ERP Data Migration Effort Calculator
Data migration is where mid-market ERP projects most often overrun. This calculator makes the effort visible by counting the records to correct, the open documents to validate and the mock loads needed before cutover.
Your numbers
Open sales orders, purchase orders, work orders, open invoices.
From a profiling run of the legacy data.
Load, reconcile, defect triage and reload.
Your results
Planning estimate. Excludes extraction and transformation programming, which depends on the source system. Use real profiling results for the defect rate.
Total migration hours vs defect rate
Sweeps Records needing correction from 0 to 60, holding your other inputs fixed.
Optional data profiling review
We can outline a profiling approach for your legacy data and tell you which checks give the best defect estimate. No obligation.
Optional. The tool and every export work without this. No spam.
How to use it
Profile the legacy system first: count items, customers, suppliers, BOM and routing lines, and open documents. Run duplicate, missing-field and inconsistent-unit checks to estimate the defect share. Enter these along with your time per correction. Use at least three mock loads, because the first usually reveals mapping errors and the second reveals the data defects behind them.
- Profile data before estimating
- Include open orders and open invoices
- Plan one mock load for performance timing
- Reserve hours for reconciliation reports
The model
Cleansing hours equal (master records plus BOM lines) times defect share times minutes per fix divided by 60. Validation hours equal open documents times minutes per document divided by 60. Mock load hours are cycles times team hours per cycle. The sum multiplied by the blended rate gives the cost. The weeks output assumes three people at 30 hours a week.
Reading the output
If cleansing exceeds 50 percent of total hours, invest in automated rules and bulk correction tools rather than manual edits. If validation of open documents dominates, reduce the open document count by closing orders before cutover and migrating only balances for old invoices. The chart shows how sharply effort rises with dirty data.
Common mistakes
Teams assume the defect rate is low without profiling, forget unit-of-measure conversions, and migrate all history instead of what the business needs. In EU projects also check that personal data in customer and contact records is migrated only as long as the retention rules allow under GDPR.
Frequently Asked Questions
How many mock loads do I need?
Three is a practical minimum: mapping, data quality and dress rehearsal. Complex multi-plant migrations often need four or five.
Should I migrate historical transactions?
Usually only what you need for operations and statutory reporting. Keep older history in an archive or reporting database to cut migration effort.
What is a typical defect rate?
It varies widely. Legacy item masters often show double-digit rates of duplicates or missing fields. Measure with profiling instead of assuming.
Does it cover custom data transformation code?
No. Add extraction and transformation programming separately because it depends on the source system and the target import tools.
Netray builds on-premises tools that profile ERP and legacy data and flag likely defects before mock loads, so estimates rest on measured numbers.
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