Understanding Data-Driven Product Service System characteristics: a conceptual framework for manufacturing applications

The explosion of digital technologies and data analytics capabilities are leading companies to rethink they offers and expand more than ever their business into the service domain. Specifically, considering manufacturers, the emerging possibility to connect products and create IoT architectures at the customer side, enable them to retrieve data flows during the products’ lifecycle. Analyze those data opened opportunities to obtain information to use intra-organization and at the same time to enhance already existing service or to develop new ones. Even the potential of data availability in this context is recognized in the literature, further work is still needed, especially defining how these new data-driven offers should be engineered and structured. In this view, this study provides a comprehensive interpretation on the general key components and characteristics of those services, defined as Data-Driven Product Service Systems (DDPSS), aiming at supporting the comprehension of specific principles and consequently the systematic creation of DDPSS. Indeed, limited research is devoted to the definition of the unique characteristics of those services and common agreement is still missing. The paper developed a two-hierarchical conceptual framework describing DDPSS typologies is proposed. The framework value is twofold: first it categories and harmonizes service typologies into a structured model and second, it can be used as a support tool during the service design phase, since it can inspire and guide service development. In the end, the paper also presents an explorative application of the conceptual framework within a different manufacturing company. The applications show both the descriptive and the prescriptive nature of the model; indeed, it is used to analyses the current position and to propose new trajectories for the companies’ service offering.