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Today we live in a world where data is a necessary asset at any part of any profitable organization. However, without a proper routine in place to keep data clean, insights and value cannot be fully realized. Before knowing how to execute an efficient data cleansing project, you first need to know the current state of your data. If you don’t know what state your data is in, it is almost impossible to know the scope of what needs to be done or to later measure the ROI of the data cleansing project.

 

Data inevitably decays over time – with asset data, for example, you will have spare parts, equipment, ongoing operations and everything is continuously changing. Therefore, the process of data cleansing can help organizations keep their data up to date. Out of date data is risky for businesses and can result in bad decisions. Here are some of the best practices for cleansing asset data.

 

1. Develop a Data Quality Plan

Set expectations for your data. Create data quality key performance indicators (KPIs). We suggest that designing 10-15 key KPIs around master data will help in achieving completeness, accuracy, and suitability in accordance with attaining your desired objectives. Then, use a staging solution where you can easily visualize the data’s completeness through intuitive dashboards and reports that can be configured around specific metrics and KPIs.

 

2. Standardize Data

You have probably heard this plenty of times but here it is in simple terms: you can’t maintain healthy data while also letting unhealthy data into your EAM. Most businesses struggle to adopt effective standards due to the quality of their data. Without this, maintenance operations suffer significantly. Ultimately, standards should be properly documented and readily available. Managing data in a solution that includes an approval process ensures all stakeholders are well informed and able to comment on proposed changes. Checking important data ensures that all information is standardized when it enters your database and will make it easier to catch duplicates.

 

3. Validate the Accuracy of Your Data

After a data cleansing project is complete there is one final but necessary step which is to validate the data before it is redeployed into your operational systems including EAM, APM, IIoT and other systems. By including this step in a data cleansing project, you can reassure yourself that everything has been done right. As in every case, there are always errors that a human might overlook. Automated solutions give businessesthe power to leverage business rules that guide data remediation and approvals and enforce corporate standards as applicable.

 

How NRX Can Help

An effective data cleansing project should allow you to load, visualize, measure and fix your asset and maintenance master data in an easy and effective way. With solutions such as NRX AssetHub, asset-intensive companies now have access to scalable and simple-to-use software solutions. If you would like to learn more about how NRX AssetHub can assist your organization, take a look at our Cleansing Solution Ebook or contact us.

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