Field Notes: Selling Social Impact Data

Rick Jacobus of CoMetrics reports his findings on the problem of who should pay for social impact data.

While measuring social impact is obviously important for the grantmakers, investors and enterprises who seeking to maximize positive impact, few funders seem willing to pay for this data as a customer. Rick Jacobus of CoMetrics, a Heron investee, launched an investigation into the different business models addressing the impact data issue and the difficulties they face in securing a client base given the discrepancy between the data needs of social enterprises and their funders.

Overwhelmingly, my interviews pointed to a single problem holding back development of the whole sector in numerous ways.  Stated simply, the problem is a fundamental misunderstanding of what value social impact data can provide and who is most likely to benefit from (and ultimately pay for) that value.

The four main conclusions Jacobus draws are that:

  • Funders are the wrong customers: Nonprofit leaders constantly hear from their funders about the importance of measuring impact and collecting better data. So it would be reasonable to assume that philanthropic funders or individual donors would be the natural ‘customers’ for better social impact data. In fact, most of the social sector data projects described below appear to have been built around this idea; that funders are the ultimate customers for social impact data.
  • Grantees are the right customers: If funders are not the ‘customer,’ who is? Who actually cares about the difference between different outcomes? Several of the examples below suggest that the programs themselves may be better customers for social impact data. While the same data may be equally interesting and even relevant to both funders and the organizations that they fund, the data may simply solve bigger problems for the funded organizations.
  • Collaboration can lower costs: While there is a nearly infinite variety of potential models, there has been a recent trend toward ‘collaborative’ models which attempt to take advantage of economies of scale. They do so by addressing the needs of multiple organizations simultaneously. In some cases, individual social enterprises band together to directly collaborate on shared data projects. In others, a ‘data intermediary’ of one type or another brings similar enterprises together in a project that meets all of their needs.
  • Purpose won't trickle up: For any data driven strategy for social change, purpose has to start at the top and flow down along with the funding – or flow both ways. Once a funder says what they want to change and what evidence they expect to see as a result of that change, then grantees can compete to produce that evidence. We can’t build a social sector that values data in some way that is completely independent of the way we fund the sector. Moving the sector to a more data driven approach necessarily means moving to more data driven funding decisions.

Jacobus also notes five ways people can find value in this kind of social impact data: science, investment decision making, differentiation, program design, and program implementation. He stresses the immense challenges in using these sources to meet the needs of today’s interested parties.

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This post was prepared by Katherine Blum.

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