Measuring Success | Can Innovators be Data-Driven?: Response to “Could the Incessant Demand for Data Kill Innovation in the Nonprofit Sector?
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Can Innovators be Data-Driven?: Response to “Could the Incessant Demand for Data Kill Innovation in the Nonprofit Sector?

18 Nov Can Innovators be Data-Driven?: Response to “Could the Incessant Demand for Data Kill Innovation in the Nonprofit Sector?

How can data and innovation, with its inherent risk, coexist? In his recent blog post, “Could the Incessant Demand for Data Kill Innovation in the Nonprofit Sector?” nonprofit communications professional and USC Professor Gary Wexler argues that maybe they shouldn’t. Data “may be killing some very good ideas that are badly needed in this changing world,” argues Wexler. But, does a non-profit that wants to be both data-driven and innovative, have to choose one or the other? Must we throw out the data baby with the innovation bathwater? Of course not.

Nonprofits and funders, evaluators and workers in the field, must approach data, like anything else, with nuance. They must know when data is useful or superfluous or, at times, limiting. This takes practice, wisdom, and courage.

Let us remind ourselves, data is simply information. Data helps us mitigate uncertainty, the most prevalent and weighing aspect on any future-driven endeavor. Somehow, the business world manages to be both data-driven and innovative; there is no reason a non-profit can’t strike a similar balance. No business leader is under the illusion that data is entirely prescriptive, the perfect roadmap for making decisions. Data is a record or a tool that helps us under- stand the potential risks we face and prepare for them better; it does not remove the unpredictable nature of most activities. Thus, innovation in the non-profit sector must employ, as Wexler puts it, “intelligent risk,” which harnesses data to better understand potential outcomes.

Nonprofits, more than ever before, should ride this wave of interest in data, which has migrated from the private sec- tor, to improve their internal processes and streamline efficiencies, as well as forecast opportunities for growth. Like for-profit organizations, though, they should use data to aid their decision-making, not become a substitute for it. Innovation will always be risky and we can best fortify ourselves against that risk by acquiring as much as knowledge and insight as we can in advance.

Is it too extreme for a funder to demand data before giving money? It depends. Does the recipient organization have the funding to collect data? Is the data really necessary for the decision at hand? Should the funder give money for the explicit purpose of collecting data? In many cases, the last question is what we’re seeing most…nonprofits need capacity building support to grow their evidence-based initiatives. This will help nonprofits know when it is the right time to take their ideas in new and exciting directions.

Fortunately, many funders who value data most are putting their money where their mouth is (e.g. Gates, Knight, Hewlett, and many others) and supporting capacity building with their grantees. Of course, the key here is to under- stand, with nuance, the limitations of data in the non-profit space. As Wexler notes, nonprofits are “rooted in the soul of a community,” not sales.

One of the best rhetoricians about the value of data for nonprofits is Mario Morino, chairman of Venture Philanthro- py Partners (VPP), a strident “outcomes-based” philanthropic investment organization. Though data-driven, Morino realized that measurement was not a catch-all. He wrote in the Stanford Social Innovation Review in 2010 that VPP “should have done more to understand ‘soft’ achievements that may in fact be every bit as real and important as ‘harder’ outcomes.”

It is these “soft” achievements, though denigrated by their very connotation as soft, that are at the heart of so much of the valuable service non-profits perform. To radically transform lives, we can’t just measure numbers, we must remember the “souls” with which we engage. While there is much good that data helps us accomplish, it is not the be all end all, it is a mechanism that allows for our very human interactions to have that much more effectiveness.