Like most asset-intensive companies, you strive to have complete and accurate data. You also want the ability to analyze the quality of asset and maintenance data in an EAM/CMMS system. To accurately predict a completion date for a data repair project, you must ensure that your data is complete and accurate. If these criteria are vital for an efficient asset-intensive company, then why do so many organizations struggle with inaccurate CMMS data?

Many organizations find it extremely challenging to have robust and complete data. They also find it labour-intensive to continuously update their data so it’s accurate. But why? Here are 4 common issues that companies face when dealing with incomplete and inaccurate CMMS data.

  1. Unable to identify gaps and inadequacies in data

To have accurate and complete data, you must be able to identify the gaps and inadequacies. There could be missing information such as missing task lists in maintenance plans or data specifications for each object. You need to identify all the gaps in order to locate the right tools for the right repairs at the right time. Many companies struggle with this because there are no obvious clues or signs that display this.

  1. Nothing to measure against for their data compliance

You want the ability to measure the compliance of your data against an established standard. This will allow you to identify the areas of concern and focus on the areas that affect operational integrity. Without a standard or something to measure against, companies will continue to struggle.

  1. Unmonitored progress & quality of data

During a data build, you want the ability to track progress in real time. Reports should include the number of objects loaded into the system and access to reports on the completeness of the data for each object. Organizations struggle because they need the ability to observe as the build progresses. They also need the ability to drive the changes required to make their data complete and compliant during a data repair project. When organizations are not constantly monitoring the progress and quality of the data build project, problems arise.

  1. No communication regarding data quality issues between organizations and contractors

Communication is key during a data build. Organizations need to generate reports that communicate data quality issues to consultants and contractors that are hired to assemble and load CMMS data. These reports will highlight issues that might otherwise be difficult to measure and communicate. With no communication, your organization will not have a detailed breakdown of the error and omissions in the data, and will not be able to stay on top of the project. You will also not be able to verify the progress reported by your contractors, or track the results of the project.

Overcome These Issues Today

NRX AssetHub provides asset-intensive companies with a powerful Data Quality Report to analyze data that quickly and easily identifies the gaps and inaccurate CMMS data. It also reports on non-compliances and operational integrity issues. Our customers rely on our solution to highlight asset and maintenance data inadequacies and provides easy to follow recommendations for creating high-quality data.

If you would like to find out more about how NRX AssetHub can help you simplify your EAM and CMMS data quality analysis, contact us at 1-877-603-4679 or book a demo today!

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