Data

Data quality ownership model for ERP programmes

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.