Data is not information

For all the buzz about how data is supposed to change the social sector, there is scant evidence that revolution is truly underway. Certainly there are high-profit efforts to catalogue and aggregate data as social sector organizations are savvy to the importance of documenting their work and outcomes in databases. But moving data from our heads to paper to the cloud does not necessarily create value, much less social change.

A recent article in GOOD asks “is solving nonprofits’ challenges as easy as creating maps?”. One of my company’s areas of focus is mapping social services in communities, helping service seekers connect to programs and helping organizations better understand their geographies. Therefore, as someone who knows a thing or two about mapping in the non-profit sector, I thought I would take a crack at answering this question.


Databases and maps store data. But data is not information. Data becomes information when used to inform decision making. Numbers, regressions, and longitudes and latitudes do not impute meaning. How we use, contextualize, and interpret data determines informational value, not the size of a database nor the contours on a map.

Despite this rather obvious point, our efforts and interests are stuck on this most primitive definition of data. Government and non-profit organizations spend considerable money on database systems to store and collect data without clear strategies for how they will use it. In this way, the social sector suffers the dual cost of both the cash outlay spent on aimless data collection, and the more insidious invisible opportunity cost of what might have been had these organizations successfully converted their data to information.

Indeed, the CTO of Infochimps, a company at the forefront of the big data revolution, smartly argues that storing data is not only a significant pain, but of no real value. Instead what matters is insight.

Data on its own provides no insight, not even big data. Before an organization thinks about collecting data, I first ask what decisions they are trying to inform. The questions an organization is trying to answer drives sound data collection efforts, as these questions provide the necessary context to inform future decision making.

The social sector would do well to focus less on buzz words like open-data, big data, mapping, info-graphics, and any other form of trivial data distractions that masks the real problems our sector exists to address every day.

The data revolution can, and should, be a boon for our sector and those we serve. Databases are cheap and public datasets are copious. Free tools like Google Earth and R afford anyone with the necessary patience to develop real analytic competence the opportunity to do so, and better the lives of those in need. And while there are efforts like Ushahidi that underscore the power of marrying technical know-how with social problems, too much of our public discourse is dominated by proponents of the most trivial data artifacts.

Hurting people could care less about slick info-graphics or mapping their descent¬†into homelessness in “real-time”. Our job is to solve social problems. If our data doesn’t help us help people better, it’s not information, it’s just noise.