When I first started hearing folks talking about complexity and social change 10-15 years ago, I figured that was fine for the ecologists and physicists, but not much use to me. Yet the more I heard, the more the ideas started making intuitive sense to me. When you’re working for social change, you’re mucking with complex adaptive systems, and our old time straightforward, linear management tools (such as logframes) just don’t cut it.
I’ve written before about complexity and managing social change (check it out if you want to see Mao compared to a spider’s web). And if you’re like me, you find it’s easier to talk about complex adaptive systems than it is manage them. So it’s very helpful to know that there are lots of tools out there for practical approaches to planning for, managing, and evaluating complexity. Today’s blog is about a few of the cool tools that are “complexity aware,” and helpful in making us more successful where the right path forward is not clear from the beginning.
These tools flip the logic of traditional management approaches. Instead of anticipating what might happen and laying out a plan to deal with it, many of these tools jump to what happened, or might happen, and track back to what you did that might have contributed to it.
That’s right, contributed, not caused. It’s actually liberating to give up claims that you and your colleagues are responsible for some key policy change, cultural shift, or rebalance of power. That’s just not how social change happens. These tools liberate you to look at what forces are pushing in different directions – cultural, political, technological, economic, whatever it is you suspect matters – and gauge the contribution of each to the results you want to see.
So below are some of my favorites, though there are many more. Feel free to point to others in the comments below.
Outcome Harvesting and Mapping
One tool that is especially useful for monitoring and evaluation is Outcome Harvesting (developed by Ricardo Wilson-Grau and his colleagues), and the closely related Outcome Mapping (developed by the International Development Research Centre in Canada). These two methods don’t try to predict social reality in any great detail, or at least don’t assume that what you want to happen will.
While logical frameworks are good for disciplining our thinking, change in complex situations often produces unexpected results which can be hard to capture with logframes. These outcomes take place in a context of many players, social forces, global and local trends. The Outcome Harvesting method can help get at outputs and outcomes that were unanticipated or came about in unexpected ways. This method is well suited to complex adaptive systems, where there are indirect relationships between program inputs and outcomes.
The method is also valuable in that it integrates stakeholders in the process of learning what’s going on, rather than some external facilitator. While there are many steps in the process, for me the essence is giving people a structured way of thinking about outcomes, whether intended or not. For collecting observations from participants, a simple form such as the following can guide participants to watch out for outcomes, whether expected or not.
Systems Mapping
If your goal requires you to work with stacks of moving parts – reducing homelessness, defending territory from extractive industry, overcoming achievement gaps in education – it can be helpful to create a map showing what forces are pushing in what directions. These maps can give you a picture of what’s going on, and suggest paths to influence that are most likely to succeed.
Systems mapping is not including everything, it’s knowing what to exclude. And as Bob Williams is fond of pointing out, what you include and what you leave out are always ethical decisions: who gets to be part of the system and whose perspective is taken into account.
An example of what such a map might look like comes from work we did in West Africa in mapping out Food Security:
Now the important thing here is not the product – in fact these maps are pretty eye-crossing, to tell the truth. The real value is in the process of getting a group together to discuss the issues and hear each other’s perspectives on what’s in and what’s out, and what the relationships among the elements should be. These maps can help then figure out how you’re going to work together, and what avenues are most likely to be productive, and which are just a bridge to far at this point.
Social Network Mapping
An additional tool that can be very useful for planning is to map out the main players in their system. In this way, participants can generate a clear consensus about who is important to the system, who has influence and who does not, and which players the agency can most likely influence.
The map below is an example: it represents the world of funding of issues important to Indigenous Peoples. This map was created by participants, and clarified who played what roles, who was within two degrees of separation of participants, and what kind of relationships participants wanted with the various players over the next five years.
Note that I am not talking Social Network Analysis here, a related but quite different tool. Social Network Analysis (SNA) tends to use questionnaires to generate a social matrix, that then creates a map with specialized software. While SNA maps have a certain “wow” factor, I find that participants have a harder time interpreting them, since the machine-generated maps can mask mistakes or biases in the underlying data, and lead participants to false conclusions about who is in relationship with whom and how. They are also harder for participants to manipulate themselves as they update their understanding of relationships and lines of influence. The method I prefer instead asks participants to generate their own maps based on their own experience and perspective. They reflect their lived experience, and can build in far more nuance. Debates over the maps generate consensus among participants, which is important for developing a Theory of Change. The more perspectives the process includes, the more valuable the maps are.
So this is just a sampling of the many tools being developed and used to take complexity seriously. Let me know which you’ve found useful, and how you’ve used them.