There is increasing recognition of the wicked nature of the intertwined climate, biodiversity and economic crises, and the need for adaptive, multi-scale approaches to understanding the complexity of both the problems and potential responses. Most science underpinning policy responses to sustainability issues, however, remains overtly apolitical and focussed on technical innovation; at odds with a critical body of literatures insisting on the recognition of systemic problem framing when supporting policy processes. This paper documents the experience of implementing a mixed method approach called quantitative story-telling (QST) to policy analysis that explicitly recognises this normative dimension, as the methodology is part of a post-normal science (PNS) toolkit. The authors reflect on what was learnt when considering how QST fared as a tool for science-policy interaction, working with European Union (EU) level policy actors interested in sustainable agriculture and sustainable development goal 2. These goals-also known as UN Agenda 2030-are the latest institutionalisation of the pursuit of sustainable development and the EU has positioned itself as taking a lead in its implementation. Thus, the paper illustrates our experience of using PNS as an approach to science policy interfaces in a strategic policy context; and illustrates how the challenges identified in the science-policy literature are amplified when working across multiple policy domains and taking a complex systems approach. Our discussion on lessons learnt may be of interest to researchers seeking to work with policy-makers on complex sustainability issues.
Keywords: Agriculture; European Union; Post-normal science; Quantitative story-telling; Science–policy interactions.
© The Author(s) 2023.