Data migration is where implementation projects most often go wrong, but the businesses that avoid disaster tend to follow the same sequence, regardless of what system they’re moving to or from.
Audit Before You Move Anything
Understand what's actually in the source system — duplicate records, unused fields, inconsistent formats — before deciding what to migrate. Migrating everything by default just moves the mess.
Map Fields Explicitly, Don't Assume
A field called "Status" in the old system rarely maps cleanly to a field with the same name in the new one — explicit field-by-field mapping, reviewed by someone who understands both systems, catches mismatches before they cause data loss.
Migrate to a Staging Environment First
Running the migration into a test environment first lets you validate the results against the source data without any risk to the live system — problems get caught before they matter.
Schedule the Cutover for Low-Activity Hours
Even a well-tested migration benefits from happening during the business's quietest window, minimizing how many people are affected if anything takes longer than planned.
Keep the Old System Read-Only, Not Deleted
Keeping the previous system accessible in read-only mode for a defined period after cutover gives a safety net for anything the migration missed, without the risk of new data being entered in two places at once.
Frequently Asked Questions
How far in advance should migration be planned?
For anything beyond a small dataset, planning should start 3–4 weeks before the target cutover date, with the audit phase starting even earlier.
What happens if we find data problems mid-migration?
This is common enough that migration plans should build in buffer time for exactly this — finding issues mid-process is far better than finding them after cutover.