Migrating to a new PDM or PLM system is one of the most high-impact steps in your digital transformation journey.
Done right, it creates a clean, structured foundation for how your organization manages product data moving forward. Done poorly, it can introduce broken file relationships, lost data, and long-term inefficiencies that are difficult to undo.
If you’re planning a PDM migration or PLM migration, success isn’t just about moving data, it’s about preparing it, validating it, and ensuring it works in your new environment. Understanding how PDM and PLM work together before migration begins is what separates a clean cutover from a painful one.
Most organizations fall into one of a few common migration paths:
File Server → Vault
This is one of the most common starting points. Engineering data is stored in shared drives, often with inconsistent naming conventions, duplicate files, limited version control, and no enforced structure.
Moving to a system like Autodesk Vault introduces structure—but only if the data is properly cleaned and organized beforehand. Migrating a chaotic file server directly into Vault doesn’t fix the chaos; it just gives it a new home.
Legacy PDM → Vault
Organizations using older or outdated data management systems often migrate to modern platforms to improve performance, usability, and integration.
The challenge here is preserving:
Without careful planning, this critical context — the institutional memory of how products evolved — can be lost permanently. Once revision history is gone, it's gone.
On-Prem → Cloud (PLM)
As companies adopt cloud-based PLM solutions like Autodesk Fusion Manage, migration becomes less about files and more about structured data.
This often includes:
Cloud migrations require a strong understanding of how data will be used in the future — not just how it exists today. A BOM structure that worked in a legacy system may need to be restructured to support the connected workflows that make Fusion Manage's PLM capabilities valuable.
Migration issues are rarely caused by the tools, they’re caused by what’s being migrated. Here are the most common errors seen during data migration:
Poor Data Quality
Duplicate files, inconsistent naming, and missing metadata can carry over into the new system, limiting its effectiveness from day one. A study by IBM found that poor data quality costs U.S. businesses an estimated $3.1 trillion annually, and migration events are one of the highest-risk moments for data quality problems to compound.
Broken File Relationships
CAD assemblies, external references, and file dependencies can break if not properly mapped and validated during migration. A broken assembly reference doesn't always surface immediately — it often shows up weeks later when an engineer tries to open a model and half the components are missing.
Loss of Revision History
Without a structured migration strategy, version history and file lineage can be permanently lost — impacting traceability, compliance, and the ability to understand how a design evolved over time. For regulated industries, this isn't just inconvenient; it can be a compliance failure.
Scope Creep and Over-Migration
Attempting to migrate everything at once — including obsolete, archived, or irrelevant data — inflates complexity, increases risk, and degrades new system performance. Not everything that exists should move.
Lack of Testing and Validation
Skipping validation steps can result in data that looks correct in the new system but doesn't function properly in real workflows. Testing in a staging environment before cutover is not optional — it's what separates a successful migration from an expensive rollback.
A successful PLM migration starts well before any data is moved. The preparation phase is where migrations are won or lost.
Clean Your Data First
Migration is the perfect opportunity to eliminate duplicates, standardize naming conventions, and remove outdated files.
Audit File Relationships and Dependencies
Understanding how files connect—especially in CAD assemblies—is critical to preserving data integrity.
Define What Should (and Shouldn’t) Be Migrated
Not all data needs to move. Prioritizing active, relevant data helps reduce complexity and improve system performance.
Test Before Full Deployment
Pilot migrations and validation environments help identify issues early—before they impact production systems.
Plan for Post-Migration Optimization
Migration is not the finish line. After cutover, users will encounter edge cases, data issues, and workflow gaps that weren't visible during testing. A structured post-migration support plan — aligned with your broader PDM/PLM adoption program — is what turns a technically successful migration into a system people actually use.
Before starting a PDM migration or PLM migration, your team should be able to answer:
If the answer to any of these is unclear, it’s worth addressing before moving forward.
At Hagerman & Company, we approach PDM migration and PLM migration as a structured, risk-managed process.
Our Migration Services are designed to help organizations move data accurately, efficiently, and with minimal disruption. This includes reviewing your current systems, planning and testing migrations, validating system performance, and supporting upgrades across environments.
Our migration process covers:
The result is a migration that doesn’t just move data, but improves it. Connect with us today to learn more!