Abstract
Supply chains are central to food security modeling, particularly in famine-prone settings, yet traditional analyses rarely adopt a system-wide perspective that accounts for their influence. One reason is that conventional predictive approaches used in supply chain analysis and systems modeling are difficult to calibrate and validate in contexts marked by sparse data and rapidly changing conditions. Drawing on a 6-year collaboration with USAID in Uganda, we argue that in such settings, an adapted system mapping approach can enable system-level analysis and produce actionable insights. We present our approach and examine its application to the Karamoja region of Uganda, where USAID sought to strengthen household resilience. We demonstrate the value of descriptive and prescriptive models in contexts where prediction is not feasible. In Karamoja, this approach highlighted the central role of supply chains in resilience outcomes and supported collective sense-making and collaboration among practitioners.