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ERP Data Quality Scorecard Worksheet

A scorecard gives managers one page that says how healthy each master data domain is. Enter record counts from your data quality checks and the worksheet calculates completeness, validity, uniqueness and a score per domain.

Download:
DomainActive recordsComplete recordsValid recordsNon-duplicate recordsCompletenessValidityUniquenessDomain score
91.8%
96.2%
95.7%
94.6%
92.6%
96.7%
94.4%
94.6%
93.1%
96.7%
94.7%
94.8%
94.2%
93.3%
100%
95.8%
89.6%
93.8%
100%
94.4%
Total active records
34,150
Average domain score
94.8%

Counts come from your rule runs: complete means all mandatory fields filled, valid means formats and lists pass, non-duplicate means not flagged as a likely duplicate. The domain score is a simple equal-weighted average. Weight dimensions if your policy requires.

Automated data quality scorecard

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How to fill it in

Add one row per domain such as items, vendors, customers, BOMs and routings. Use active records only, because inactive history inflates counts and hides problems. Take the complete, valid and non-duplicate counts from your rule runs. Completeness is complete records divided by active records. Validity and uniqueness follow the same pattern. Each percentage is shown per row and averaged into a domain score.

  • Count active records only
  • Use the same rules each period
  • Record the run date in the notes
  • Keep the previous period's file for trends

Reading the score

Do not treat the score as a grade. Use it to compare domains and track movement. A 94% completeness on 18,400 items still means over a thousand items with a missing mandatory field, which may include fast moving parts. Combine the scorecard with a defect log that lists the actual records and owners, and prioritize by business impact.

Choosing what to measure

Measures should reflect decisions. For items, completeness of planning attributes such as lead time, UoM and planner code drives MRP. For vendors, tax ID and bank data drive payments and compliance. For BOMs, consistency such as no inactive components drives costing and shop floor releases. Define each measure once in your rule catalog so the numbers are comparable between periods.

Common mistakes

Changing rules between periods, which makes trends meaningless, counting a record as complete when a field holds a placeholder such as TBD or 999, and reporting one big percentage that hides a bad domain. Check for placeholder values in your completeness rule.

Frequently Asked Questions

What is a good data quality score?

There is no universal target. Many teams aim for the high 90s on critical fields and accept lower scores on optional attributes. Set targets by business impact and raise them over time.

Should the dimensions be weighted?

Equal weighting is a fair starting point. If duplicates are far more costly than blank optional fields in your business, weight uniqueness higher and document the choice.

How often should I update the scorecard?

Monthly is common for governance reviews, with weekly rule runs feeding it. Daily runs suit high volume creation and migration cutovers.

Can I add more dimensions?

Yes. Export to Excel and add columns for consistency or timeliness, then include them in the domain score formula.

If the counts are gathered by hand each month, we can run the checks against your ERP read-only and populate this scorecard automatically.