Most of us have not seen a rhinoceros in the wild. We might have seen a rhino at the zoo and maybe on television. Only a few of us who live outside Africa have been fortunate enought to see one of these beautiful creatures in its natural habitat. Imagine we’d never seen a rhinoceros in any form? Dürer’s Rhinoceros is an example of what we get if we have good information without sightlines on the actual thing being described. The name is based on the work of German artist Albrecht Dürer who composed a visual of a rhinoceros from secondhand notes, without ever having seen the animal.
It looks pretty close.
Dürer’s rhinoceros is like many of the systems and innovation models out in the world (you’ve probably seen them shared on LinkedIn or other social media). We’ve not actually seen the system or the ideas represented, but we have a lot of stories and images. That’s where I take issue: we speak of systems change models without much other than ideas and little evidence. While these ideas may turn out to be true, right now, they are more hypotheses than models, yet they don’t get treated this way.
So what are we looking to change the system with? In short: systems change (and evidence for our models) require a reality check (or update).
Modelling and Evidence
Models help us to think and ‘see’ things. There is strong evidence that visual models, such as illustrations, diagrams, and concept maps, significantly enhance learning and communication, particularly for complex concepts. According to Dual Coding Theory (Paivio, 1971), people process information through both verbal and visual channels, and using both strengthens memory and understanding. Cognitive Load Theory (Sweller, 1988) shows that visuals can reduce the burden on working memory, making complex information easier to process.
Mayer’s Multimedia Learning Theory (2001) further supports the idea that combining words and images leads to better comprehension than using words alone. Research on concept mapping (Novak & Cañas, 2008) demonstrates that visuals help organize and relate ideas, deepening conceptual understanding. Lastly, research from cognitive neuroscience confirms that visual-spatial representations activate brain networks associated with problem-solving and comprehension (Yarkoni et al., 2003).
While we have much evidence to support using visual models to engage people in learning, we lack the same evidence for the models themselves. While models are useful means to provoke inquiry about systems, they are not the system itself. This last part is often forgotten.
There’s a risk that we design strategies for changing systems based on false, misleading, and incomplete representations of reality. Systems change initiatives are resource-intensive. Thus, committing to a course of action based on a model or theory of change is not inconsequential. Further, adopting a model of change can also create a mindset that shapes how we think and conceive of addressing a problem.
We see this with other models and theories in psychology. For example, cognitive rational models of change take as the presumption an information deficit and that the quality of the evidence and its communication is what changes people. This model, while having its merits, neglects the role of emotions, situational, and environmental factors that shape behaviour. It’s why many generations of public health campaigns around drug and tobacco use (“just say no”, “smoking kills”) failed to shift population health outcomes in any substantive way. Only through other means could the benefits of the cognitive rational models be leveraged. We had to take a systems approach and use models and approaches that had evidence. (See Greater Than the Sum for how this was done).
All of this was backed by evidence.
Strategic Design for Systems Change
What we see in systems change efforts is a lot of energy in celebrating representations of how people perceive change, but not on whether these perceptions align with reality. We lack the evidence base to guide many our strategies.
Systems change practice and praxis require evidence generation and strategy working together. This is where strategic design comes in. Strategic design connects our intentions with evidence and an understanding of context, especially systems, to create a path from where we are to where we want to be. Just as a roadmap is not the journey, so is a system map not the system. To extend that metaphor, we use evidence to assess speed, direction, weather conditions and elevation when travelling. System models aren’t applicable without an evidence plan to guide their implementation by design.
Otherwise, they are just maps, just as I thumbed through the pages of my National Geographic World Atlas as a kid to dream of places I would go. Those were dreams, not reality.
The many systems around us, such as those found in healthcare, social policy, and the protection of our environment, require that we get honest about what we intend to do and how we get there. That means looking at what models we choose to shape our thinking and actions. I also means being systematic and creative in generating our maps and models. It means knowing when we see a rhinoceros in the wild and when we’re looking at pictures.
Image Credit: Albrecht Dürer – National Gallery of Art., Public Domain,
References for further reading:
- Paivio, A. (1971). Imagery and verbal processes. Holt, Rinehart, and Winston.
- Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285.
- Mayer, R. E. (2001). Multimedia learning. Cambridge University Press.
- Novak, J. D., & Cañas, A. J. (2008). The theory underlying concept maps and how to construct them. Institute for Human and Machine Cognition.
- Yarkoni T, Speer NK, Zacks JM. Neural substrates of narrative comprehension and memory. Neuroimage. 2008 Jul 15;41(4):1408-25.