Maintenance Data Quality
Maintenance data quality is the degree to which asset, work, inventory, cost, and reliability information is accurate, complete, consistent, timely, and usable.
What this term means in maintenance
Maintenance data quality is the degree to which asset, work, inventory, cost, and reliability information is accurate, complete, consistent, timely, and usable.
Data-quality dimensions
Useful maintenance data should be:
- Accurate
- Complete
- Consistent
- Timely
- Unique
- Valid
- Traceable
Practical example
A pump work order is recorded against the correct component with clear action, labor, parts, downtime, failure mode, and completion date.
Common data problems
Examples include duplicate assets, vague comments, incorrect status, missing parts, wrong dates, and inconsistent codes.
Governance
Required fields, controlled lists, validation, review, and ownership improve quality.
Common mistake
Making every field mandatory encourages users to enter guessed values instead of accurate information.
Related concepts
Related maintenance terms
Keep exploring connected CMMS, reliability, and maintenance planning terms.
Asset Data Governance
Asset data governance defines ownership, standards, approval, quality rules, and lifecycle controls for asset information.
Asset Master Data
Asset master data is the controlled core information used to identify, classify, locate, maintain, and report on assets consistently.
Failure Code
A failure code is a controlled classification used to record how an asset or component failed in a consistent, reportable way.
Maintenance Data Quality FAQs
- What is maintenance data quality?
The accuracy, completeness, consistency, timeliness, uniqueness, validity, and usability of maintenance information.
- What are common data problems?
Duplicate assets, vague comments, wrong status, missing parts, incorrect dates, and inconsistent codes.
- Should every field be mandatory?
No. Mandatory fields should be limited to information users can accurately provide.