Salesforce data migration sounds simple: move data from System A to Salesforce, test it, and go live.
But in practice? It’s one of the riskiest parts of a Salesforce project. Migrate too fast, and you risk breaking mission-critical workflows. Migrate too cautiously, and you burn through timelines and budgets.
Beyond duplicates and field mismatches, real-world migrations surface less obvious challenges that often go unnoticed until it’s too late. Let’s go deeper into the seven challenges that can derail a Salesforce migration—and the strategies that actually work.
Poor Data Quality Goes Beyond Duplicates
Most blogs will tell you to “deduplicate your records.” But poor data quality runs deeper:
- Hidden formatting errors: Dates stored as free text (“12/5/2025” vs “05-12-25”).
- Inconsistent picklists: “USA” in one system, “United States” in another.
- Ghost records: Leads with no associated activity history.
Solution: Create a data profiling matrix that checks not just for duplicates, but for:
- Null values in required fields.
- Inconsistent field formats.
- Records with broken parent-child relationships.
Complex Data Mapping Isn’t Just Fields—It’s Relationships
Mapping “Name → Name” is easy. The hard part? Migrating relationships:
- One Account linked to multiple Contacts.
- Opportunities linked to custom objects.
- Historical activity tied to now-deleted records.
Solution:
- Document all lookup and master-detail relationships before migration.
- Use unique identifiers (like external IDs) to re-establish links post-migration.
- In sandboxes, simulate a “full load” to catch orphaned records.
Large Data Volumes Hit Invisible Limits
Salesforce imposes API and storage limits that many migration projects overlook. A migration of just 2–3 million records can hit governor limits quickly.
Solution:
- Use Bulk API with parallel mode for high volume.
- Stagger jobs to respect daily API limits.
- Monitor logs for “partial successes,” not just failures—many records fail silently.
Field Mismatches Break Automations
It’s not just that fields don’t align—it’s that automations break when migrated data doesn’t match expected formats.
- A workflow expecting a 10-digit phone number breaks when legacy data includes country codes.
- Validation rules reject migrated records because required fields weren’t populated historically.
Solution:
- Audit active validation rules, triggers, and flows before migration.
- Either disable them during migration or adjust legacy data to comply.
- After migration, re-enable and run regression tests.
Downtime Isn’t Just About Access—It’s About Sync Drift
Migration downtime isn’t always “no access.” The real risk is sync drift: while you’re migrating, users keep adding records in the legacy system, creating discrepancies.
Solution:
- Freeze legacy system input during final cutover.
- Or run delta migrations (initial bulk load + incremental syncs).
- Confirm record counts match post-cutover.
Security and Compliance Requires Audit Trails
It’s not enough to encrypt data. Auditors want traceability:
- Who moved the data?
- Was it transformed during migration?
- Can you prove no sensitive data was lost?
Solution:
- Maintain data migration logs (source ID, target ID, timestamp, user).
- For sensitive industries (finance, healthcare), generate audit reports before and after cutover.
- Store sanitized backups for compliance purposes.
Testing and Validation Goes Beyond Record Counts
Most teams stop at “10,000 contacts in → 10,000 contacts out.” But raw counts don’t reveal broken logic.
What to test:
- Parent-child relationships (Accounts → Contacts → Opportunities).
- Historical activities (emails, calls, cases).
- Reports and dashboards built on migrated data.
- Permission-based visibility (does Sales see only their own Opportunities?).
Solution:
- Define business-driven test cases (e.g., “Can a Sales Manager pull a quarterly pipeline report after migration?”).
- Run both system-level and user-level tests.
Beyond the Basics: Hidden Challenges Few Discuss
Here are bonus issues migration veterans encounter but few blogs mention:
- Automation collisions: Old workflows fire unexpectedly during migration, flooding users with emails.
- Picklist dependencies: Migrating picklist values without migrating their dependencies breaks records.
- Time zones: Date/time fields can shift when moving across systems with different default time zones.
Best Practices for Resilient Migrations
- Always back up legacy data before touching it.
- Run at least two dry runs in sandbox before production.
- Involve end-users in UAT—they’ll spot issues no script can.
- Document mappings, transformations, and decisions for future admins.
Conclusion
Salesforce data migration isn’t just about moving records—it’s about preserving trust in data. By planning for hidden challenges like API limits, automation conflicts, and compliance audits, you can avoid costly mistakes and build a Salesforce org users actually want to work with.
And while many teams handle migrations in-house, organizations sometimes turn to experienced Salesforce partners—such as 360 Degree Cloud—who bring structured frameworks for field mapping, relationship management, and validation.
💬_ Have you run into an unexpected Salesforce migration challenge? Share your story—I’d love to hear what caught you off guard._
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