‘You need a few data, otherwise you don’t exist,’ said Benoit Fontaine of the King Baudouin Foundation, speaking at a High Tea meeting co-hosted by the EFC and Alliance in Brussels on 19 November. The purpose of the event was to discuss some issues arising out of the special feature of the September issue of Alliance – ‘What can data do for philanthropy?’ Has private philanthropy – foundations, individual philanthropists and impact investors – been slow to jump on the data bandwagon? How could better data help philanthropy?
How much data foundations need was a live topic. According to Fontaine, ‘nowadays there is an addiction to figures in some sectors, which then creates bureaucracy.’ In his view, we need a few data that we can compare over the years: ‘You don’t want to look at a photo; you want to watch the film.’
Paul van Haver of TechSoup Global, perhaps not surprisingly, was in favour of more data. In his view, there is a great deal of data out there, and a great opportunity to connect and index relevant data worldwide: ‘Our biggest challenge is the global distribution and un-connectiveness of all our data.’ BIG data is possible and it can deliver value, he said. ‘If the corporate sector raves about it, why should it not be good for us?’
Encouragingly, he didn’t seem to think sharing existing documents such as due diligence reports and evaluations should involve a great deal of extra work. The technology exists to index ‘unstructured documents’, he said.
Data for market intelligence
Why do we need all this data? Larry McGill, one of the guest editors for the Alliance special feature, suggests in his overview article several ways in which better data could help foundations. For individual foundations, he says, the main use is for ‘market intelligence’, ie understanding potential constituencies, unmet needs among those constituencies, mechanisms for meeting those needs, and the work of other organizations operating in that market. ‘Having access to data in each of these areas minimizes the risk of making poor investment decisions,’ he says. But are foundations collecting and using data for this purpose? And would it improve their work if they did?
The EFC’s Marilena Vrana described a mapping exercise carried out by the EFC’s European Environmental Funders Group. The aim was to establish as detailed a picture as possible of European independent funding for environmental issues. The study highlighted anomalies and gaps in funding. Out of 791 environmental grants made by 27 foundations to 599 organizations, amounting to €181.5 million in all, more than a third were directed to initiatives under the two categories ‘Terrestrial Ecosystems & Land Use’ and ‘Biodiversity & Species Preservation’ while ‘Climate & Atmosphere’, ‘Energy’ and ‘Transportation’ together accounted for only 20.4% of all grants made. ‘European foundations appear to have little appetite for grappling with “systemic” environmental issues,’ was Vrana’s conclusion.
While more than 80% of European environmental legislation is developed at European Union level, only just over 4% of grants were explicitly directed towards advancing European policies. Only 0.5% were dedicated to work in China – despite ‘the impact that China and other rapidly economies are having in the global environment’. Finally, the research shows that European philanthropic resources are heavily concentrated in countries such as the Netherlands and the UK, which already perform well on environmental indicators and have no shortage of environmental groups.
It’s one thing to reveal mismatches and funding anomalies, another to remedy them. How did the mapping help funders? According to Vrana, it is too soon to tell, but the research seems to have provoked interesting debates around funding priorities and the effectiveness of grantmaking and more funders have expressed interest in participating in the next study, to be launched before the end of 2012.
Data for monitoring and learning
Larry McGill’s second suggested use of data by foundations is for monitoring and learning. Funders must collect data on how well their own interventions actually worked and share it with others. There must be collective learning as well as individual learning. Is this happening? Before thinking about sharing data with others, said Fontaine, foundations first need to capture the data inside their own organization – an area where ‘there is certainly some room for improvement’. Several speakers made the point that sharing and learning is more likely to happen within communities/networks than through a mega database in the sky.
Data for advocacy
The third use of data McGill suggests is for supporting advocacy on behalf of the foundation sector. Do associations have the information they need to do this? Richard Jenkins of the UK’s Association of Charitable Foundations had mixed feelings. On the one hand, even within the UK it is hard to give an accurate figure for UK foundations, especially given that their legal form is the same as for NGOs. This issue is magnified across Europe. So, for those who want to promote the role of foundations in civil society, the more information we have the better, like the recent survey that showed that 80% of UK foundations had maintained levels of giving since 2008, and 5% had increased their spend. On the other hand, going back to his experience ‘on the other side’ as a government policy adviser, what decision makers really want is ‘one killer fact and one killer story’ rather than pages of information.
Data for transparency
Transparency came up a lot. Transparency should be seen as a preventive concept, said Fontaine, to uphold the reputation of NGOs and foundations: ‘we don’t have clients or electors to give us legitimacy.’ But it was generally agreed that NGOs might have more incentive to be transparent than foundations. Foundations could, for example, decide to give grants only to NGOs meeting certain transparency standards. But what are the drivers among foundations? One possible one is the need to be more transparent and more able to demonstrate impact if foundations are to continue to enjoy the tax benefits they now receive in many countries.
A magic bullet?
Do we expect too much from data? It’s easy to think of better data as a magic bullet. What are its limitations? One point made by several speakers was that one should always be cautious in the interpretation of data. Figures can give you a false impression of the truth, said Fontaine. ‘You always need a story behind the data.’ Another issue for Europe is language: sharing data among countries with different languages. You can develop classification systems that begin to overcome this, said van Haver, but he admitted it was hard.
Caroline Hartnell is editor of Alliance magazine