How to Run an Effective Data Cleansing Project
With the rise of international competition and market globalization, asset intensive organizations have made considerable efforts to improve efficiency and reliability while reducing operating costs. As a result, they have invested billions of dollars in ERP, EAM, and CMMS systems to meet their maintenance and reliability goals. Unfortunately, many companies have failed to ensure their data is accurate and complete which can affect major aspects of their infrastructure including maintenance, operations, asset integrity, reliability, materials utilization, engineering and planning. Therefore, generating high-quality EAM data that is complete and accurate is critical for their operations to run effectively.
This blog article outlines the importance of data quality, how to run an effective data cleansing project, as well as the benefits it can bring to your company.
Before we reveal the ways to run an effective data cleansing project, it is important to highlight the effects of bad data, and how ignoring it can be detrimental to your organization. For example, not only can bad data drastically increase maintenance costs, it can lead to unexpected down time and decreased productivity. In addition, it increases exposure to EH&S risks, it affects parts overages and of course wastes time searching for information.
Without an adequate data foundation, EAM systems will fail to deliver their expected value. As a result, improving maintenance operations becomes an impossible feat. When running an effective data cleansing project, there are a number of ways to execute this successfully. We have listed 3 of these ways below.
- Prioritize Data
When faced with bad master data, often the first instinct is to fix everything at once. A task of this magnitude cannot be completed simultaneously. Rather, a strategic list highlighting the most critical tasks is the best course of action.
First, focus on problems that have the largest impact on your company’s revenue and costs. Next, continuously test your results after syncing back into your EAM. This will allow you to evaluate which subsystems provide the best ROI. Finally, reuse work across other similar subsystems so you can save time and money.
- Measure Progress
Measuring the progress of a data cleansing project is typically a difficult task to pursue. Some best practices in achieving this include remaining focused on your ROI-based business objective. For example, be mindful of what your company is trying to accomplish and how your EAM system can be used to achieve this.
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. Next, use a staging solution where you can easily visualize data completeness through intuitive dashboards and reports that can be configured around specific metrics and KPIs.
- Adopting and Setting Standards
Most businesses struggle to adopt effective standards for master data. Without this, maintenance operations tend to suffer significantly because they are too demanding and the implementation is too difficult. Ultimately, standards should be properly documented and readily available. In addition, managing data in a solution that includes an approval process ensures all stakeholders are well informed and able to comment on proposed changes. Finally, use a solution that comes with a robust variety of out-of-the-box features such as reporting, KPIs and ISO 14224 compliance libraries.
Running an effective data cleansing project should allow you to load, visualize, measure and fix your EAM 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, contact us at 1-877-603-4679, download our Cleansing Solution Ebook or visit us at http://www.nrx.com
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