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Clean your data before importing to EDGEBIC and the migration goes smoothly, because the import surfaces every gap as a broken link or a wrong date. In EDGEBIC by User Solutions, references link by name and the schedule reads specific fields, so name drift, blank required values, and dead references all show up the moment you import. Fixing them first in the spreadsheet is cheap. Chasing them after the import is not, which is why a short cleaning pass is the best time you spend on a migration.
The import is honest, so give it clean input
An import mask does exactly what you tell it. It links a routing step to a work center by the name in your file, and it schedules an order by the times and quantities you mapped. That honesty is a strength, but it means the quality of what comes out matches the quality of what goes in. Feed it a name spelled two ways and the link breaks. Feed it a blank run time and the step has no duration.
So the highest-value migration work happens before the first import: cleaning the data so the import has good input to be honest about. This is not about perfection, and it is not the whole database. It is about the scheduled tree you are actually bringing across, and it targets the specific problems that break an import or distort a schedule. It fits at the front of the phased path on the RMDB to EDGEBIC guide.
Clean only the data scheduling reads
Years of accumulated data hold cruft: duplicate parts, retired work centers, half-filled records. You do not have to clean all of it, because scheduling does not read all of it. Clean the scheduled tree, the finished goods, sub-assemblies, components, work centers, routings, and open orders you are migrating, and leave the dormant remainder in your system of record.
That reframing makes the job tractable. You are not scrubbing a whole ERP. You are tidying the few hundred parts and few dozen work centers that feed the schedule, which is a far smaller target.
Three problems to fix, in order
Name drift. References link by name, so a product or work center spelled one way in one file and another way in another breaks the link. This is the single most common migration failure. Make every product and work center name identical across your item, work center, routing, and order files. A find-and-standardize pass in the spreadsheet fixes it before it can become a broken link, the symptom explained in the order to import your data into EDGEBIC.
Blank required fields. The schedule needs specific values. A routing step needs a work center, a setup time, and a run time. An order needs a product, a quantity, and a due date. A blank in any of these leaves the schedule with nothing to work from. Scan the columns the schedule reads and fill the gaps at the source. Watch the flip side too: depending on the mask, a blank in a mapped column can clear a field on re-import, so a blank is not always harmless.
Dead references. Over time, routings come to reference work centers you retired and sub-assemblies that no longer exist. A step pointing at a work center that is not being migrated has nothing to attach to. Drop the dead routings, or repoint them at the work centers you actually run, before you import.
Reconcile capacity, because wrong dates are quiet
Broken links are loud: a missing reference is obvious. The dangerous failure is quiet, a plausible-looking date that is simply wrong because the capacity behind it is off. A missing holiday, a wrong instance count, or an efficiency factor that did not come across produces dates that look reasonable and are not.
So part of cleaning is reconciling capacity before you read any dates. Confirm EDGEBIC's capacity per work center matches what your current system assumed, work center by work center. This is the same capacity check that anchors migrating your work center and shift definitions to EDGEBIC, and it is the guard against wrong-but-plausible dates. The concept behind it is finite versus infinite capacity scheduling.
Cleaning is iterative, not a gate
You do not have to clean everything perfectly before you import at all, and trying to would stall the migration. Because import masks are saved, cleaning is a loop: clean the obvious problems, import, spot-check, fix what the import reveals, and re-import in one click.
The goal of the pre-import pass is narrow: remove the problems that break the import outright, the name mismatches and missing required fields, so the first import is useful enough to review. Everything else you refine in the fast import-fix-reimport cycle. A shop that re-imports its routings four times while cleaning them does the column mapping once and clicks three more times.
A worked example
A shop cleans its make-to-order line before migrating.
- Standardize names. The planner runs a find-and-standardize pass so every work center and product name is spelled one way across all four files.
- Fill required fields. They scan the routing file for blank setup or run times and the order file for missing due dates, and fill the gaps in RMDB.
- Drop dead references. Three routings point at a work center retired last year. They repoint two and drop one.
- Import and reconcile. They import in dependency order, then verify capacity per work center against RMDB before reading a date.
- Loop. A spot-check finds two routings with a swapped sequence in the source. They fix them, re-export, and re-import in a click.
The loud problems were gone before the first import, and the quiet ones were caught by the capacity check.
The takeaway
Cleaning your data before importing to EDGEBIC is the highest-value hour of a migration. Standardize names so references link, fill the required fields the schedule reads, and drop dead references, all on the scheduled tree you are actually bringing across, not the whole database. Reconcile capacity before you trust a date, because a wrong date is quiet where a broken link is loud. Then let the saved masks make cleaning iterative rather than a gate. See the platform in full on the EDGEBIC overview, read the whole path on the RMDB to EDGEBIC guide, and work from an EDGEBIC migration checklist as you go.
Expert Q&A: Deep Dive
Q: Our RMDB data has accumulated years of cruft: duplicate parts, work centers nobody uses, half-filled routings. Where do we even start cleaning for a migration?
A: Start with the data that scheduling actually reads, and clean it in the order the import needs it. First, the names that form links: make sure every product and work center name is spelled one way and used consistently across your item, work center, routing, and order files, because a single mismatch breaks a reference. Second, the required fields on the records you are migrating: routing steps need a work center, a setup time, and a run time; orders need a product, a quantity, and a due date. Third, dead references: drop routings that point at work centers you retired and sub-assemblies that no longer exist. Deliberately ignore the cruft that does not touch scheduling, the dormant parts and unused work centers you are not migrating anyway. You are not cleaning the whole database; you are cleaning the scheduled tree you are bringing across, which is a far smaller and more tractable job.
Q: We are worried a bad import will silently produce wrong dates that look plausible. How do we catch that?
A: The silent failure to guard against is not a broken link, which is loud, but a plausible-looking wrong number, so you catch it by reconciling capacity and spot-checking totals rather than trusting the schedule at face value. Before you read any dates, verify that EDGEBIC's capacity per work center matches what your current system assumed, because a wrong instance count or a missing holiday produces dates that look reasonable but are off. After the import, spot-check a handful of routings against the source, confirming operation counts, times, and sequences match. Then compare EDGEBIC's dates for a small set of jobs against your existing plan, and treat every difference as something to explain, not something to accept. A difference that traces to a data problem is one you fix at the source and re-import; a difference you cannot explain is a signal to keep digging before you trust the migration.
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