Why so many ERP migrations fail in production

A migration plan can separate scoping, development, testing and cutover. This becomes risky when the first confrontation with real data is postponed until acceptance: discrepancies are then discovered with little time left to address them.

A migration isn’t finished when the code is written. It’s finished when it has been stabilized through execution.

Examine the sources as well as the target

The target model, its interfaces and its configuration need verification. The state of the source data deserves the same attention, particularly:

• incomplete or outdated documentation;
• implicit business rules, never written down, sometimes contradictory;
• years of history with exceptions that were never handled;
• real volumes far above the estimates.

A specification can document these difficulties. Extraction and checks on real data establish their scope and help identify cases that the documentation omits.

Five risks to examine in the plan

These risks can combine. Their presence and significance need to be assessed for the project:

1. The sacrificed audit. The project starts on assumptions because the data audit was reduced to a documentation review. Nobody ever measured the real scope.
2. Migration treated as a technical sub-project. Scheduled after configuration and development, it can inherit their delays and leave too little time for data qualification or business decisions.
3. Tests run on convenient samples. For example, five hundred clean parts can pass acceptance without testing the duplicates and historical exceptions in a scope of two million records.
4. The tunnel effect of the plan. If each phase waits for the previous one to finish, delays can reduce the time available for rehearsals and corrections.
5. A chain that can’t absorb corrections. Without checkpoints or error isolation, one blocking record can require an entire batch to be replayed. Plan error tracking and replay with scripts or a platform, then measure recovery time.

The real risk: discovering it too late

Discrepancies can remain despite the controls. Discovering them in production adds a constraint: they must be corrected while operations already depend on the target and rollback options may be reduced.

The longer you postpone the confrontation with real data, the more uncertainty remains at go-live. Public reports describe ERP programme disruption and costs, but do not establish that data migration alone caused every loss.

Flipping the logic

The alternative is to execute early, on real scopes, and to correct in a loop. Each run becomes a source of learning: it reveals edge cases, surfaces the implicit rules, and allows for gradual stabilization.

That is the principle behind the Run / Fix loops of our methodology: the migration system executes scope after scope, every discrepancy is analyzed, corrected, replayed. Reliability is built iteration after iteration, long before cutover.

Evidence to gather before Go-Live

This evidence supports the cutover decision without guaranteeing an incident-free launch:

• the scope was measured on real data, not estimated in a workshop;
• complete rehearsals are planned and executed on the real scope, with reconciled values and business processes;
• every reject is located and qualified, with a recovery mechanism that accounts for its dependencies;
• a dry run at real volume has validated the chain end to end.

The control results, remaining discrepancies and rollback plan let the responsible teams decide whether cutover is acceptable. For the full picture (scope, cutover approaches, costs), see our ERP data migration guide.

The aim is to make risks measurable and decisions explicit before production cutover.