The shift from product to service-centric manufacturing companies has been considerably fostered by technological advancements and Smart Connected Product (SCP) adoption. In particular, the data collected at customers’ locations supports the definition of innovative Product-Service System (PSS) solutions, defined as Data-Driven PSSs (DDPSSs), which provide a new source of value to both manufacturers and customers. In this context, the paper aims to provide an overview of how B2B industrial companies are approaching the path towards data-to-value transformation. To reach this aim, the paper presents and analyses seven empirical case studies, through the lens of an existing framework which depicts DDPSS characteristics. Specifically, it evaluates the dimensions that characterise DDPSS: data source, data visibility, response mechanism and decision ownership. As a result, the paper highlights the most frequently implemented features, as the collection of several data types and the areas on which companies are less ready, as the openness to the ecosystem, bringing out industrial needs and possible future research interests.

(2021). From Data to Value: how are B2B companies working on the data-driven PSS transformation? . In ...SUMMER SCHOOL FRANCESCO TURCO. PROCEEDINGS. Retrieved from http://hdl.handle.net/10446/210380

From Data to Value: how are B2B companies working on the data-driven PSS transformation?

Zambetti, Michela;Pezzotta, Giuditta;Barbieri, C.;Pinto, Roberto;Saccani, N.
2021-01-01

Abstract

The shift from product to service-centric manufacturing companies has been considerably fostered by technological advancements and Smart Connected Product (SCP) adoption. In particular, the data collected at customers’ locations supports the definition of innovative Product-Service System (PSS) solutions, defined as Data-Driven PSSs (DDPSSs), which provide a new source of value to both manufacturers and customers. In this context, the paper aims to provide an overview of how B2B industrial companies are approaching the path towards data-to-value transformation. To reach this aim, the paper presents and analyses seven empirical case studies, through the lens of an existing framework which depicts DDPSS characteristics. Specifically, it evaluates the dimensions that characterise DDPSS: data source, data visibility, response mechanism and decision ownership. As a result, the paper highlights the most frequently implemented features, as the collection of several data types and the areas on which companies are less ready, as the openness to the ecosystem, bringing out industrial needs and possible future research interests.
Zambetti, Michela; Adrodegari, F.; Pezzotta, Giuditta; Barbieri, C.; Pinto, Roberto; Saccani, N.
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