Is your Master Data quality
impacting productivity?
With the use of Computerised Maintenance Management Systems (CMMS), there is a heavy reliance on quality Master Data to safely and reliably operate and maintain plant and equipment.
Master Data is the centrally stored data that enables the system to plan and manage operational and maintenance tasks.
It includes the maintenance strategy, asset register, functional locations (FLOC), spares, bills of material (BOM), and operational and maintenance documents.
The quality of Master Data has a significant impact on the productivity of an Operations limited resources.
Common Data Problems
Some of the most common master data issues encountered in asset-intensive organisations include:
- Asset registers no longer reflecting the actual plant
- Inaccurate equipment and spare parts information
- Poor capture of maintenance history
- Outdated procedures and documentation
- Missing failure and breakdown data
These issues result in:
- Additional maintenance planning effort
- Delays waiting on parts
- Longer shutdown durations
- Missed priority work
- Reduced ability to perform reliability analysis
- Workforce disengagement and loss of confidence in systems
Building Quality Master Data
Fixing flawed Master Data is not always straightforward and will take time. The more information you have, the more work there is reviewing, cleansing, updating and implementing. Hence why getting it “right” the first time is so important!
From our experience, you need to take several well-defined actions to ensure Master Data is correct, whether you are establishing data for new assets or creating/transferring data into a new (or existing) system. These are as follows:
1. Establish Data Standards Before Data Entry
Set up the rules for data management before you start entering it into your system; this includes naming conventions, asset register / functional location structures and management processes. Remember, the more “free text” boxes, the more free text will be entered (and the less accurate the data will be)
2. Reduce Free-Text Fields Wherever Possible
Engage your team throughout the process to get their feedback on how they will use the data. Make sure they are trained in the use of the system before implementation to avoid workarounds created (and extra low-quality data)
3. Engage the People Who Will Use the Data
3. If using BOM’s to plan maintenance activities, they need to be accurate. Ensure the people creating them understand how the equipment functions. Personnel will also need to know the supply business processes for ordering and returning spares.
4. Validate Data Before Implementation
Establish the Plan-Do-Check-Act cycle with your team. Regular reviews of the effectiveness of the system are critical to the ongoing improvement of the data. Waiting for an annual review will only ensure you have a year’s worth of insufficient quality data to review.
Maintain Data Quality Over Time
As we continue to develop and improve maintenance practices, the importance of the various forms of data will only increase.
Whether it is equipment operational information (run/production data), maintenance information (breakdowns/maintenance tasks), OEM inputs (maintenance strategy, parts, capacities, etc.) or business information (plant performance, shift activities, etc.), the ability of any maintenance system will be significantly impacted by the accuracy of this data.
By ensuring you have established master data correctly and have a process to manage the data/system, you will substantially improve the way you manage your assets and workforce.
Key Takeaways
Quality Master Data Helps Organisations
- Improve maintenance productivity
- Improve planning effectiveness
- Support reliability analysis
- Increase plant availability
- Build workforce confidence
Poor Master Data Leads To
- Rework
- Delays
- Incorrect purchasing decisions
- Reduced productivity
- Ongoing reliability issues