This data quality audit checklist helps SME finance and operations teams find duplicate records, missing owners, inconsistent values, spreadsheet workarounds and reporting defects before migration, reporting or automation work starts.
This data quality audit checklist helps SME finance and operations teams find duplicate records, missing owners, inconsistent values, spreadsheet workarounds and reporting defects before migration, reporting or automation work starts.
Use this checklist when messy operational data is starting to affect reporting, migration, automation or management decisions. It is written for SME teams that need practical evidence, not a theoretical data-governance programme.
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Duplicate customers, suppliers, products, contacts, locations and accounts.
Blank values in fields used for reporting, workflows, migration or finance checks.
Invalid status values, inconsistent naming, stale records and abandoned codes.
Manual spreadsheet corrections that are not written back to the source system.
2. Check ownership and definitions
Name the person who owns each important field, list or report definition.
Find fields used by multiple departments with different meanings.
Document which values are allowed and who can change them.
Flag fields that drive reports, approvals, stock, invoicing or customer communication.
3. Prioritise cleanup by risk
Start with records that affect money, stock, customer commitments and cutover readiness.
Separate cosmetic cleanup from defects that break reporting or migration.
Create a backlog with owner, fix, due date, evidence and retest status.
Put checks in place so the same defect does not return next month.
Evidence note
These resources are based on practical ERP migration, data-readiness and reporting-reconciliation controls: named owners, source inventories, issue registers, source-to-target maps, validation evidence and sign-off before leadership relies on the numbers.