ATS data migration is the move of candidates, applications, requisitions, notes, attachments and hiring history from an old recruiting system into a new one. The work is mostly decisions rather than transfer: what genuinely needs to move, how fields map between two different data models, and how the switchover gets tested.
Move what you will use, and archive the rest. Active requisitions, candidates sitting in live pipelines, and the talent pool you actually search are worth carrying across. Decade-old applications to roles that no longer exist are not, and importing them makes search worse rather than better while inflating whatever you pay per record in a new [applicant tracking system](/ats). A common split is to migrate candidates with activity in a recent window plus anyone flagged as a silver medallist or a hire, then export everything else to a stored archive that satisfies record-keeping obligations without cluttering daily work. Retention rules vary by country, sector and sometimes employer size, so agree the archive period with whoever owns data protection internally and confirm it with qualified counsel rather than choosing a number that merely feels reasonable.
Someone builds a document listing every field in the old system, its destination in the new one, and the transformation needed to get there. That sounds mechanical and is where most of the effort goes, because two products rarely model hiring identically. Stage names differ and seldom line up one to one. Custom fields added over years may have no home at all. Free-text values need to become picklist options, or the picklist needs new entries. Source labels accumulate variants of the same channel that ought to be consolidated on the way in. This is also the moment to clean rather than faithfully reproduce, since duplicate records, dead email addresses and abandoned tags are much cheaper to fix during mapping than after go-live. Expect the map to change once you see real data in a test load, and keep it versioned.
A test load takes a representative sample, not the easy records, and pushes it into a staging copy of the new system so you can inspect what arrived. Check counts first, then open individual records and compare them against the source. Are dates right, did attachments come through, did notes keep their authors, are stage histories intact. Fix the mapping and load again. Two or three rounds is normal. Cutover is the switch itself, usually run over a quiet period with the old system set to read-only so nothing gets created in two places. Plan the sequence in advance: final export, load, verification, then opening access. Keep the old system readable for a while afterwards, since something always turns out to be missing, and pair the move with a proper [ATS implementation plan](/ats-implementation) covering training and process change.
Attachments and history are the classic casualties. Resumes fail to transfer or land unattached to the right person. Interview notes arrive stripped of their authors and timestamps, which makes them useless as evidence later. Duplicates multiply, because an import bypasses the matching that normally runs at application time. Stage mappings collapse several distinct stages into one and destroy the ability to compare funnel data across the switch. Email threads generally do not migrate at all. Beyond the data itself, the recurring failure is treating migration as a technical task handed to a vendor while the recruiting team carries on as though nothing is changing. Somebody internal has to own the decisions, verify the loads and accept the result. Budget time for that person, and expect reporting continuity across old and new systems to need manual reconciliation.
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