Finally, what are the roles of data in digital civil society? When something is digitized, it is translated into binary code – literally, strings of ones and zeros. It doesn’t matter what the original was made out of – music, text, images, human tissue, or even solid steel; in digital form, everything becomes ones and zeros.
This is why everything digital is so interchangeable. Think of all of those ones and zeros as data, and recognize those (interchangeable) data as the core resource of the digital age. When I talk about data, I mean not only numerical data on grants but also images, stories, movies, music, almost anything that can be digitized. The nature of data is already changing the norms of transparency, ownership, and governance – these are first generation changes. Second generation innovation comes in the form of enterprises and interventions designed from a starting point that assumes readily available, digital data as a core resource.
That said, let’s start with the data most familiar to the social economy – actual numerical data on the enterprises and resources within it. While there are major efforts underway to collect better information about nonprofits and foundations and the revenue that supports them (as shown in Blueprint 2013), we still have a long way to go before this information becomes a valuable resource of and for the work of the social economy. We do see some glimmers of what’s possible. Progress can be seen in a few instances: shared maps of commonly-coded grants data are being used by funders interested in black male achievement; philanthropic education funders use a shared platform to stay abreast of innovative U.S. Department of Education proposals in need of matching funds; and many of the largest foundations in the U.S. have agreed to share a coding taxonomy and report their data in an open, machine-readable, and standardized form.
A few other examples offer evidence that the ability to gather, store, and share digital information can change the fundamental practice of social economy actors. The rise of impact investing in the last five years has depended on the development of shared metrics for social and environmental return. Secure, accessible digital databases and the software to analyze and compare the data they store finally became affordable, making the expensive human side of collaboration and coordination worth the effort. The process of developing these measures has been both coordinated and entrepreneurial. It includes deliberate collaborations such as the creation of IRIS, GIIRS, and PULSE – digital measures, reports, and a reporting platform, respectively. It also includes efforts such as ImpactBASE, a database of investors and investments, and MissionMarkets, a database for private equity placements in mission-driven businesses. Don’t misunderstand me; data did not create impact investing. But the movement would not have grown with the momentum it has if digital solutions hadn’t been available to meet the demand for both common language and metrics. Shared, comparable data are a prerequisite for the impact investing movement. Their use here demonstrates how data can catalyze new enterprises, behaviors, and investments.
We’ve seen less of these behavior changes than I thought we’d see. The human and organizational resistance to new practices and behaviors is significant, and the pressures to change philanthropic behavior are weak. That said, we do see glimpses of new practice. The newly launched Feedback Labs, a joint venture of several organizations focused on global development, recognizes that direct input (data) from beneficiaries is readily available and should be used for program and organizational improvement. Similarly, the last year saw an unprecedented partnership between a nonprofit charity review organization, GiveWell, and a philanthropic funder, GoodVentures. This might be the first such partnership where datadriven analysis is being used as the basis for both individual and shared philanthropic funding decisions, and where all of the data and analysis being used by the partners is being shared publicly. In a slightly different vein, the DetroitLedger is a – volunteer-led effort to open funding information on all grant funding to Detroit, America’s largest city ever to declare bankruptcy. It demonstrates digital expectations about transparency that have roots in the United Kingdom’s project, TheyWorkForYou.
The role of data in the social economy raises several new issues, especially if we circle back to fundamental questions of privacy and of ownership and governance. Not all enterprises in the social economy are governed by the same data practices or expectations. The first place this distinction has reared its head is with regard to the disclosure of data about donors to social welfare organizations and charitable nonprofits in the United States. The culture of data disclosure regarding political donations is quite strong in the U.S. Most of the campaign finance system revolves around making information on campaign funders readily available to the public. On the other hand, people making charitable donations to nonprofit organizations do not need to be identified; anonymity is a treasured norm within American philanthropy. As some nonprofit oranizations (social welfare organizations) have become increasingly politically active, these two contrasting norms – disclosure and anonymity – have come into direct conflict.
Similarly, there are no common practices guiding the sharing of data funded by, used by, and resulting from grants given by philanthropic organizations. Every funder has individual requirements. This can easily put a nonprofit with two funders in the impossible position of presenting the same information under two different standards. Many organizations rely on revenue earned from data in either raw or analyzed form and, though they may see a benefit to sharing the data freely, they also need to keep the lights on.
Takeaways are critical, bite-sized resources either excerpted from our guides or written by GrantCraft using the guide's research data or themes post-publication. Attribution is given if the takeaway is a quotation.
This takeaway was derived from Philanthropy and the Social Economy: Blueprint 2014.