Three Shifts Philanthropy Needs to Make to Better Design and Evaluate Social Change

Good strategy-making and evaluation sit at the heart of philanthropy. Yet as a sector, we continue to struggle with how to design strategies, how to understand our impact, and how to use that understanding to drive stronger strategies. While we've made progress in using theories of change, logic models, indicators, and various types of evaluations in our work, we are often still stuck in more traditional, linear paradigms of thinking that do not lend themselves to the complex, ever-changing contexts in which we work.

I believe there are three key shifts that philanthropy needs to make to more fully embrace a complexity-friendly approach to designing and evaluating social change:

From...		To....
Projects	→	Systems
Results	→	Hypotheses
Planning	→	Learning

From Projects to Systems: Most foundation staff tend to think of their work in terms of programs, projects, or even specific grants. There is value in opening up the aperture and examining the whole system, with all its interconnected components.

At the Democracy Fund, we created elaborate "systems maps" to explore the connections and dynamics that characterize the systems we seek to influence and created strategies that utilize specific "leverage points" in the system. While evaluating the impact of our strategies, we look not only at indicators of program impact but also at a set of "system impact indicators" that track system-level variables.

For instance, while our Elections program tracks how many jurisdictions are adopting a particular tool (program impact), it also tracks how voter confidence in elections is shifting overall (system impact). The point is not to attribute causality, but rather to situate and understand our impact in the broader context of how systemic variables are moving. (To learn more about taking a systems and complexity approach to evaluation, check out Evaluating Complexity.)

From Results to Hypotheses: While results matter greatly, we often spend inordinate time and effort on them and not enough on articulating and clarifying the hypotheses and assumptions that undergird our thinking.

In my previous role as a philanthropy consultant, I had a client who set a target of 88 percent high school graduation as the key result they wanted to see. A lot of deliberation and negotiation had gone into that number. There was just one glitch — almost all their programming focused on third-grade reading. While there could be a hypothesis that connects third-grade reading to high school graduation, the links are tenuous, at best.

The point here is to think through exactly how difficult are the challenges we are tackling, and what kinds of efforts and resources are needed to achieve the results we want. Making the hypothesis and assumptions explicit also sets us up well to test them. (A helpful resource on taking a hypothesis-based approach is this report on Evaluating Ecosystems Investments.)

From Planning to Learning: Most of us that came to philanthropy in the last two or three decades were indoctrinated into a traditional form of "strategic planning" that takes several months to complete and involves a process that proceeds from vision and mission to goals, objectives, strategies, and tactics. I believe that is a luxury we can no longer afford.

In a rapidly evolving context, the challenge is more about creating an adaptable and flexible plan that can keep up with the times, complemented by a robust learning agenda. A learning agenda should have a few components — a set of questions (about context, implementation, results) that must be answered, a plan for actually collecting the information through monitoring, research, and evaluation, and structures and processes for using the information to create meaning and drive decisions.

Accountability around the last component is critical, as without it what is learned often sits on a shelf. At the Democracy Fund, in addition to internal learning processes, each program team also goes in front of the board for a "learning conversation" roughly every twelve to eighteen months to recap lessons learned and offer mid-course corrections. Other foundations have instituted a variety of learning processes as well (such as those outlined in this report on Learning in Philanthropy).

Underneath each of these shifts is a humble and honest reminder that language matters in all of this. While "goals" and "targets" convey a sense of direct control, "aspirations" and "informed predictions" convey a more thoughtful, flexible direction. Even small changes like this to how we think about our work will influence how we move forward as a sector.

Philanthropy is driven by meaning that informs action. At a time when philanthropy is being criticized on various fronts, it is imperative that we seriously examine how we construct meaning — and do so in a way that strengthens our legitimacy. The three shifts outlined above are subtle yet powerful ways for philanthropy to challenge itself.

Srikanth Gopal guides overall strategy and the programmatic portfolio at the Democracy Fund, where he also develops learning systems to ensure that the fund is impactful in its work. This post originally appeared on Candid's GrantCraft blog.