How Long Does a SaaS Migration Actually Take?

"A few weeks" is the answer almost everyone gives before a migration starts. The honest range is days for a five-person team and up to a year and a half for a large enterprise — and the phase most estimates skip almost entirely is the one that tends to eat the most time.

Why "a few weeks" is almost never the real answer

Migration timelines get underestimated for a predictable reason: the estimate usually comes from whoever is selling the new tool, and it's built around the parts of the process they control — account setup, initial configuration, a training session. It doesn't include the parts they don't control: cleaning up the data you're bringing over, testing that nothing broke, and the stretch after go-live where people quietly keep using the old tool because the new one doesn't feel finished yet. Our hidden-costs framework covers what that gap costs in dollars. This one is about what it costs in time.

The phases, and where the time actually goes

Underneath the specifics, most software migrations — from a small team switching project-management tools to a large enterprise replacing its ERP — move through the same six phases: discovery, design, build and data migration, testing, go-live, and stabilization. What varies enormously is how long each phase takes, and for large organizations, industry reporting puts the median enterprise software project at roughly nine months end to end.

The phase most estimates get wrong: data cleansing

Of the six phases, one consistently consumes more time than planners expect: cleaning the data before it moves. Duplicate records, inconsistent formatting, and missing fields don't cause visible problems in the old tool — they've usually been quietly worked around for years. A migration forces them into the open, because the new system won't accept them the way the old one silently did.

The practical implication: if nobody has audited the data quality in the source system before the migration timeline gets set, the timeline is a guess. Identifying data exceptions before attempting to load them — rather than discovering them mid-migration — is consistently the difference between a project that runs long by weeks and one that runs long by quarters.

What determines whether you're closer to 4 weeks or 18 months

• Data volume and cleanliness — the single biggest swing factor, and the hardest to estimate without actually looking.
• Number of downstream integrations — every other tool that reads from or writes to the one you're replacing adds its own testing surface.
• Change management, not just technical migration — organizations that underinvest in training and internal communication tend to add 30–50% to their baseline technical schedule, because adoption lags the technical cutover.
• Whether there's a parallel-run period — running both tools simultaneously before fully cutting over adds calendar time but meaningfully reduces the risk of a hard failure at go-live.

Building migration time into your break-even math

A longer migration isn't just a scheduling inconvenience — it's a direct cost, in the specific sense our calculator is built to price: every week you're running both tools in parallel, or paying staff to do double data entry, or delaying the productivity gain the new tool was supposed to deliver, is a week where the switch is getting more expensive before it's paid for anything. A realistic migration-hours estimate belongs in that math from the start, not as a correction after the timeline has already slipped.

Bottom line

Migration timelines scale with organization size, but not smoothly, and the phase that decides whether you land at the short end or the long end — data cleansing — is rarely the one anyone estimates first. Audit the data before you set the date.