Last weekend's This American Life included a great Planet Money segment about GiveDirectly, a charity that gives poor Kenyans not food or equipment or livestock or training but cash. The idea is that, whatever risks or downsides exist in just giving people money, these are outweighed by a) extremely low overhead, and b) the fact that the poor actually know best what they need.
GiveDirectly is big on data, and they're currently having independent researchers run a randomized control trial to evaluate their own effectiveness. Founder (and economist) Paul Niehaus said this:
We would like to see organizations make the case that they think they can do more good for the poor with a dollar than the poor could do for themselves. . . And I think some may be able to make a convincing case, but if you go to their websites today, I don't think you're going to see that argument being made. Nobody even bothers.
The Planet Money reporters took this challenge to Elizabeth Bintliff, who runs Heifer International's Africa programs. They suggested a side-by-side test; she responded by downplaying the importance of data:
We’re not about experiments. These are lives of real people. We have to do what we believe is correct... It’s just not that linear. It’s not an equation.
Then she told a story about a specific woman Heifer has helped.
Bintliff comes off as slightly cagey, and Planet Money's main takeaway here is about data: GiveDirectly represents a shift toward data-driven program in the charitable world, and more traditional players are suspicious of this. But I spent the whole segment thinking about a related issue the show tiptoes up to but doesn't really unpack: the fact that it's a lot easier to fundraise for specific purchases than it is to get people to basically sign their checks over to strangers in Kenya.
When Bintliff plays down data and plays up story, it doesn't sound like she's thinking about the program work she oversees. It sounds like she's thinking about raising moneyfor it. Which is to say: the question for GiveDirectly is not just whether they can do more with a dollar but whether they can get as many of them to do anything with in the first place. However precisely effective Heifer's cows and flocks of chickens are, they make for awfully good promotional materials.
As any pastor who's run both a food drive and a missional campaign knows, people like to give things. We also like our donations to have a story—and GiveDirectly's model doesn't necessarily preclude telling success stories. (The Planet Money segment tells a couple good ones.) I'm curious whether GiveDirectly will move toward finding ways to do their data-driven work while also communicating more and more effectively with story-driven donors.