Ready to plan your EAM migration project? First and foremost: ensure your asset and maintenance master data’s quality is high enough before migrating. High quality master data paves the way for increased productivity and a reduction in expenses related to maintenance and operations.

Simply lifting your master data from your current EAM/CMMS system into your new system brings the same inaccurate data from your current system into your new system. An EAM migration is an ideal time to fix foundational data issues because you are already required to move your master data out of your current system to complete the migration process. If you do not improve the quality of your master data before migration, it becomes much more challenging to make changes to your data once it is live in your new EAM/CMMS system. Investing in a new EAM/CMMS software is a waste of money if you do not set up your master data to get the intended benefits and ROI that your new system makes possible.

Search your Master Data for Quality Issues

Many asset-intensive companies struggle with inaccurate asset and maintenance master data. Issues include data quality, completeness, and integrity issues with the data in their current EAM/CMMS system. There is a minimum level of master data quality that is required to make every EAM/CMMS system work. Therefore, locating data quality issues, reviewing your asset hierarchy to identify gaps, and evaluating the completeness of the master data in your current EAM/CMMS system are significant steps in an EAM migration project. You should identify areas of particular concern, such as whether your asset register is incomplete, if your failure codes are inaccurate, or missing information such as task lists or equipment attributes.

 

Identify, Edit, and Validate

Once you have identified data quality issues, you can commence the data cleansing process. This process involves filtering and locating records and editing large amounts of data. Implementing a standard such as ISO 14224 can also be beneficial at this stage in a data improvement project because it makes it easy to validate your data against standards and industry best practices. A standard allows you to measure the compliance of your master data against an established standard, identify the areas of concern, and focus on the areas that affect operational integrity. Adopting a process-oriented hierarchy is a prerequisite for ensuring initiatives like Asset Performance Management, Improved Scheduling, Predictive Maintenance and Digital Twins are successful.

 

Cleanse and Export

​Once you have edited and validated your master data, you are ready to deploy your cleansed EAM-ready data into your new EAM/CMMS system. With your data cleansing project finished, you will be able to launch your new EAM/CMMS system with absolute confidence that it is populated with a complete and accurate master data.

 

How Can We Help?

If you would like to learn more about how our solutions can help you prepare your master data for an EAM migration, feel free to download our brochure or book a demo!

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