Five Lessons for New Philanthropists

Recently, Napster co-founder Sean Parker announced the funding of the Parker Foundation and posited some advice for the coming wave of Silicon Valley “hacker philanthropists.” Parker’s fundamental critique is that traditional philanthropists are neither as transparent nor accountable as they should be, and lack the tools needed to measure impact and solve problems. This isn’t a radical proposition. Telling foundations that they need to do a better job maximizing and measuring impact is like telling a company they need to do a better job maximizing revenues.

The question isn’t whether we should do this. It’s how.

Parker’s critique of traditional philanthropy as a “strange and alien world made up of largely antiquated institutions” has a ring of truth; the philanthropy sector can be opaque and slow moving. Yet foundations and individual philanthropists have been trying to maximize impact for generations, and more so now than ever before. Ignoring these decades of experience and existing networks of experts doesn’t make you innovative—it simply means that you have a strong chance of reinventing the wheel.

To that end, we suggest that new philanthropists consider the following:

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Scan the ecosystem first. Your ideas may seem disruptive, but there is a chance someone smart is already doing it. Before you embark on creating the next big thing, check to see if there are organizations, academics, or funders working in the same direction. Warren Buffet saw this in philanthropy and gave his money to Bill Gates. Matt Damon saw this in water and gave his money to Water.org. You wouldn’t get far trying to disrupt the ride-sharing market if you had never heard of Uber. The social sector is no different.
Make the time. Systemic change takes time for the doers and the donors. Changing the status quo on a given issue at scale requires a lot of work and substantial amounts of coordination. It’s easy to talk about “hackable” problems, but it’s much harder to find discrete issues where you can have an immediate impact, especially if you’re focused on broader social change; providing malaria nets, for example, is not the same as providing quality healthcare to a mostly rural population. So you need to understand why the status quo is the way it is. You need to understand who is working on that problem, and the extent to which they have—or haven’t—succeeded. If you want to give smart, you have to make the time to dig in or get someone else to.
Get comfortable with ambiguity. For complex social issues, it’s difficult—if not impossible—to determine cause and effect. No single intervention will create better education outcomes or more-effective health care systems, much less resolve conflict in Syria. There are just too many players and factors involved. Impact is indeed difficult to measure, but attribution is even more difficult in so-called “wicked problems.” Before you start giving, decide whether you are comfortable working on an issue where, at best, you might be able to measure total impact but not your specific role in contributing to that impact.
Give unrestricted funding. One of the most profound lessons funders and service providers have learned is the essential role that unrestricted funding (often called general operating support) plays in helping organizations scale. When you tell a nonprofit they can only do certain things with the money in a certain timeframe, it fundamentally limits their flexibility and hence their ability to adapt, change, and grow. Can you imagine a venture capitalist giving money to Facebook, and then saying it could only use the funding for engineering, not for product development, servers, business development, or marketing? Exactly.
Use data as a tool, not a solution. The social sector is doing some exciting work on gathering and analyzing data related to social issues. In particular, we are doing a better job of capturing broader swathes of data, and using this to inform and test our interventions. But we need to remember that this data is almost always incomplete and may only tell part of the story. For instance, a child may fall behind in school because she doesn’t have enough to eat or because of a family history of abuse. Judging her performance solely as a function of the school environment is insufficient. We must know the limits of data and the value of testing ideas, measuring, sharing results, and trying again.