Note: As I mentioned earlier, I am taking a few weeks away from the blog to relax and reconnect with the world outside of social change. But I am leaving you in the incredibly capable hands of a rockstar set of guest bloggers. First up is David Henderson, Director of Analytics for Family Independence Initiative, a national nonprofit which leverages the power of information to illuminate and accelerate the initiative low-income families take to improve their lives. David also writes his own blog, Full Contact Philanthropy, which is amazing. Here is his guest post…
In early June I was invited to be on a data mining panel at the Stanford Social Innovation Review Data on Purpose conference. The conference was full of nonprofit executives interested in tapping the big data revolution for social good. Naturally, the panel moderator asked us panelist to weigh in on if, and how, data was changing the social sector. Characteristically, I turned a feel-good question into a critique of the state of analytics in the social sector, which I’ve written about elsewhere and will expand on here.
Data is not changing the social sector. I would argue it’s not changing the world either. While it is very likely that data is changing your world, I do not believe data is changing the world.
For all the talk about how data is revolutionizing the world and that software is eating everyone’s lunch, the fact is that for the over two billion people who have no lunch to eat (literally and figuratively), the impact of the data revolution is muted, if nonexistent all together. Changing the world indeed.
The corporate data revolution has largely been fueled by data exhaust. Data exhaust is comprised of the various digital breadcrumbs you and I leave all over the Internet but that we might not think about as data in a traditional sense. For example, companies like Facebook and Amazon don’t simply log data when you click “submit”, they track your every movement around the Internet, logging every click and clack, allowing unprecedented marketing optimization. All these additional metrics are data exhaust, as consumers are almost passively generating data marketers can capture and monetize for almost nothing.
On the social sector data conference circuit, countless data-wonk hopefuls mindlessly espouse all the incredible things nonprofits can do now that data acquisition costs have been driven almost to zero. This is nonsense, as the social sector has no such data exhaust analogue, which is why the social sector doesn’t truly have big data.
Nonprofits often work with populations with a number of barriers, which drives up the cost of data acquisition relative to for-profit counterparts. Just some of the data collection barriers nonprofits grapple with include working with populations with low levels of literacy or limited to no access to technology. How exactly is one going to generate digital exhaust without any digital possessions in the first place, or while working three jobs to support her family?
Obviously, you don’t. The barriers too many people face in this world are exactly why nonprofits are in the business of social change in the first place. But it is also why we are so poorly poised to capitalize on the alleged data ubiquity, as that revolution is not permeating class boundaries to the extent technology evangelists would have us believe.
Another reason why data is not changing the world, or rather, why the social sector is failing to change the world with data, is that by and large we simply are not investing in the necessary capacity to turn data into insights.
While a new “data for the social sector” company with an unfortunate misspelling of a common word seems to pop up every day, there are very few companies actually building the tools the sector needs to put data in to action. Meanwhile, our technological overlords in Silicon Valley are depressingly stuck on the assumption that innovation in the social sector means fundraising software. Sigh.
If we want to use data to change the world, we need to think beyond software tools and simple (if colorful) data visualizations. Nonprofits need to invest in building their own analytical capacity, both by hiring analysts and also by investing in the entire staff’s ability to be intelligent consumers of data analysis.
Illusion of Insight
Everyone loves the idea of being data driven, but very few organizations actually want to make the investment. My employer, the Family Independence Initiative (FII), did make that investment. In turn, FII is now able to not only run regressions and build decision tree models, but can continuously learn from its data, augmenting every level of the organization from Chief Executive to line staff.
That investment is not cheap. Worse yet, like any good analyst, I can be a major buzz-kill. Much of my time is spent explaining why a particular regression coefficient doesn’t necessarily mean we are super awesome. In fact, a good analyst can make you less sure of your social impact.
But facing the tough reality paves the way to real impact. We cannot collectively do more without exactingly quantifying how little we’ve accomplished. These are tough truths, and most nonprofits would rather assume the hypothesis of their greatness, leaving no room for data’s insights.
The Path Forward
Just because data is not changing the world does not mean data cannot change the world. I believe it can, which is why I do what I do. While by and large nonprofits fail to invest in rigorous analysis, organizations like GiveDirectly are leading by example, showing what is possible when fact is paramount to fundraising.
Ultimately, being data driven is less about statistical techniques and more about a relentless commitment to the truth. The truth is that data is not changing the world. But if we, as a sector, can elevate the truth above all else, then we might just be able to change the world after all.