I have worked with the concept of ‘impact pathways’, or ‘theories of change’ for nearly 20 years. Perhaps the best advice I have received in this time is that theory of change should tell a good story. A good story draws you in, it is compelling because it is about real people in real places. We come back to good stories and find deeper meaning when we do. They teach us something and challenge the way we think about things – they challenge our underlying mental models. As humans we are hardwired to respond to stories; we fill in the gaps in the plot from our own experience if we find them compelling. I think the analogy works because one would hope that those involved in implementing and evaluating programs would relate to a program theory of change in the same way.
At about the same time I got this advice I came across Christopher Booker’s book on the seven basic plots that underpin all story telling. These are:
1. Overcoming the Monster
2. Rags to Riches
3. The Quest
4. Voyage and Return
A story plot pertains to the main events of a play, novel or film, presented by the author in an inter-related sequence.
Booker also introduces the idea of an overarching meta-plot that reaches across and binds together the more detailed aspects of the story. This matches well with the idea of nested theories of change in which a program is made up of a number of interventions, each with their own theories of change, bound together by an overarching theory of change.
If a theory of change should tell a good story I wondered if there might be basic plots by which agricultural research works to achieve impact. I identified three causal plots, or impact pathways, from my own experience of working with theory of change as a way of making research more developmentally relevant:
- Impact through the adoption of research output – the technology development and adoption pathway
- Impact through building the capacity to innovate of agricultural innovation systems – the capacity development pathway
- Impact through influencing policy – the policy influence pathway
Figure 1 shows that at the highest level, agricultural research for development achieves impact by catalyzing and supporting processes of innovation through the three pathways. The technology development and adoption pathway is the most familiar to many researchers. The capacity development pathway is less familiar. In this, the process of carrying out research builds the capacity of rural innovation systems to innovate. Participatory and collaborative research brings different stakeholders together to identify common challenges, and builds structural and cognitive social capital in the process. Soon-to-be-published research (Douthwaite and Hoffecker, 2017) shows that participatory action research builds the following component capacities:
- New technical skills, e.g. how to carry out experiments and analyze the results
- Self- and collective- efficacy
- Ability to assess options and identify key system challenges
- Ability to go through iterative visioning, planning and reflective learning cycles
- Capacity to link to other actors and to use linkages strategically in support of own plans
- Enhanced capacity for effective collective action
- Enhanced leadership skills
In the policy influence pathway, researchers generate insight and evidence with the specific intent of influencing policy, for example with respect to strategies for agriculture to mitigate and adapt to the effects of climate change. Policy change then helps build an enabling environment for beneficial rural innovation.
I think the main value of the three pathways and their interactions is that it suggests the existence of three positive feedback loops dependent on the capacity development pathway (see Figure 2). In the first virtuous cycle, increased rate of innovation leads to more interactive, experiential learning that leads to greater capacity and opportunity to innovate in terms of new links and new ideas, knowledge and technology. In the second cycle, faster rates of innovation speed up the adaptation and adoption of research output, thus increasing the impact of the technology development and adoption pathway. In the third cycle, faster rates of institutional innovation create an enabling environment for innovation, and so on. The model suggests that agricultural research might better serve overall rural development if it focus on inducing sustained virtuous cycles, rather than the current fixation on adoption of research output. Indeed, some would argue that pushing for the adoption of externally-generated technology damages rural innovation systems by creating the idea that external sources of innovation are better. While there is some evidence to the existence of these virtuous cycles, more is needed.
Another value of the three pathways is helping staff in on-going programs to identify their main pathway. I have been part of two programs that were closed down partly as a result of unfavourable external reviews (the Rural Innovation Institute at International Center for Tropical Agriculture (CIAT – Spanish acronym) and the CGIAR Research Program on Aquatic Agricultural Systems). In both cases I felt we were not evaluated against what we were trying to do but against the evaluators’ pre-conceptions of what CGIAR research should look like. In both cases we were pursuing a capacity development pathway but evaluated against our production of so-called international public goods, in other words against the technology development and adoption pathway.
I have found the following schematic (Figure 2) useful in helping people think through where their own work fits with respect to the three pathways. In doing so, workshop participants have found it helpful to further differentiate their respective approaches according to scale – either ‘local to regional’ where research is carried out within, and in response to, specific on-going development processes or ‘regional to global’ where the work does not have the same level of grass-roots engagement. One result of locating program approaches in this framework is that it helps program staff identify the main pathway to which they directly contribute — their main contribution to the overarching program theory of change (the meta-plot) and how both may change over time. Hopefully it will help them avoid feeling stupid the next time they are evaluated!
See here for a video that covers some of this.