Design for policy in data for policy practices. Exploring potential convergences for policy innovation.

This position paper recognises and investigates a gap between two fields of research and practice dealing with innovation in public policy: data for policy and design for policy. These fields act within government and the public sector, but with a different focus. On the one hand, data for policy deals with the use of non-traditional digital data sources for policy-making (as administrative or citizens-generated data) and emergent organisational practices connected to these data (e.g., data collaboratives). On the other hand, design for policy inquiries the adoption of design approaches, methods and tools in policy-making and public services development. The difference in focus explains the current gap between the two fields and implies different approaches toward policy innovation. This paper advances an argument in favour of explicitly and systematically connecting these fields. To do so, I propose three areas of convergences by looking at experiences in the data for policy field. In these areas, I look at the value of this integration through the lens of policy innovation, intended as innovative ways of learning about policy-related matters that can influence the design of policies. The perspective offered is directed to scholars and practitioners in both fields and hopes to sparkle a fruitful discussion on innovative policy epistemologies needed to address the contemporary complexity of policy problems. In the paper, I first contextualise my reasoning line by reviewing the concept of public sector innovation (PSI). Then I consider different disciplinary perspectives about one particular subset of PSI: policy innovation. Starting from these authors, I propose to see policy innovation as innovative ways of learning about policy-related matters that can influence the design of policies. I hypothesise three potential areas of convergence between data for policy and design for policy by holding this perspective. To support them, I will draw on illustrative examples found through a systematic review of articles published in the past editions of the Data for Policy Conference.