QCA as an approach to make sense of micro-level data-centric practices for policy innovation: a walk-through

The paper explores the potentialities and challenges of using a comparative research method — Qualitative Comparative Analysis (QCA) — as a methodological approach for researching policy innovation. The paper argues for QCA to constitute a rigorous and systematic way to explore policy innovation using micro-level experimental and innovative practices in the public sector as the empirical base. Conceptually, we propose considering the importance of policy workers in policy innovation processes. This proposal addresses a gap in policy innovation research that appears to have mostly focused on entrepreneurship while under-appreciating other individual agency explanations of change (e.g., policy workers). Policy innovation researchers should therefore reframe the concept of policy innovation from an out-based view to a process-based view, while avoiding the development of ideographic knowledge. To address this issue, we provide a walk-through of using QCA as a methodological approach to investigate data-centric practices in the public sector. In the walk-through, we simulate the execution of the first three steps of approaching different cases of data-centric practices through QCA, identifying variables and calibrating them. Other researchers might find this approach useful to investigate similar innovative practices in the public sector in the perspective of policy innovation.