Assessing food systems as complex adaptive systems
Food system assessments may be able to simplify their approach, and foster more effective action, by framing the food system to be assessed as a complex adaptive system (CAS): as a system in which component entities are learning from each other and adapting to what they learn. These shifting interactions, often involving the core dynamics of the system itself, may pose considerable difficulty to more linear approaches to measurement. As one example, by the time a given data set or interview is compiled and published, the findings may no longer reflect current conditions.
Introducing a conscious approach to adaptive complexity reaps several rewards. First, it harnesses quantitative and qualitative data to illuminate core system dynamics. Second, it taps essential wisdom from community members, helping to identify the essential levers that can move a given food system to greater sustainability. Third, by so doing, this approach facilitates community foods initiatives that develop systemic theories of change, for which indicators cut across issues that are often separated by disciplinary divides. These suggest measurement approaches that illuminate how system dynamics have shifted, and whether systems levers have moved, rather than focusing solely on programmatic outcomes. While this approach is discussed in the US context, the core elements can be applied in other countries.