Leveraging Assets as a Service for Business Intelligence in Manufacturing Service Ecosystems

When manufacturers join forces to create, manage, and offer new Product-Services in globalized markets, a huge amount of inter-organizational data on tangible and intangible assets is generated in corporate knowledge bases. This data implies new economic opportunities as well as barriers. The presented approach depicts how e-business companies can benefit from virtualized assets - namely Assets as a Service - for Business Intelligence (BI) in Manufacturing Service Ecosystems (MSE). Thanks to Assets as a Service, more valuable, reliable, and structured data are available within the MSE, ready to be further evaluated, elaborated, or visualized. In this context, BI techniques can be used to automatically deduce implicit dependencies among assets. The purpose of this paper is to advance the understanding and adoption of BI practices in MSE by applying formal semantics also to collaboratively gather, monitor, and analyze shared data about production assets. Consequently, the findings of this work empower MSE members to take better decisions while managing Product-Service innovations in e-business scenarios, hence to create more value. Results are outlined through the example of an industrial scenario.