Parallel learning loops in collaborative innovation: Insights from digital government

The implementation of digital innovations in the public sector—such as Electronic Health Records (EHRs)—requires decisionmakers to engage in learning processes. This article investigates how collective learning processes unfold in collaborative innovation, focusing on the development of Switzerland's national Electronic Health Record (EHR) system. Building on policy learning and collaborative governance literatures, we conceptualize learning as comprising two interdependent processes: policy-oriented learning (focused on technical effectiveness) and power-oriented learning (concerned with political feasibility). Drawing on 39 semi-structured interviews and extensive document analysis, we find that the EHR initiative followed a sequential learning pattern—technical solutions were developed before sufficient political support was secured—leading to a politically endorsed but technically flawed implementation. The study introduces the concept of parallel learning loops to explain how simultaneous engagement with technical and political dimensions can improve innovation outcomes. These findings advance theoretical understanding of collaborative learning in digital government and underscore the need for institutional designs that support concurrent technical and political deliberation in complex innovation processes.