Why so many ERP migrations fail in production
Most migration projects are planned as a straight line: you scope, you build, you test, you switch over. On paper, it’s reassuring. In industrial ERP and PLM environments, that is precisely what makes them fail.
A migration isn’t finished when the code is written. It’s finished when it has been stabilized through execution.
The problem isn’t the target system
When a migration blows up at the end of a project, the instinct is to blame the target tool. In reality, the target system is rarely at fault. It’s the source data that holds the surprises:
- incomplete or outdated documentation;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.
None of this shows up in a specification. It only appears at execution time, on real data.
The real risk: discovering it too late
The danger isn’t that discrepancies exist. There will always be some. The danger is discovering them in production, when there’s no room left to correct them and the cost of an error is at its highest.
The longer you postpone the confrontation with real data, the more invisible debt you accumulate. And that debt is paid in full on Go-Live day.
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.
Going live is then no longer a leap into the void. It’s the last in a long series of executions that have already been mastered.
Complexity doesn’t disappear for all that. But it stops being something you endure: it gets mastered.