefore did look at funders for which there were a full 5 years and compare those. One of those was The National Lottery Community Fund. And this was fascinating….
The first thing that is immediately clear is that NLCF have invested significantly more in ‘digital’ than ‘data’. However the thing that struck me most is the divergence from 2016 onwards.
Look closely at 2016. Yes, they are exactly the same amount.
Identical because they are the same grants. Anything that had a key word of ‘data’ also had a keyword of ‘digital’ and vice versa. And after 2016? Well clearly something changed.
Funding, policy and attention
I’ve always maintained that as well as being important sources of money, foundations are huge shapers of policy, attention, action within the charity sector. It’s obvious really. If a funder states they will fund something, charities will naturally take that as ‘important’. Take key terms and look at trends within the sector over time. If funders put the term in their grant title the number of applications with that term in an application with increase, and therefore a charity will prioritise that activity if they can (and are successful in being funded to do so.)
Now you may be thinking that NLCF had a whole fund devoted to Digital, called ‘The Digital Fund’ and so of course that has skewed the previous chart. But what if I told you that
- The Digital Fund was 2019 only and counts for ~60% of digital funding that year from NLCF
- Well, that’s kind of my point. They were intentionally focusing on it, and therefore others (including in their own organisation) also focused on it too.
- Imagine if there was a Data Fund….
Shaping the data eco-system is therefore as much about policy and strategy as it is money, though the two go together.
In conversations with foundations it has struck me that many have described their investment in data internally as focused on improving their ‘operational data’. Most larger foundations have impact or insight leads. Some have data specialists. But mostly it seems they are focused on supporting operations. Few, if any, appear to have people who are focused on data strategy or shaping data policy. And this may be impacting how they attempt to support the data eco-system.
A look at the projects that have been funded over the previous 5 years, the vast majority of funding has been directed at ‘operational’ data with the sector. Very little has been directed at strategic data initiatives or data policy. There are notable exceptions to this, with 360 Giving, DataKind UK, Open Data Institute and the DataCollective all being examples of more strategic investments in data, but these investments are rare and small in comparison to the rest of the sector.
The reason I think this is important
- I wonder if we focus only on ‘operational’ data, then do we miss broader opportunities for change?
- Do we leave this space open for others, **such as the ‘for profit’ sector,** who may shape the data eco-system from a skewed view?
- Do we miss the opportunity to focus attention from across the sector on data, and the potential good or harm that can be created?
Questions I’m left with
- How much funding is directed to Data Infrastructure?
- Are we even clear about how we collectively define Data Infrastructure within the sector?
- How much funding is directed at the ‘long tail’ of products rather than at Data Infrastructure or Platform approaches?
Where the data came from and how I processed it
So here is how i went about it:
- Using grant data available via 360 Giving (data infrastructure)
- Key word search of ‘data’
- Filtered to 2016–2021
- Filtered to funding by ‘Grant Making Organisations’
I purposely excluded grants from central government in this search
This gave me 2071 records which needed some work to get a dataset I felt would at least help answer my question.
Firstly the key word search via Grantnav is great, but it returns all records with ‘data’ somewhere in the available fields. This means it will return this record to me if ‘data’ shows up in any of the following
- Recipient organisation
- Funding organisation
- Funding programme
The field that causes most problems here (unsurprisingly) is the free text box ‘Description’ as this comes (in most cases) directly from a charities application. This meant a huge number of records with some relation to organisations wanting support with purchasing ‘mobile data’ either for participants or for staff. Whilst this is interesting (especially to anyone who might be looking at data poverty) it wasn’t helping to answer my question. So I spent some time cleaning this data using key terms including
- mobile data
- 3g, 4g
Once cleaned I now had 1083 records.
Next up I removed all funding from Wellcome Trust. Nothing against Wellcome Trust, they are a fantastic funder, however the sheer size of their funding and who they fund completely skewed any analysis. What I mean by this is that
- One of their grants per year may be more than the rest of the funders combined
- 99% of the funds went to universities
- Most of the funding was directed to medical research
So Wellcome Trust Grants were removed. I now had 458 records.
In some of the analysis I also removed all grants which had Universities as the only grant recipient which removed a further 51 records.
I did a similar process for the ‘Digital’ grants data
You can find the data below