Weaving Learning into the Fabric of Philanthropy: Working Smarter in the Age of Big Data
In this data-rich world, are we getting better at learning in philanthropy?
Given the growing proliferation of data in our lives—big data, digital data, automated data, etc.—one might assume that our ability to work more effectively as a result of increased information grows at a comparable rate. But research and lived experience suggest otherwise. Consider a few recent works of journalism:
- In the National Public Radio Hidden Brain podcast titled “Facts aren’t enough,” the hosts discuss the main drivers of human behavior, which surprisingly are not facts at all. Instead, people are most swayed by an argument based on their perception of the messenger’s credibility and whether the message itself incites good (or bad) feelings.
- In a popular 2017 article in The New Yorker titled, “Why facts don’t change our minds” Elizabeth Kolbert discusses the science behind cognitive biases, and how our interpretation of facts is determined by our deeply-held worldviews—i.e., our biases. Individuals add different values or levels of significance to the data and evidence put before them and thus arrive at different conclusions about the same set of facts.
- Bess Rothenberg, Senior Director of Strategy and Learning at the Ford Foundation, writes about how this applies to philanthropy in the Chronicle of Philanthropy article, “How grantmakers can better see what’s coming.”
In short, simple access to information does not guarantee what we learn. Our biases interfere and we need new ways of processing information to combat them.
So if it’s not just about data or information, what is needed to help people and organizations to learn?
Over the course of the last year, with support from the W.K. Kellogg Foundation, evaluation and learning leaders at 14 U.S-based foundations formed the “Lab for Learning” to experiment with ideas for supporting more impactful organizational learning. The Lab was led by Rockefeller Foundation partners Jane Reisman, Social Impact Advisor, and Julia Coffman and Tanya Beer from the Center for Evaluation Innovation.
Several “ground truths” about what it takes to support dynamic learning in philanthropy guided the Lab’s work, based on multi-disciplinary research on learning, the work of organizations in the sector who focus on this topic (e.g., Fourth Quadrant Partners), and Lab leaders and participants’ own decades of experience [read about the ground truths in more detail here]. The ground truths were these:
- Learning requires a transformation in how foundations work, not just what they know.
- Organizational systems acutely affect our ability to learn.
- Learning habits are best introduced into regular work routines, often implicitly.
How do efforts to support learning play out at The Rockefeller Foundation?
The Rockefeller Foundation, a participant in the Lab for Learning, focused on one of the three truths—learning requires a transformation in how foundations work, not just what they know. Learning doesn’t only take place in an isolated event or a meeting or a memo; it is an everyday practice.
The Rockefeller Foundation has been working on two routine learning habits in particular to accomplish that goal—making our thinking visible and asking powerful questions. Applied to evaluation and learning around our grantmaking, these habits will help us to better clarify and then pressure test our own hypotheses and assumptions about how change happens.
This level of practice and culture change takes time, patience, and endurance, especially for an organization that is more than a century old. Making these habits stick in the short term requires that the individuals who make up an institution get “smarter” about how to shift deeply-rooted individual and organizational patterns. We need to ensure that new habits lead to new rewards or paybacks to show that they are worthwhile.
What does it take to shift learning habits in philanthropy?
Lab for Learning participants concluded that new learning practices are more effective and have greater staying power when they are introduced as smaller-scale experiments that staff can help to shape and adapt. Once they are tested for the value they add, only then should they be scaled or integrated into the regular workflow so that staff experience them as integral to their work rather than something that has been added on as another procedural requirement.
The Lab for Learning is continuing to work further to shift habits in ways that improve philanthropic work. Data is important, but we need better learning habits to ensure that the data is leveraged to lift up impact.