In today’s world, quality information is often siloed, with a focus on detection rather than prevention and early warnings disconnected from resolution processes.
Companies struggle to share and merge data across the value chain due to fragmented tools and platforms, and face limitations in applying intelligent technologies.
The consequences include high recall costs, low customer satisfaction, delayed innovation, and loss of competitive advantage.
Early detection and timely response to quality issues is enabled through consolidated data, machine learning, workflow automation, and predictive analytics.
Seamless data exchange between companies allows for joint investigations, shared monitoring, standard containment measures, and collaborative root cause analysis, supporting both preventative action and effective problem resolution.
The Collaborative QM Vision for Data Exchange involves continuous sharing of defect information across different tiers (OEM, Tier 1, and Tier 2) whenever issues are detected through early warning or predictive features.
When a quality issue is identified at any level, the information is exchanged upstream or downstream to enable joint root cause analysis and collaborative resolution, supported by both continuous and issue-based data sharing between the involved parties.
SAP Collaborative Quality Management enables organizations to work together across the supply chain to prevent, detect, and resolve quality issues. By consolidating data from multiple systems, providing advanced reporting and monitoring, and leveraging machine learning, it helps identify emerging problems early.
Utilizing SAP Datasphere and SAP Analytics Cloud, the solution allows defects to be detected up to 10 weeks sooner, reduces warranty claims by up to 25%, lowers financial accruals for recalls by up to 20%, and can save the equivalent of one full-time employee through process efficiencies.
SAP Collaborative Quality Management relies on two core components: SAP Datasphere for managing and integrating data, and SAP Analytics Cloud for advanced analytics and reporting.
Additional functionality can be extended with optional service components like SAP Business Network Material Traceability for supply chain transparency and SAP Integration Suite for connecting various systems.
SAP Early Warning supports efficient data management and exchange by consolidating quality data from various internal sources for unified reporting, enabling easy access to supplier data through a data marketplace, and simplifying the process of generating Catena-X compliant data offers for suppliers using an intuitive data sharing cockpit.
SAP Early Warning enables users to monitor quality data through customizable dashboards, leverage pre-built dashboards for quick insights, and perform advanced statistical analyses using integrated tools such as the R interface for tasks like Weibull distribution modeling.
Early supplier involvement enables error detection up to four months sooner and speeds up root cause analysis. Collaborative field monitoring combines real-time production and test data, improving anomaly identification and drastically reducing the number of affected vehicles.
Linking field and supplier data accelerates root cause identification, cutting down the impacted units from millions to just a few thousand. Advanced hypothesis verification and faster analysis with specialized quality tools lead to significant cost avoidance.
Time efficacy is improved as new data enables much quicker evaluation and implementation of corrective actions, allowing for earlier resolution compared to traditional methods.
Catena-X certified components enable secure data exchange using either SAP EDC (for SAP-based suppliers), a direct connection through Datasphere, or FOSS EDC (for non-SAP suppliers).
Core elements include SAP Analytics Cloud, Datasphere, Integration Suite, S/4HANA, and data lakes, supporting connectivity and collaboration across heterogeneous systems.