Unlocking Value in Manufacturing through Data Sharing

Manufacturing industries are on the verge of a data-driven revolution. They collaborate in hyperconnected value networks employing a large variety of data‑and‑analytics applications. Data is 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 increased 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 only happens when all stakeholders in production ecosystems come together and continue to solve important organizational and technological challenges.

Shedding light on these issues, this project aims to help manufacturers collectively make the best of their collective data and build successful data ecosystems in manufacturing. To do so, the community has developed tool to map out 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 leverages this framework and ongoing community discussions to embark on a cross-industry learning journey, 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 best practices and success stories for data collaborations, demonstrating achieved impact in productivity, customer experience and the environment

  • Applying the Manufacturing Data Excellence Framework by performing a maturity self-assessment and providing continuous feedback to retain its relevance in the ever-evolving manufacturing operations

  • Contributing in the development of new pilot collaborations together with community peers

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Further reading

Manufacturing and Value Chains

制造业未来将由数据和分析驱原因如下

在制造业中有效地使用数据可以使企业更可持更有效益但只有39%制造业高管表他们成功将数据驱动的应用扩展至单一产品生产过程之世界经济论坛制造业数据卓越框为该行业开发分析新能力和新型伙伴关系提供了指南为制造商提供了获取数据更大价值参照手册

13 Oct 2022

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