As part of some research the Monitor Institute has been doing on how to effectively identify early-stage, high-potential grantees, I’ve been thinking a lot lately about the role of intuition in philanthropy. I was introduced to the idea by Chet Tchozewski of the Global Greengrants Fund, who has been talking about intuitive grantmaking for a few years now. He came to it out of necessity. Global Greengrants was giving away extremely small grants (often $5,000 or less) to grassroots environmental organizations, so it couldn’t afford to spend thousands of dollars on a rigorous due diligence process. His solution was to use a network of on-the-ground advisors in the regions where GGF is funding, and to trust those advisors’ instincts and knowledge about who would be good grantees. Global Greengrants feels that this system has worked well over the years. And while their process may not be as thorough as what some other foundations use, there is a clear sense that this intuitive approach is “good enough.”
This notion of trusting the intuition, knowledge, and experience of experts was echoed as I recently began to talk with funders doing innovation grantmaking and a few folks from the venture capital world. VC’s do a great deal of research, but it often comes down to the idea of trusting their gut. It’s about intuition. And intuition, when you drill deeper to figure out what’s behind it, often appears to be in large part about pattern recognition.
It was Patrick Maloney of the Lemelson Foundation who suggested to me that vetting high-risk, early-stage efforts is really about pattern recognition. He explained that you get really good at recognizing one "pattern" that works—one type of team or approach that is likely to succeed. But recognizing one pattern doesn’t mean that you’re good at catching all of the good ideas. You end up missing a lot of things that might succeed, because you’re really good at seeing the single type of pattern you know. As Maloney explained to me, “You may get good at picking grants that work, but you’ll never be great at picking what won’t work, because you don’t know what other types of things, outside your pattern, will succeed.”
And this is where the power of networks comes into the picture. By using a network of knowledgeable experts, each of whom is good at recognizing a certain type of pattern that works, you can ultimately catch many more of the types of things that will succeed. Call it “network intuition” if you will—building on the cumulative pattern recognition of multiple expert perspectives to create a more systematic way of using intuition.
A networked approach to intuition also allows you to eliminate some of the error and bias that can creep into intuitive judgments. It’s possible to see the flaws when you’re using logical reasoning, but it’s almost impossible to catch mistakes and biases in your intuition. By compiling the perspectives of a network of advisors, you can begin to filter out some of the specific biases that might taint a single individual’s intuition.
In many ways, the idea of intuitive grantmaking flows naturally from Clayton Christensen’s theories about disruptive innovation. He talks about how cheaper, simpler versions of products or services that are "good enough” for many users can ultimately displace more sophisticated offerings. Think, for example, of the way that IBM was focused on making mainframe computers in the 1970s, allowing the upstart personal computer to build a new market serving as a “good enough” tool for most everyday users. PCs were aimed at a new market that manufacturers of the larger product weren’t interested in, and the machines ultimately moved up-market through performance improvements until they actually started competing for customers that used to be buying mainframes.
This idea was on my mind when I went to the “Innovation and Evaluation” meeting at IDEO a few weeks ago. If intuition can be used as an effective, “good enough” tool for due diligence, could it also be applied to evaluation and impact assessment? In many ways, it seems a natural fit. Right now, the social sector is clamoring for quasi-experimental control groups and sophisticated evaluations that cost a great deal of money, but more often than not produce inconclusive findings. Because of the challenges of proving causality in the social sector, the result of many of these expensive studies often ends up being: “It depends.”
And while I’d never argue that we should stop trying to find better metrics and better approaches for measuring impact, I have begun to wonder whether in some cases, we might be better off developing methods for using and trusting the intuition of a network that will allow us to do a “good enough” job of assessing our impact?
I don’t have answers here yet. But it seems like something worth thinking about.
- What would it look like to do intuitive impact assessment?
- Who would be the right network, and how would you build it?
- And would it really be “good enough?”
I’d love to know what others might think about this.
Gabriel Kasper is a consultant at the Monitor Institute, a social enterprise that helps innovative leaders develop and achieve sustainable solutions to significant social and environmental problems.