Your CTO greenlights the switch from one CRM to another. Engineering writes a migration script. It runs over a weekend. Records transfer. Someone spot-checks a few contacts in the new system, confirms they look right, and the team declares the migration complete.
Except it isn’t. The script handled historical records, but your sales team is still logging calls in the old system because nobody retrained them yet. Marketing has campaigns that write back to the old CRM. A few automations nobody documented are still pushing data into the original tool. For the next four to eight weeks, both systems are live, and records are diverging by the hour.
This is the parallel system problem. It’s where most migrations actually fail, and almost nobody plans for it.
Why Every Data Migration Produces a Parallel System Period
I’ve seen teams try to avoid the parallel period entirely. The plan is always the same: hard cutover on a Friday, everyone uses the new system Monday morning. In my experience, this works about 20% of the time, and only for teams under ten people.
The reason is behavioral, not technical. People don’t switch habits on command. The sales rep who’s lived in Salesforce for three years will keep opening Salesforce on autopilot for weeks after you move to HubSpot. The marketing team will keep using their existing email sequences until someone rebuilds them in the new platform. Third-party tools with API integrations pointing at the old system don’t magically re-point themselves.
So you end up with two systems both receiving real data. This isn’t a failure of planning. It’s just how migrations work in organizations with more than a handful of people.
Some teams acknowledge this and build a transition plan around it. Most don’t. They plan for the migration event and assume adoption happens immediately after.
Records Diverge Faster Than You Think
Here’s what the parallel period actually looks like in practice.
Day one after migration: everything looks fine. The new system has all historical records. The old system is “frozen.” You pat yourself on the back.
Day three: a sales rep updates a phone number in the old CRM because their browser auto-completed to the old URL. A marketing automation fires and creates a new contact in the old system from a form submission you forgot to redirect. A Zapier workflow nobody remembers building pushes a Stripe event to the old CRM’s custom field.
Day ten: you have 200+ records that exist in the old system but not the new one, 50 records with conflicting field values, and a growing sense of dread about which system has the “real” data.
The math works against you here. Even if 95% of your team adopts the new tool immediately, the 5% who don’t are generating data mutations in the old system every single day. Over four weeks, that compounds into something ugly. I’ve seen companies run a second migration script at the end of the transition period to “catch up,” only to discover that 12% of their records had conflicts requiring manual review.
And this problem gets worse with every additional tool involved. If you’re migrating a CRM, you’re probably also migrating the integrations connected to it. Support tickets, billing data, marketing automation. Each one is another source of parallel writes.
Plan Your Data Migration Around the Overlap
The conventional advice is to plan your migration in phases: assess, map, migrate, validate. Fine as far as it goes, but it treats migration as a point-in-time event with a clean before and after. A more honest framework adds a fifth phase: the parallel period.
During the parallel period, you need three things:
- A source of truth declaration. Pick which system is authoritative and communicate it clearly. “As of March 1, HubSpot is the source of truth for contact records. If it’s not in HubSpot, it doesn’t exist.” This won’t prevent people from using the old system, but it gives you a tiebreaker when records conflict.
- A sync mechanism that runs continuously. Your migration script got records from A to B once. Now you need changes in A to flow to B on an ongoing basis until the old system is fully decommissioned. This is the part most teams skip entirely.
- A kill date for the old system. Without a hard deadline, parallel systems run forever. I’ve worked with companies still paying for both CRMs eighteen months after the “migration” because “some people still use it for a few things.”
The sync mechanism deserves more attention than it usually gets. A one-time script won’t help during the parallel period because new data is being created and existing data is being modified in the old system continuously. You need something that watches for changes and propagates them.
Some teams build this themselves. A cron job that queries the old system’s API for recently modified records and pushes them to the new one. It works until you hit rate limits, miss a deleted record, or discover that the old system’s “modified date” field doesn’t update on related record changes. I’ve seen teams spend more engineering time maintaining their parallel sync than they spent on the original migration.
The better approach is purpose-built data migration tooling that handles both the initial backfill and the ongoing sync in a single configuration. You set up the migration once, it transfers everything, and then it keeps running on a schedule until you’re ready to cut over completely. The migration becomes ongoing sync without any additional work.
What Your Migration Checklist Is Probably Missing
Most checklists focus on the technical transfer: field mapping, data type conversion, ID reconciliation. Those matter, but the items that actually derail migrations are organizational.
- Audit your inbound data flows before migrating. Every form, webhook, API integration, and automation that writes to the old system needs to be cataloged and redirected. The ones you miss will create phantom records in the old system during the parallel period.
- Freeze automations in the old system. If you can’t decommission it immediately, at least disable automated writes. Turn off drip campaigns, pause workflow automations, disable webhook receivers. The old system should become read-only as quickly as possible.
- Plan for a longer parallel period than you expect. If you think the transition will take two weeks, budget for six. If you think four weeks, budget for eight. Every migration I’ve been part of has taken longer than planned. External integrations are the usual culprit, because third-party vendors don’t move on your timeline.
- Track adoption, not just record counts. The migration is done when nobody uses the old system anymore, not when all records exist in the new one. Monitor login frequency on the old platform. If it’s not trending toward zero, you have a people problem, not a data problem.
The temptation is to treat migration as a technical project that ends when the data lands in the new system. In practice, it’s a change management project that ends when the old system gets turned off. The gap between those two moments is where most of the actual work happens, and where most of the data quality problems come from. If you only plan for the script, you’re planning for maybe 30% of the real effort.