The increasing amount of data that can be collected from interconnected devices offers various opportunities for the co-creative innovation of datadriven services. It demands for the integration of traditional and new actors that have to deal with alternating roles. Using a modified Delphi method, this study takes a microfoundational view and investigates the roles and capabilities of individual actors that together shape an organization's ability to innovate. By identifying relevant activities and their relative importance in the innovation of data-driven services, the study specifies nine actor roles and their contribution to organizational capabilities. The findings indicate that technical roles are less important than those that shape mindset and strategy. The paper contributes to current research on the utilization of data for service innovation by providing a microfoundational view of individual actors that helps to account for such higher-level phenomena as dynamic capabilities.
Data collected from interconnected devices offer wide-ranging opportunities for data-driven service innovation that delivers additional or new value to organizations’ customers and clients. While previous studies have focused on traditional service innovation and servitization, few scholarly works have examined the influence of data on these two concepts. With the aim of deepening the understanding of data as a key resource for service innovation and overcoming challenges for a broader application, this study combines a systematic literature review and expert interviews. This study (a) synthesizes the various existing definitions of a data-driven service, (b) investigates attributes of data-driven service innovation, and (c) explores the corresponding organizational capabilities. The goal is to examine the repercussions of data utilization for service provision. The findings indicate that the use of data makes service innovation more complex. Data add new attributes, including a data-oriented culture; issues of data access, data ownership, privacy, and standardization; as well as the potential for new revenue models. The paper contributes to current discussions by providing an aligned perspective of theory and practice in data-driven service innovation and recommending that managers implement a culture and strategy that embraces the specifics of data usage.
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