6 steps to master asset data collection, validation and enrichment

On Thursday 9th February, ABL hosted a free webinar on the what, why and how of master asset data collection, validation and enrichment, in order to help attendees mitigate against common challenges and pitfalls.

The webinar was held in response to ABL’s 2022 Maintenance Manager report, where one third of more than 400 professionals who took part in the study identified CMMS data quality and usage as one of the biggest challenges they currently face. 

In this blog post, we’ve shared a summary of the importance of master asset data and our 6 step roadmap to success, presented in the webinar by Principal Consultant at ABL, Brendan Furrow…

The importance of master asset data

“Data drives everything we do when it comes to asset management, from design documents and drawings, to operating procedures and operational data. Foundational data is the highway to a robust CMMS, so it’s crucial to develop a solid base of high quality data that will enable you to extract information, knowledge and ultimately, wisdom from the system.”

“Master asset data includes key details such as the equipment number, description, manufacturer and so on. Data can tell us many truths depending on its quality and accuracy – and it’s common for there to be a number of separate systems present when it comes to asset management. It’s crucial to integrate relevant systems and be able to create a feedback loop to empower leadership to make informed decisions on company targets and goals.”

A 6 step roadmap to success in master asset data

Step 1: Data gathering

“This initial stage encompasses the quality and quantity review of all available source material. You need to gather data in order to be prepared and have a sense of predictability in your assets for future planning. 

“Example documentation includes standards and taxonomy which often refine the asset management system, such as parent-child relationship within the CMMS, how each tag is structured, and diagrams. All are very important, however, we often find that data sources are of poor quality, outdated or missing.”

Step 2: Standards, taxonomy and guidelines

“Data standards are crucial in attaining a consistent and accurate interpretation of information and data analysis, as they allow companies to enhance management of processes, improve business decisions and optimise work preparation, scheduling and execution. 

“Taxonomy refers to the structural component of individual items, depending on what the system or CMMS requires and how the data should be presented. This could be any character limitations, formatting or tagging of equipment, all of which are very important, however 15 – 40% of asset management information is recorded incorrectly. 

“Guidelines further refine how the standards and taxonomy will impact working with the system based on the information available, outlining the best approach to harnessing the data available and how to fill any gaps consistently and accurately.”

Step 3: Desktop asset verification

“Desktop asset verification is where data begins its journey from source material to the CMMS. Some common issues we see include a lack of clarity around which data is important, reluctance to see the entire process through, and no clear links between drawings and the existing asset register.

“It’s important to focus on a defined scope, agree upon achievable delivery dates, envision the final product and seek guidance from those who work with the equipment to overcome these challenges. Remember, not all equipment on a drawing needs to be populated into the CMMS – only the maintainable equipment that you’re focusing on.”

Step 4: Physical asset verification

“Once your desktop asset verification is complete, you need to physically verify this on site or in the field. Common challenges we come across at this stage include outdated drawings, or companies being unsure around what’s important and how much effort will be required. Again, we recommend focusing on quality over quantity, and setting out a clear scope of work beforehand, as well as conducting a short pilot assessment to determine the future efforts required. 

“It’s crucial to remember that electronic methods are always far more efficient than traditional pen and paper at this stage. We’ve found that project duration and resources are reduced by up to 60%, if electronic methods are used instead of pen and paper, with increases of about 400% in data accuracy.”

Step 5: Master data implementation

“This pivotal step involves the reconciliation of collected data against the source data, and is therefore highly time sensitive. This should involve multiple quality management steps to ensure the data meets taxonomy and standards, with a continuous cycle of reviewing data and strategies, as well as validating, enriching and cleansing data to ensure the CMMS is optimised with accurate, high quality data. This requires clear ownership of the database and must be understood throughout the organisation with a clear management of change system in place.”

Step 6: Master data governance

“Once data has been collected and validated, it’s important to govern the data so it can be utilised effectively. Master data governance refers to the rules and policies around acquiring, storing, managing and sharing your master asset data so it can be used to inform effective decision making going forward. At this stage it’s important to focus on quality and security, and ensuring your master asset data is clean and consistent for those who use it.”

If, like many others, CMMS data quality and usage is a key challenge you and your team face, you can learn more and unlock your roadmap to success in master asset data collection, validation and enrichment by watching our free webinar on-demand.