Data as a catalyst for philanthropy

We live in challenging times. From climate change to wars and economic inequality, the difficulties confronting decision makers are unprecedented in their variety and also in their complexity and urgency. Our standard toolkit for solving problems seems stale and ineffective; existing institutions are increasingly outdated and distrusted. Increasingly, it is clear that we need not only new solutions but also new ways of arriving at solutions.

These are cross-sectoral challenges affecting government, corporations, academia, and civil society. The field of philanthropy is certainly not immune. Modern philanthropy faces a range of distinctively 21st-century difficulties. There is a profound need to reimagine how philanthropic decisions are made and how investments and programmes are designed and delivered. In particular, much as organisations in other sectors have leveraged new technologies to enhance their roles and better achieve their missions, so too must philanthropic organisations consider how to become more innovative, responsive, and effective in the digital era. 

Let’s begin with the premise that one of the most important routes to 21st-century philanthropy runs through data. The increased use of data, advanced analytics, and artificial intelligence – all part of the datafication of our world—offers tremendous potential benefits for philanthropy as well as for society at large.  Yet data poses its own challenges and risks, of course; the datafication of our era is not an unqualified good. And this, in fact, is where philanthropies may play their most crucial role: in helping to ensure that the positive potential of data is unleashed while limiting its possible negative consequences. At a time of increasing public anxiety about our data-driven economy, philanthropies must rise to the challenge and help determine the contours of the emergent data ecology, ensuring the public good–including a vibrant democracy – while at the same time spurring innovation and economic development.

In what follows, we offer five thoughts on how to advance Data Driven Philanthropy. These are operational strategies, specific steps that philanthropic organisations can take in order to harness the potential of data for the public good. At its broadest level, then, this article is about data stewardship in the 21st century. We seek to define how philanthropic organisations can be responsible custodians of data assets, both theirs and those of society at large. Fulfilling this role of data stewardship is a critical mission for the philanthropic sector and one of the most important roles it can play in helping to ensure that our ongoing process of digital transformation is more fair, inclusive, and aligned with the broader public interest. 

Five Steps Toward Data-Driven Philanthropy:

Philanthropic organisations are involved with data in many ways. They are holders of data, often collectors of data (including personally identifiable information, or PII), and they also interact with a range of other data holding and collecting organisations. Each of these areas offers opportunities–and challenges–to fulfil their role as data stewards for the public good.

OPTIMISING DATA HELD BY PHILANTHROPIES:  Philanthropies themselves collect and store a vast range of digital information, including grant management records, impact evaluations, archival materials, and much more.  This information offers tremendous potential, not least to optimise the decisions that philanthropic organisations themselves make about funding, hiring, and other matters. Yet, as a sector, philanthropy has yet to fully leverage these assets. Too often, data is not standardised in a manner that can be shared or analysed, and the sector is marked by a more general failure to develop a method of analysis of a set of questions that could systematise how data is collected, stored, or used. As a result, the potential of philanthropic data is stunted, limiting the impact of philanthropic organisations themselves and also the benefits for society at large. The path to a more data-enlightened philanthropy therefore begins at home – within philanthropic organisations themselves and the way they handle data.

ENABLING CROSS-SECTOR PARTNERSHIPS: Philanthropies also play a valuable role in initiating and enabling data partnerships with external stakeholders, including both private and public sector organisations. Philanthropy has a particularly important role in facilitating data collaboratives – partnerships between data holders and users – to optimise the public-interest impact of data generated by corporate actors. In order to maximise this impact, philanthropy can act as a convenor or catalyst to facilitate three critical assets: 1) domain knowledge of a problem space amenable to data fixes; 2) access to private-sector data that can help solve problems; 3) data science and artificial intelligence capabilities relevant to problem solving. Philanthropies are uniquely positioned both because of the range of areas where they directly perform funding (including basic and applied science, machine learning and AI), and because of their vital role as convenors, or a bridge, across sectors.  Thus far, philanthropies have not maximised their cross-sectoral potential in the data ecology; greater action in this area is essential to help fulfil the public good potential of data within and external to the sector.

IMPROVING DECISIONS AND GRANTMAKING: In addition to the above two steps, philanthropic organisations can also use data to create cross-organisational maps and decision-making tools or processes. Among other goals, these tools can be used to:

• Improve the grantmaking cycle and overall operations – for instance, by combining digital transformation tools and data analytics to introduce new efficiencies and greater effectiveness across the grantmaking cycle. One example would be the creation of knowledge graphs on who is doing what, with which beneficiaries, in which intervention areas, in order to prevent duplication, and identify gaps or areas of potential collaboration. Similarly, data can be used to streamline processes for grants management, evaluation of proposals, and more.
• Transform philanthropic governance, in the process making philanthropic organisations more accountable and transparent.
• Increase impact, for example by allowing grantmaking organisations to make more evidence-based decisions and continuously adjust their activities to take account of realities on the ground.

While philanthropy is making progress in leveraging data toward all these objectives, systematic transformation remains elusive, especially for smaller organisations, who may lack the financial or technical wherewithal. The GovLab and Paul Ramsay Foundation’s new initiative, DATA4Philanthropy.net, aims to address these issues by establishing a community of practice around data to inform the grantmaking cycle of philanthropies. The platform includes several data-driven methods, tools, and case studies that can be used across the entire grantmaking process including primers on Participatory Sourcing of Questions, Digital Ethnography, and Living Evidence and Visualisation amongst others. By doing this, the platform aims to support philanthropies – large and small – in forming new connections with philanthropic and data innovators, experimenting with new data initiatives, and aligning on shared priorities across the sector.

DATA SCIENCE AS A FUNDING PRIORITY: As the transformative potential – both positive and negative – of data has become increasingly evident, data science (including machine learning and artificial intelligence) has emerged as a crucial field of activity across domains. Given the steady datafication of society, philanthropies should prioritise funding and investments that advance knowledge sharing and methods for extracting public value from data. Some examples of funding areas include:

• Computational science, especially as it relates to making all domains of society and policymaking more data-driven through new methodologies and new data infrastructures
• Deeper integration of data in public policymaking, for example in processes to improve urban housing, better cope with global warming, or respond to pandemics
• Encouraging data activism, for instance so that social activists are better able to leverage data in addressing social injustices or advocating for change

DATA AND AI AS A POLICY AND REGULATORY PRIORITY: Moving forward, the ways in which data and artificial intelligence is governed will have profound implications for the future of democracy, innovation, and economic inequality. Yet the current debate over data and AI governance is dominated by special interests and actors who do not necessarily represent the public good. Philanthropies can play a key role in fostering a more inclusive and responsive debate and in ensuring that key public good values are embedded in the policies, standards, and regulations that will define the digital landscape. For example, philanthropies can help fund organisations or individuals involved in data or digital governance, and it can similarly help convene cross-sectoral interactions and organisations that may bring together various stakeholders to create a richer, more inclusive conversation.

Conclusion: Envisioning Data-Driven Philanthropy

The integration of data in philanthropy is not just a passing trend or a side issue. It is increasingly core to the very practice of philanthropy and to addressing the multifaceted challenges of our time. By effectively harnessing data, philanthropies can become more innovative, legitimate, and effective. The journey toward Data-Driven Philanthropy is complex, and requires a collective commitment to innovation balanced with responsibility and a commitment to existing stakeholder values. As philanthropic organisations navigate this transition, they have the opportunity to redefine their impact and role in a rapidly evolving digital landscape–and, in the process, to fulfil their core responsibility of helping to build a better, more inclusive and more fair society.

Find out more on data-driven philanthropy with Philea and Fondazione Compagnia di San Paolo’s new publication “Data Science, AI and Data Philanthropy in Foundations: On the Path to Maturity”