Product lifecycle management as a data challenge
Product lifecycle management (PLM) spans the full breadth of a manufacturing business. To manage product data from development through to delivery and service, the data has to flow reliably across engineering, sales, sourcing, logistics, and services. Without clear governance, product data was scattered across systems with conflicting definitions, slowing processes.
For this global energy manufacturer, building data-driven processes and automation across this entire scope was the challenge.
From data definitions to data products
Making data work end-to-end across PLM starts with getting the foundations right. Norrin led data definitions and concepting work, establishing clear definitions of critical product data, such as product specifications and performance standards, and how they should be understood across the organization. Data process modeling and data flow mapping followed, creating a clear picture of how information should move between systems and business functions.
From those foundations, Norrin helped to create data products that could be used across business units. Data development roadmaps were planned and maintained to keep the work structured and progressing.
This approach advanced the organization's ability to automate integrations and run data-driven processes end-to-end creating an AI-ready foundation for future growth.
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