Measuring the social impact of blogging

Professionally I do two things; I help organizations make high impact data-oriented decisions, and I write. As 2011 draws to a close, I reflect on another year helping a lot of great organizations increase their social impact, and a pile of blog posts that I hope help advance the social sector toward lasting change.

Obviously I believe writing, and the exchange of ideas that comes with it, is important to the growth of our sector and advancement of solutions. If I didn’t believe that, I wouldn’t write anything. But as someone who prefers evidence to anecdotes, facts to feelings, I’m at a loss for much evidence that blogging (at least my blogging) helps move the needle even a little bit.

I feel like I get quite a bit more than I give in terms of writing. And maybe that is okay, so long as I believe writing helps me get better at what I do, and that what I do with my agency has social value.

But my ambition for writing and the promise of free-flows of information in the social sector exceed simply personal gratification and advancement. My hope is that by sharing with one another what works and what doesn’t, that we would improve our own services, turning those little insights into collective action.

While articles about changes in the poverty rate and misleading homeless counts are compelling reads for people like us, if that information exchange doesn’t improve the output of our efforts, then what are we doing? There are certainly times when I worry that the articles we write and share with one another have no value other than to amuse ourselves, like a gossip rag for poverty-geeks.

I hope I am wrong, and in 2012 I plan to actively seek evidence to the contrary. I want to believe that we are evolving into a sector that thrives on sharing best practices and possesses the sophistication to integrate information across the fields of politics, sociology, finance, social work, community development, and a slew of other focus areas that collectively sum to the vastness of the social sector.

Indeed, it is in the vastness of the social sector that I worry the value of our information exchange is lost. As you know, the social sector is complex. Its complexity in part stems from the fact that it is not so much a sector, but rather a sector of sectors (some call it the un-sector). The sector-of-sectors nature I fear lends itself to sharing information in parallel, rather than exchanging information that directly impacts what we do.

I, like you, picked this line of work to improve the lives of hurting people. When we read posts, share information, and write on our blogs, we are diverting our time away from our work. I hope, I think, this is a good use of our time. I think writing matters, and I hope in 2012 I can prove it to myself.

Why predictions are so difficult to make in the social sector

As 2011 comes to an end and we look forward to 2012, pieces predicting what will happen in the coming year are popular in every industry, including the social sector. While making predictions is no easy task, not even for psychics, making predictions in the social sector is especially difficult.

Most industries tend to have clear industry leaders. These organizations, like Apple, Chevron, and Wallmart are significantly large that they can in many ways move industries on account of their sheer size. In the social sector we have no clear market makers, with the exception of governments. But governments are inherently unpredictable. Democracies are subject to deadlock, compromise, and regular leadership change. Dictatorships, while marked by leadership consistency, lend themselves to rulers with unpredictable and often erratic behavior and management decisions.

Of course, a common metric used for industry predictions is consumer demand. While a company like Amazon can use its vast consumer behavior database and market research to predict the directional winds of what consumers want, addressing needs is a significantly different undertaking. The demand we address tends to be either immediate (homelessness, hunger) or arguably intractable (systematic poverty).

Aggregate social indicators like poverty and unemployment rates are the most popular indicators used for predicting future demand. Yet the reliability of these predictors is questionable considering the regularity of reports about how organizations are blindsided by demand for their services. Indeed, these social predictors are highly imperfect, especially considering our inability to agree on a definition of poverty in the United States and the persistently misleading reports of homeless counts.

While big-data is being put to lucrative use in some sectors, especially technology, the most accurate predictions are based on the aggregation of front-line organizations’ own data. Big-data is itself by definition aggregations of micro-consumer behavior and transactions. The difficulty we face in applying these same tactics in the social sector however is that in order to aggregate meaningful large-scale data-sets, we must first collect and analyze meaningful micro-sets.

To this end, my company is working with organizations helping them setup data collection pipelines and analytic processes so they can better make predictions of both demand and impact. Making increasingly more accurate organizational level predictions is a necessary first step to reliable industry wide predictions.

Despite all the blog posts, books, and questionable models to the contrary, we are a long ways away from being able to predict with any relevance the future of the social sector. Therefore, the only prediction I will make for 2012 is that the future is unclear.

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.