How do you calculate an ERP Data Quality Score?

Multiply the severity, occurrence, and detection ratings. With severity 6, occurrence 4, and detection 3 the raw product is 72, which this calculator expresses as a 4.55 score on its normalized scale.

What is a good ERP Data Quality Score?

Lower is better, and the useful comparison is relative. Set an action threshold against your own backlog — for instance remediate the top quartile of scores and any defect whose severity alone is high regardless of total.

What do severity, occurrence, and detection mean for ERP data?

Severity is the downstream damage of the defect (wrong cost, failed MRP, blocked PO); occurrence is how often the defect arises; detection is how likely existing controls catch it before it propagates — a high detection rating means it is hard to catch.

Why multiply the ratings instead of averaging them?

Multiplication, the FMEA convention, makes defects that are severe, frequent, and hard to detect rise to the top. Averaging would dilute a single critical dimension and bury genuinely dangerous defects.

How is this different from a Routing Accuracy Score?

The math is identical FMEA scoring; the scope differs. This score targets ERP master-data attributes broadly, while a routing accuracy score targets routing-specific defects. Keep separate scales so each backlog ranks internally.

How do I drive an ERP data-quality risk score down?

Reduce the dominant rating: add validation rules and field constraints to cut occurrence, build data-quality dashboards or audits to improve detection, or fix downstream processes so a defect causes less damage and lowers severity.

Manufacturing Master Data & Data Governance calculator

ERP Data Quality Score Calculator

The ERP Data Quality Score is an FMEA-style risk priority number for defects in ERP master data — wrong costing keys, blank planning parameters, inconsistent UOMs, or stale supplier records. ERP data stewards, master-data governance leads, and IT business analysts use it to rank which data-quality problems to remediate first. It matters because a single bad master-data attribute propagates into MRP runs, purchasing, costing, and reporting across the whole enterprise. Scoring severity, occurrence, and detection on a shared scale turns a long defect backlog into an ordered, defensible action list.

What this calculator does

Estimate ERP data quality for manufacturing master data and data governance using production-ready inputs so teams can rank risks and decide which issue needs containment, controls, or escalation first.
Use it when erp data quality in manufacturing master data and data governance needs a defensible ranking against other manufacturing master data and data governance risks for the next review.
It multiplies severity, occurrence, and detection ratings into one risk priority number for an ERP data-quality failure mode.

Formula used

ERP data quality risk score = ERP data quality severity score × ERP data quality occurrence score × ERP data quality detection score
Use the same scoring scale across comparable ERP data quality risks.

Inputs explained

ERP data defect severity rating:
ERP data defect occurrence rating:
ERP data defect detection rating:

How to use the result

Use it when triaging an ERP data-quality backlog, running a data-governance FMEA, or prioritizing remediation before a system upgrade.
It produces a relative ranking, not an absolute risk; identical scores can come from very different rating combinations, so always inspect the underlying severity, occurrence, and detection.

Common questions

How do you calculate an ERP Data Quality Score? Multiply the severity, occurrence, and detection ratings. With severity 6, occurrence 4, and detection 3 the raw product is 72, which this calculator expresses as a 4.55 score on its normalized scale.
What is a good ERP Data Quality Score? Lower is better, and the useful comparison is relative. Set an action threshold against your own backlog — for instance remediate the top quartile of scores and any defect whose severity alone is high regardless of total.
What do severity, occurrence, and detection mean for ERP data? Severity is the downstream damage of the defect (wrong cost, failed MRP, blocked PO); occurrence is how often the defect arises; detection is how likely existing controls catch it before it propagates — a high detection rating means it is hard to catch.
Why multiply the ratings instead of averaging them? Multiplication, the FMEA convention, makes defects that are severe, frequent, and hard to detect rise to the top. Averaging would dilute a single critical dimension and bury genuinely dangerous defects.
How is this different from a Routing Accuracy Score? The math is identical FMEA scoring; the scope differs. This score targets ERP master-data attributes broadly, while a routing accuracy score targets routing-specific defects. Keep separate scales so each backlog ranks internally.

Last reviewed 2026-05-12.