How a Manufacturing SME Reduced ERP Import Errors by 85%
A French industrial parts manufacturer was losing 14 hours per week to manual catalog correction. Six weeks after adopting ImportCheck, that figure dropped to under 2 hours — and their first ERP go-live shipped on schedule for the first time in the company's history.
Industry
Industrial parts manufacturing
Company size
120 employees
ERP
Sage X3
Time to results
6 weeks
Key results at a glance
85%
Reduction in import errors
34% → 5% error rate
12h
Saved per week
Across operations team
6 wks
Time to full deployment
No developer required
€38k
Avoided ERP delay costs
vs previous migration
Customer profile
The customer is a family-owned industrial parts manufacturer based in the Lyon metropolitan area, founded in 1987. With 120 employees across two production sites, they supply mechanical components to automotive and aerospace sub-contractors throughout France and Belgium.
Their product catalog spans approximately 8,400 active SKUs — structural fasteners, precision bearings and machined assemblies — maintained by a two-person purchasing team and updated by five to eight field sales representatives depending on the season.
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Industry
Industrial parts manufacturing
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Team size
120 employees, 2 purchasers
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Catalog size
~8,400 active SKUs
The problem
In early 2025, the company began migrating from an aging custom ERP to Sage X3. The IT project manager estimated an eight-month rollout. By month three, catalog imports had become the primary bottleneck.
“Every Monday morning, Sophie from purchasing would open the import log and find the same types of errors. Invalid price format, missing supplier code, duplicate reference. She'd spend her entire morning correcting rows one by one in Excel. By the time she re-imported, half the corrections had introduced new errors.”
The core issues were structural, not human. The catalog was maintained across multiple Excel files by contributors with different habits. No validation occurred before the file reached the ERP. The ERP rejection messages were technical and difficult to interpret without developer involvement.
Pain points identified in initial assessment
Implementation
The IT project manager discovered ImportCheck during a search for ERP catalog validation tools. The evaluation-to-deployment timeline was deliberately kept short: two weeks of parallel testing, four weeks of operational rollout.
Evaluation & parallel testing
- Created ImportCheck account; uploaded the last three historical import files to compare detected errors against known Sage X3 rejections.
- ImportCheck identified 91% of the errors that Sage X3 had previously rejected — plus 23 additional issues the ERP had silently accepted but that caused downstream data quality problems.
- Shared findings with the purchasing team lead. Decision taken to proceed without any IT development work.
Process integration
- Established a new "validate before upload" step in the catalog update process: contributors export from Excel, upload to ImportCheck, receive the error report, fix, re-upload.
- Purchasing team trained in 45 minutes — no technical background required. The error report uses column names from their own file, not ERP field IDs.
- IT team removed from the import correction loop. They remained as escalation point only.
Operational rollout
- All eight catalog contributors added to the team account. Each contributor validates their own section before submitting.
- Error rate at first Sage X3 submission dropped from 34% to 6% in week five, and to 4% by week six.
- First full catalog import of the new ERP go-live completed on the scheduled date — no overrun.
No developer involvement after day one
The entire rollout was owned by the IT project manager for setup and the purchasing team lead for day-to-day operation. No custom integration work, no scripts, no API configuration — the operations team ran it independently from week two onward.
Results
By the end of week six, the team had fundamentally changed how catalog imports worked. The results below are based on data from the four weeks prior to ImportCheck adoption vs. the four weeks immediately after full rollout.
| Metric | Before | After (6 weeks) |
|---|---|---|
| Import error rate (rows rejected) | 34% | < 5% |
| Avg. correction cycles per file | 5–7 cycles | 1–2 cycles |
| Time spent on catalog correction per week | 14 hours | < 2 hours |
| IT team hours per import cycle | 2–3 hours | 0 hours |
| Time from file ready to clean ERP import | 3–5 days | Same day |
| Contributors able to self-validate | 0 of 8 | 8 of 8 |
| ERP go-live on scheduled date | No (6-week overrun) | Yes |
“What changed is not the tool — it's who owns the problem. Before, Sophie would discover errors after the ERP rejected the file and come to us to decode the log. Now she catches everything before she even submits. IT hasn't touched an import file in two months.”
Detailed metrics
Time saved — weekly breakdown
Error type breakdown (pre ImportCheck)
€38,000
Avoided ERP delay costs
Previous migration overran by 6 weeks; this one shipped on time
624h
Operational hours recovered per year
12h/week × 52 weeks — reallocated to commercial activities
7:1
Return on subscription
Year 1 value vs annual subscription cost at Pro plan
Lessons learned
Looking back on the rollout, the IT project manager identified four factors that determined the speed and depth of the improvement.
Validate before — not after — the ERP
The entire previous process was reactive: submit to the ERP, read the rejection, fix, repeat. Moving validation before the upload removed the ERP from the correction loop entirely. Errors were caught in a familiar tool (ImportCheck) rather than in cryptic ERP logs that required IT to interpret.
Make the error report readable by the person who can fix it
ERP error messages reference internal field identifiers. ImportCheck reports reference the column headers from the uploaded file — the same names the purchasing team uses every day. This single change eliminated the IT translation step entirely.
Distribute validation to the contributors, not the reviewer
The previous model had one person (Sophie) responsible for validation of the whole file after all contributors had submitted. With ImportCheck, each of the eight contributors validates their own section before submission. Errors are caught closer to their source and the reviewing step becomes a formality.
Measure the error rate from day one
Uploading historical files during the evaluation phase gave the team a baseline: 34% row rejection rate. Without that number, it would have been difficult to demonstrate the value of the new process internally. The IT project manager recommends any team considering ImportCheck to start by uploading their last three import files before making any process changes.
What they would do differently
The IT project manager noted that he would have introduced ImportCheck at the very start of the migration project — not three months in. “We lost time we didn't need to lose. The validation problem was visible from the first test import. We assumed it would get better. It didn't, until we addressed it directly.”
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