Data spaces in manufacturing: An essential component for data-driven businesses

In manufacturing, data spaces refer to shared, secure environments where organizations can store, share, and analyze data across different stakeholders, such as the suppliers, manufacturers, and customers. These spaces facilitate collaboration, improve data interoperability, and enhance decision-making in manufacturing processes.

In Germany, several publicly driven initiatives have been set up to develop industry-specific data spaces such as Factory-X for the machinery and plant industry. The idea behind Factory-X is to promote the digital transformation and networking of the industry. Besides Atos, other software vendors and service providers such as Siemens and SAP, and even machinery manufacturers like DMG Mori or Trumpf are involved in Factory-X.

The increasing demand for data-driven insights and collaborative ecosystems is nudging companies to build their own data spaces. For example, disrupted supply chains have increased the need for end-to-end transparency and flexibility, necessitating secure data shared with other stakeholders in the ecosystem such as the suppliers, the manufacturers, and the customers.

Another key driver for data space adoption is the growing need for data analytics which, in turn, generates valid analysis and insights to improve company performance.

Data spaces need to address various demands to be successfully adopted by manufacturing companies. They must be able to integrate data from various sources, machines, and systems, including ERP, manufacturing execution systems (MES), and IoT devices. The use of standardized data formats and communication protocols is also key. They need to be flexible to match pace with the growth of the organization and the rising data volumes.

The integration of new data sources, analytics tools, and emerging technologies without significant disruption is another key requirement, as is the provision of capabilities for real-time data analysis supporting timely decision-making and operational adjustments. The analytics results need to be displayed in easy-to-use dashboards and reports.

Data governance and management also play important roles. The integration of various internal and external stakeholders necessitates thorough security concepts and solutions.

Enhancing collaboration, data sharing, and decision-making

Data spaces in manufacturing create shared environments that enable organizations to store, share and analyze data collaboratively. Therefore, data spaces support the realization of major manufacturing use cases. Here are some examples:

• Predictive maintenance: Aggregate data from machinery, equipment sensors, and maintenance logs to predict equipment failures and schedule maintenance activities.
• Quality management and assurance: Collect and analyze quality control data from various production sites to identify trends, defects, and areas for improvement.
• Collaborative product development: Facilitate collaboration across design, engineering, and production teams by sharing data related to product specifications, prototypes, and testing results.
• Enhanced customer interactions and service: Share data with customers regarding order status, product specifications, and warranty information through a collaborative data space
• Supply chain visibility and optimization: Enablement of real-time tracking of materials, components, and products throughout the supply chain.

The application of data spaces is not limited to manufacturing. Other industries that are applying data spaces are logistics and transportation and energy and utilities.

Faster knowledge sharing. Faster decisions.

Data spaces are instrumental in creating a connected enterprise — a major prerequisite for Industry 4.0 and digital transformation. And they are doing so by facilitating seamless data exchange between internal and external stakeholders. This adoption by manufacturing companies will be beneficial in several ways:

• Data spaces facilitate collaboration among different parties in the supply chain enabling seamless data sharing.
• Stakeholders can access a centralized repository of data, leading to better communication and alignment of objectives.
• They support data integration from multiple sources, including IoT devices, MES, and ERP systems, ensuring a holistic view of operations.
• By utilizing standardized data models and protocols, these spaces enhance data interoperability, making it easier to share and analyze information.
• They provide real-time access to operational data, allowing manufacturers to monitor processes, detect issues, and make informed decisions quickly.
• Access to comprehensive data allows for better strategic planning and operational decision-making based on reliable information.
• They facilitate knowledge sharing across the organization, empowering employees with access to critical information and improving overall performance.

Boosting data space adoption

Collaborative ecosystems in manufacturing (where multiple stakeholders work together) will enhance the need for shared data environments.

Companies have understood that data will drive their business in the future, not just to improve operational excellence but to create new business opportunities. The access and opportunity to analyze and contextualize data is important to improve decision making in quickly changing markets.

Apart from business-driven factors that foster data spaces, technological progress will also influence data spaces of the future.