“Moneyball,” “Freakonomics,” & Philanthropy
| Other articles on: | Philanthropy & Responsible Investing |
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| Posted: | September 23, 2008 10:07 AM |
| Author: | Sean Stannard-Stockton |
Earlier this spring, The New York Times Magazine featured the fascinating article “What Makes People Give.” The article chronicles the attempts by John List and Dean Karlan, economists at Yale and the University of Chicago respectively, to understand why people give.
List and Karlan considered the usual answers—to make the world a better place, to see your name printed on the back of an annual report and the like—as too pat, too simple, and sometimes just wrong. Over the years, whenever one of them asked fundraisers why they did what they did, their responses were vague and unimpressive. There didn’t seem to be much empirical evidence to support the strategies employed by most fundraisers. So the two economists wondered whether charities were wasting a lot of effort.
When charities are designing their donor appeals, they often go by nothing more than a few rules of thumb, some of which may be profoundly insightful and others a good deal less so. “I think some fundraisers have developed terrific intuitions, passed on through the fraternity of fundraisers,” says Paul Brest, president of the William and Flora Hewlett Foundation in Menlo Park, Calif., which often works with charities. “But a lot of the intuitions don’t work. Look at how much junk mail you get.” Matching gifts were another good example. People figured that they worked, because—well, how could they not? They seem so sensible.
The story reminds me of two of my favorite books, Moneyball and Freakonomics. Michael Lewis studied the Oakland A’s’ use of statistical analysis to drive the way they built their baseball team and played the game. In Freakonomics, Steven Levitt and Stephen Dubner used economic analysis techniques to understand falling crime rates, the organizational structure of street gangs, and the inner workings of professional sumo wrestling.
What both books (and the New York Times Magazine article) use as their premise is that quantitative analysis is incredibly useful in understanding our world. Yet all three also understood that statistics do not themselves give you answers; they just help you understand your environment better so that you can more easily find the answers you are looking for. This is the promise of metrics and other quantitative measurements in philanthropy. They are not themselves the answers we seek, but they help describe the world we live in.
When used as tools to advance our understanding, metrics in philanthropy are wonderful. But when viewed as some sort magical answer that shows us the Truth, we are better off with Mark Twain as a source of insight than Moneyball or Freakonomics:
“There are three types of lies—lies, damn lies, and statistics.” - Mark Twain
Sean Stannard-Stockton is a principal and director of Tactical Philanthropy at Ensemble Capital Management. Ensemble Capital provides families both traditional investment management and philanthropic planning. He is the author of the blog Tactical Philanthropy and writes the column On Philanthropy for the Financial Times.
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Sean’s post illuminates a key issue facing the sector today. Moneyball is required reading at the company I co-founded—and for good reason. As Sean points out, this book, along with Freakonomics, offers a helpful primer on how to press beyond intuition and conventional wisdom when trying to determine what works and why. In order to truly develop and replicate best practices in the human services sector, we too must embrace this way of thinking and strive toward (while recognizing the limitations of) an evidence based approach to all aspects of our work. Not just in fundraising, but also in the way we manage and deliver services. This isn’t without risks, however. When it comes to service delivery, like fundraisers and their rules of thumb, convention tells us to stick with what appears to be working. Eventually, we do what everyone else does because everyone else is doing it. It is really hard to step away from the norm and pursue a new path with the fervor and diligence that is required to succeed against the odds – even if you believe (or know) that it is the right thing to do. As practitioners, we often fail to ask the questions or press the issue, we don’t have sufficient access to or interest in the data, and therefore, we don’t truly know whether programs and services are having the impact that we assume they are. A Moneyball or “evidence-based” approach, gives us the opportunity to use real data that provides a more accurate depiction of where a program stands. It encourages us to realize that data can be a tool that informs our daily approach to our work. Sounds simple, but this is a determination that must be consistently made and fiercely defended at every level of an organization for it to succeed. So, as Sean accurately points out, metrics may not give us the magical answer to the big questions looming over us today. But even if the application of metrics does nothing more than promote a different way of looking at things and open our eyes to what is really going on in our organizations and in our industry, then that alone would seem to justify taking the risk of unconventional, evidence-based thinking. And while Mark Twain was a genius in his own right, maybe we should look to Galileo for a little insight in this regard with his declaration that we “Measure what is measurable, and make measurable what is not so” – a phrase that is more commandment than aphorism for the true believers!
Adrian Bordone
Co-Founder and Vice President of Social Solutions
»» Posted by: Adrian Bordone on September 26, 2008 12:33 PM