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ERP migration: which customer gets the open order?

The service-order file has all the required columns, but some entries still reference old customer IDs. The migration lead has to establish which customers those orders belong to in the new ERP. Automated data checks can compare the orders with the agreed target customer list and identify specific links that need clarification before migration.

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Syntalith

Published Updated 4 min read

Each migration rehearsal can bring back the same work: the team opens an export, searches for an old ID in the mapping spreadsheet, and asks someone who knows the customer. If the answer stays in a separate email, it is hard to tell whether the latest files include it. A useful check leads from an unresolved ID to the order and the person who can resolve the question.

An open service order with no agreed target customer

Suppose a company is preparing an open service order for migration. It contains a customer ID from the old system. Neither the agreed target customer list nor the mapping, which links old IDs to new ones, resolves that identifier. The service-order file itself has passed the required-column check.

The migration lead needs to see the order, old identifier, and missing mapping together. They can send the question to the person responsible for customer records. That owner reviews the relationship history and supplies an approved match or confirms that the issue remains unresolved. A similar company name in the new database is not enough to assign the open order to it.

Once the decision is recorded, the team reruns the checks on data using the changed mapping. The result shows whether the order now has the correct target customer and which other entries still need an answer. The lead does not have to guess whether a note marked “fixed” referred to the source file, the mapping, or a spreadsheet comment.

Check relationships across the files being migrated

A format check can establish whether the customer ID is in the right field. The team also needs to know whether that ID links to an agreed customer in the new system. The order and customer record can each be complete while their relationship still needs attention.

The exception list should therefore identify the specific orders and the versions of the exports and mapping used. The customer-data owner can open the material behind the issue. The lead sees the answer alongside the same entry instead of gathering it again before the next rehearsal.

The check history helps establish whether fewer open issues reflect agreed corrections or a new export version. The migration team decides whether to proceed with the import.

Use the checks available in your migration tool

Microsoft describes staging, mapping, processing order, and job history in Dynamics 365. Staging supports verification and conversion, while job history shows processed records and failures. Check whether your team can already see the relationships needing investigation there.

If the existing tool identifies the unresolved ID and links it to the right order, organizing how the team handles those cases may be enough. Additional automation is useful when exports are compared with mappings in separate spreadsheets and answers are manually passed between data owners and the migration team.

Ordinary rules can check known identifiers and their relationships. AI may help summarize differently worded investigation notes if they are difficult to review. It is unnecessary for establishing that a particular ID is absent from an agreed mapping.

What to commission when explanations lag behind new exports

In a proposed Syntalith project, we check relationships between records prepared for migration and build a view for the people resolving exceptions. Beside an order, the lead can see the unresolved mapping, the data owner's response, and the result of the next check. Checks use identified export and mapping versions, so the team can return to the basis of an earlier result.

The initial scope can cover open service orders and customer records. The migration team identifies the files and agreed mapping, while data owners identify who approves missing assignments. Syntalith connects the checks with the work of resolving questions; the scope ends with material for review before import.

For a conversation about automating data checks, describe an order whose customer had to be tracked down manually during the last migration rehearsal. Explain which files the team searched and where it recorded the decision. See Syntalith's pricing page for pricing information.

Reduce manual work in a defined process

Start with where work gets stuck and who has to repair it. We will compare the available improvements with implementation and operating costs.

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