Asset and Maintenance Master Data Quality Is Not an IT Challenge

Data quality is often the domain of IT, who are responsible for ensuring high-quality data in the corporate enterprise systems. While this works well for many different types of data, it does not work well for asset and maintenance master data. IT can implement and maintain maintenance and reliability systems, but they cannot and should not be responsible for the master data that goes into them.

Corporations typically try to store all their asset and maintenance data in one place, their EAM system. Connected to their EAM, they may have multiple document management programs and other smaller disconnected platforms. But for the most part, when looking for information, the first place to start should be their EAM. The data stored there is vast and often only connected through process. Financial data looks nothing like supply-chain data, which looks nothing like asset and maintenance data. Each specific type of data is unique and therefore has different needs for how it is stored and accessed. And of course, different data stewards who are experts on their specific subset of data.

Asset and maintenance data specifically is quite unique compared to the data that other departments will be using. It is quite technical, detailed, and vast. It covers information such as:

• How long maintenance tasks take
• How to classify technical equipment
• How critical the equipment is to production
• How equipment links together as part of a process

To understand this data, and to make any improvements to any master data problems, maintenance and engineering expertise is required. It is also beneficial to have an understanding of the assets and how they operate and are maintained.  This is for the same reason, that you would want qualified individuals interacting with your sensitive, financial data. Take asset criticality, for example. Many of our customers struggle with having the correct and complete equipment criticality assessments. This makes it impossible to prioritize work, and increases the time required for scheduling and planning. Others struggle with:

• Missing equipment information, such as make and model numbers
• Disconnected documents
• Automating scheduling
• Asset data organization
• Equipment classification
• Reporting

And the list goes on! We have spent a lot of time with customers who deal with similar issues, and in our experience these issues are best tackled by maintenance and reliability experts. These are the people that are entering, storing and using the data every day. They understand the issues caused by poor-quality data, and they usually have some great ideas and incentive to fix it. Getting the EAM data right is not primarily an IT or data management challenge. It’s a maintenance and reliability challenge.