Caroline is a content marketing specialist on the content excellence team out of Boston, MA. Her writing supports the IoT, augmented reality, and PLM technologies at PTC.
From fragmented product data to global PLM: lessons from a MedTech digital transformation
Most MedTech organizations don’t struggle with tools alone. They struggle with fragmented product data spread across disconnected systems, spreadsheets, and document-heavy processes that were never designed to scale.
For organizations still relying on Oracle Agile or other legacy PLM environments, these challenges are becoming increasingly difficult to overcome as product complexity, regulatory expectations, and global collaboration demands continue to grow.
One leading MedTech manufacturer faced this challenge firsthand. Operating across 44 global manufacturing sites and multiple engineering centers, they relied on a mix of local systems, paper-based workflows, and disconnected processes. Product data lived in different tools, documents, and spreadsheets, making even small changes slow and difficult to manage.
Engineering, manufacturing, and regulatory teams worked effectively within their own domains, but aligning across functions required significant manual effort. Important information was frequently duplicated, reinterpreted, or recreated at different stages of the lifecycle.
As product complexity, regulatory demands, and workforce pressures increased, the company recognized that modernization required more than new tools. It needed a connected, scalable way to structure and use product data across the business.
Instead of replacing systems all at once, leadership focused on a more fundamental shift: creating a global, scalable approach to managing product lifecycle data.
Starting with the fundamentals
The transformation began by digitizing core workflows and creating a consistent global approach to product lifecycle data that could both deliver immediate value and establish a global foundation.
Early efforts centered on digitizing and standardizing core processes:
- Transitioning from paper-based workflows to digital document management
- Introducing electronic approvals and digital signatures
- Enabling shared access to product information across global engineering teams
- Integrating core engineering systems, including mechanical CAD, into a central PLM environment
These changes reduced regulatory submission effort, improved first-time-right manufacturing, and enabled a 76% reduction in change cycle time. Just as importantly, teams gained greater visibility and consistency across regions, reducing reliance on local workarounds.
Shifting to a product-centric approach
The next shift moved teams beyond document-centric processes toward a structured, product-centric model where teams could define products through components, relationships, and configurations rather than relying solely on files.
This shift made it easier to:
- Define and manage product structures more consistently
- Improve configuration management and change tracking
- Reduce duplication and manual interpretation of documents
Over time, this evolved into a more complete representation of product data, spanning physical structures, system definitions, and device behavior.
With structured product data in place, collaboration became more scalable. Teams no longer had to reinterpret information at each stage, making decisions faster and more reliable.
Strengthening engineering and manufacturing alignment
Engineering and manufacturing alignment became one of the highest-value use cases. Historically, these functions operated with different views of the product.
To address this, the organization introduced structured definitions of product data for both engineering and manufacturing:
- Engineering Bill of Materials (EBOM) for design intent
- Manufacturing Bill of Materials (MBOM) aligned to production requirements
Connecting these views allowed teams to collaborate earlier in the development process, aligning manufacturability and cost before issues surfaced downstream.
From there, the company expanded into Manufacturing Process Management (MPM), focusing not just on what to build, but on how to build it. This enabled:
- Global standardization of manufacturing processes
- Flexibility to adapt processes locally across different facilities
- More efficient implementation of changes without reworking entire documentation sets
Together, these changes improved execution, reduced errors, and made it easier to manage a global manufacturing network.
Extending value across the lifecycle
With a strong foundation in place, the next step was extending structured product data across the lifecycle by connecting engineering, manufacturing, regulatory, and service information.
Regulatory visibility was a key focus. Teams required a clearer picture of which product configurations were approved in different markets and how product data supported regulatory submissions. Because much of that documentation was derived from product, better organization and traceability reduced regulatory preparation effort and helped decrease approved lead times by 10 days.
Build regulatory readiness into connected product data
See how MedTech teams can manage complexity with a connected lifecycle approach.
Explore Regulatory ReadinessAt the same time, the business began leveraging data from manufacturing and service more systematically.
With hundreds of thousands of connected devices in the field, new opportunities emerged to capture and analyze real-world usage data. This made it possible to:
- Identify recurring issues earlier
- Improve component reliability
- Incorporate service insights into product design decisions
- Move toward more predictive and preventive service models
These feedback loops created a more continuous, data-driven lifecycle, improving product reliability, enabling earlier issue detection, and reducing the cost and time required to resolve problems across the installed base.
Laying the foundation for a Digital Twin and smart manufacturing
As digital capabilities matured, the organization moved toward a more comprehensive digital representation of its products.
By combining structured product, manufacturing, and lifecycle data, the organization established the foundation for a digital twin, providing a consistent, end-to-end view of every product. This made it easier to simulate performance, validate designs earlier, and reduce risk before physical changes were introduced.
In parallel, efforts expanded into smart manufacturing initiatives, including:
- Connecting manufacturing processes with execution systems
- Enhancing visibility into factory operations
- Exploring automation to reduce reliance on manual intervention
- Improving efficiency and minimizing unplanned disruptions
Driving adoption across the organization
Technology was only part of the transformation. Executive sponsorship, domain expertise, targeted rollouts, and close collaboration with users helped turn PLM modernization into an operating model change.
By focusing on practical improvements and engaging teams early, the organization created momentum that supported broader adoption across the business.
What this means for MedTech leaders
Across the MedTech industry, organizations are rethinking how they manage product data as regulatory demands, product complexity, and global collaboration continue to increase.
Modern PLM is no longer just about managing documents or consolidating legacy systems. It’s about creating a connected, structured foundation for product data that supports the full lifecycle.
This enables:
- Stronger alignment between engineering and manufacturing
- More consistent management of product changes
- Improved visibility into product configurations across global markets
- Better support for regulatory compliance and quality processes
- Continuous improvement through lifecycle feedback loops
When product data remains fragmented or overly document-driven, the impact goes beyond inefficiency. It becomes harder to scale, manage complexity, and keep pace with changing market and regulatory demands.
A different path to modernization
One of the most important takeaways from this journey is how the transformation unfolded. Rather than attempting a large-scale overhaul, the organization progressed in phases:
- Establishing foundational digital capabilities
- Transitioning to structured, product-centric data
- Aligning engineering and manufacturing through shared models
- Expanding into lifecycle insights, service integration, and continuous improvement
This step-by-step approach enabled the business to modernize without disrupting critical operations while building a platform that continues to evolve.
For MedTech leaders, the takeaway is clear: the ability to scale, innovate, and remain compliant increasingly depends on how effectively product data is structured, connected, and leveraged across the lifecycle.
For organizations evaluating their next step beyond Oracle Agile, this journey demonstrates that successful modernization isn’t about replacing one system with another, it’s about creating a connected foundation for product data that can scale with the business.
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