Manufacturing industries are on the verge of a data-driven revolution. In the near future, they will collaborate in hyperconnected value networks employing a large variety of data‑and‑analytics applications. Data will be the lifeblood of these applications, driving productivity, new customer experiences and ensuring a positive impact on society and the environment. While companies can implement many applications using only internal data, they can rarely unlock the full opportunity alone. More sophisticated applications often require the exchange of data beyond company boundaries to effectively train artificial intelligence algorithms and to support collaboration in complex networks that require full transparency. Consequently, data sharing is a key enabler of multiple advanced data‑driven applications in manufacturing.

However, there are challenges the industry alone cannot address. Success will only happen if all stakeholders in production ecosystems come together and continue to solve important organizational and technological challenges.

Shedding light on these issues, this project can help manufacturers collectively make the best of their collective data and build successful data ecosystems in manufacturing through a community-driven tool to overcome barriers and achieve excellence, the Manufacturing Data Excellence framework. Drawing learnings from successful, value-adding data-collaborations, this framework will lay out prerequisites and principles for data sharing excellence, help companies assess their readiness and highlight key priorities to achieve the next maturity levels. The community may share best-practices and embark on a cross-industry learning journey along the dimensions of the framework, but also incubate new collaborations around common areas of interest to support a journey towards globally connected manufacturing data ecosystems. 

Organizations may chose to engage in this initiative by:

• Sharing leading use cases of successful applications to be captured in upcoming publications


• Contributing to the co-development of the framework by sharing knowledge and best practices


• Testing and applying the framework and being part of a cross-industry learning journey

To learn more and engage in this project, please contact memia.fendri@weforum.org