This article examines the implications of adopting a socio-technical perspective on the design and implementation of GovTech solutions. To observe the phenomenon, it adopts a case study approach focusing on the WiseTown solution and its City Digital Twin (CDT), developed by the Italian company TeamDev. The article investigates how integrating social factors, such as urban governance, with technical elements, like data analysis and modeling, can enhance the conceptualization, design, and implementation of user-centric, data-driven digital solutions as part of a broader digital transformation strategy. The article explores an Italian best practice that is developing four dimensions of the GovTech socio-technical framework: Governance Structures, Institutional Arrangements, User and Context Understanding, and Technological Development. It critically examines and discusses the challenges and opportunities associated with the adoption of CDTs and their impact on public policy implementation. The analysis is centered on two main aspects that emerged from the case study: data integration and sharing within CDTs, and the social implications associated with data usage for decision-making. Ultimately, the article explores the role of stakeholder collaboration (public-private partnerships) and the creation of innovation ecosystems—GovTech ecosystem in this specific case—to inform and steer policymaking through and beyond the adoption of CDTs.

Societal challenges such as climate change and health inequalities require complex policy decisions, for which governmental organizations rely on a good information position. Having access to data from various domains is seen as a facilitator of making evidence-informed decisions that are more legitimate and less uncertain. To identify and make data available that is stored at various organizations, stakeholders participate in sociotechnical networks, also known as data ecosystems. Data ecosystems aimed at addressing societal challenges are characterized as complex because knowledge about societal issues is uncertain, information is scattered among (governmental) actors, collaboration extends beyond existing organizational networks, and values and interests of network actors can be conflicting. In this translational article, we examine how to successfully establish and maintain data ecosystems aimed at addressing societal challenges, given these complexities. We analyze two cases of successful data ecosystems in the Netherlands and present five narratives about how these data ecosystems navigated these complexities. We find that establishing collaboration among network actors, using bottom-up approaches, contributed to the success of both cases. The cases created structures in which participants were able prioritize the right questions, find common interests, and work together. The narratives present insights for government officials about collaboration in data ecosystems and add to the literature by highlighting the importance of organizational capabilities.