Data
Data quality ownership model for ERP programmes
Reviewed by ERP Search editorial team Last reviewed 01-Mar-2026 Independent buyer guidance for growing businesses
Editorial context
- Category
- Data
- Role
- Top-of-funnel trust + newsletter content
- Next step
- Link to related guide or comparison page
A practical operating model to assign data ownership and reduce migration defects.
Data quality is a business accountability supported by technology, not an IT-only task.
Assign data stewards by domain and require measurable quality thresholds.
Track defects to source process owners to prevent recurrence.
Why this matters
- Data quality improves when ownership is attached to business outcomes such as credit accuracy, inventory trust, supplier readiness, and reporting confidence.
- A data operating model should define who approves standards, who fixes defects, and how exceptions are escalated.
- Migration defects are often symptoms of weak source process discipline, so the goal is not just cleansing but prevention.
What to check in practice
- Data quality is a business accountability supported by technology, not an IT-only task.
- Assign data stewards by domain and require measurable quality thresholds.
- Track defects to source process owners to prevent recurrence.
Mistakes that create avoidable project pain
- Confusing software functionality with business readiness.
- Assuming a partner or vendor will solve unclear process ownership for you.
- Treating post-selection execution risks as someone else’s problem.
What to do next
- Translate the key points into a shortlist scorecard, project risk log, or operating checklist the team can use immediately.
- Use the article to shape the next vendor demo, partner workshop, or internal decision forum rather than leaving it as passive research.
- Pair this article with a relevant guide or comparison page before final decisions are made.