Workflows for Knowledge Co-Production—Meat and Dairy Processing in Ohio and Northern California

Solving the wicked problems of food system sustainability requires a process of knowledge co-production among diverse actors in society. We illustrate a generalized workflow for knowledge co-production in food systems with a pair of case studies from the response of the meat and dairy production sectors in the wake of the COVID-19 pandemic. The first case study serves as an example of a scientific workflow and uses a GIS method (location allocation) to examine the supply chain linkages between meat and dairy producers and processors in Ohio. This analysis found that meat producers and processors are less clustered and more evenly distributed across the state than dairy producers and processors, with some dairy processors potentially needing to rely on supply from producers up to 252 km away. The second case study in California adds an example of a stakeholder workflow in parallel to a scientific workflow and describes the outcome of a series of interviews with small and mid-scale meat producers and processors concerning their challenges and opportunities, with the concentration of processors arising as the top challenge faced by producers. We present a pair of workflow diagrams for the two case studies that illustrate where the processes of knowledge co-production are situated. Examining these workflow processes highlights the importance of data privacy, data governance, and boundary spanners that connect stakeholders.