16 Apr. 2014 | Comments (0)
In his recent post, “Could the Incessant Demand for Data Kill Innovation in the Nonprofit Sector?”, Gary Wexler argues that data can’t deliver a comprehensive assessment of the nonprofit sector, because there are fine details and hidden components that simply can’t—and shouldn’t—be measured. He says that pressuring nonprofits to provide information on all facets of their work can constrain the generation of ideas and experimentation in the social sector. We think his argument is flawed.
The nonprofit sector is rife with inefficiency and irrelevance, a situation that generated the desire for empirical scrutiny in the first place. To revert to a state in which funders and nonprofits interact solely through open-ended conversations and inconclusive dialogue is a significant step backwards. The rest of the business world is moving irrepressibly toward a world of big data. It is true that applying data analytics to the nonprofit world is complex, since social impact results from multiple concurring factors, but technology and analytical models are evolving and becoming more and more accessible—surely the nonprofit sector needs to exist in the same world or face the prospect of irrelevance.
Funding data demands
Gary says that foundations demanding data and evidence of impact “must be ready to fund the data actions required for new ideas over the period it takes to create the proof they want—which may be years.” We disagree. Foundations should set the bar and raise expectations for the nonprofit sector. Then competition in the sector will ultimately drive the process to improve measurement. The pressures of responding to the data and evidence demands of their funders will no doubt result in casualties, but so be it: some cleansing is needed, and the nonprofit world as a whole will benefit from clearer parameters of competition. This is not to say that the conversations Gary calls for are unnecessary. Of course funders and their recipients should collaborate. But that does not mean that nonprofits should retreat from the business language that the rest of the world is speaking: the language of data.