June 9, 2025 Clean ERP Data: How to Upload for Success

Manufacturers can strengthen ERP implementation by making sure that only clean, relevant data is uploaded into their systems.

By Zoey Majewski

Given the advancements in technology and software in integrated manufacturing functions, the importance of clean data cannot be overstated. Optimizing performance continues to be foundational for businesses of all sizes across a wide range of industries, and information is key to that initiative. As companies increasingly rely on enterprise resource planning (ERP) systems to streamline operations and enhance decision-making, it is crucial to ensure the accuracy and relevance of the data being uploaded.

Clean data is the backbone of any successful ERP implementation, and businesses must adopt best practices to achieve this goal. (In addition to its effect on performance, this is, of course, also a means by which businesses may gain, or continue to hold, a logistical advantage.)

Identifying and addressing data quality issues

Before diving into the data-cleansing process, businesses must assess which data truly needs to be brought into the new ERP system. While some businesses might see benefit in using as much data as they possess for this process, unassessed data loads can create systems hindrances that become increasingly unwieldy and difficult to manage as implementation and integration move forward.

Properly assessing data involves identifying all the different data points from various systems and determining their relevance. Often, a significant amount of data may no longer be relevant and does not need to be migrated. By focusing on essential data, businesses can avoid data overload and help ensure a smoother migration process. And, just as using unassessed data can compound systems obstacles, using properly assessed data can help enhance processes and grow operational gains going forward.

Once all relevant data to be migrated is identified, you need to begin the data-cleansing process. The first step in data cleansing is identifying and removing obsolete data. This includes records of customers who no longer purchase from the company, vendors who are no longer active, and items that are no longer sold or purchased. By eliminating this “junk data,” businesses can help ensure that only relevant and up-to-date information is migrated to the new ERP system.

During ERP migration, businesses often encounter several data quality issues. Inconsistent data is a common problem, where the same value is entered in multiple ways due to free-form text fields. Additionally, some fields may not be required, leading to incomplete records that hinder consistent reporting.

Outdated information points—such as old addresses, email addresses, phone numbers or even name renderings—and duplicate records are other common issues that need to be addressed. These should be addressed before data is loaded into the new system to avoid unnecessary errors during the implementation. Additionally, the process of correcting and/or removing these records can divert valuable time from higher-priority objectives and key functions.

Balancing comprehensive data with data overload

One of the challenges businesses face is balancing the need for comprehensive data with the risk of data overload. Historical data is often an area where companies try to bring in too much information. But, as noted earlier, this can have a hindering effect on processes: It could create a greater volume of information than could feasibly be processed within systems; and correcting that overload can, in turn, negatively affect resources for more impactful tasks. So it is essential to determine the true value of this data.

Instead of migrating all historical data into the ERP system, businesses can store it in external tools like Microsoft Fabric (Power BI), Tableu, Qlik or data warehouses, where it can be accessed when needed without slowing down the ERP system.

External data tools play a crucial role in enhancing the efficiency of data migration: These tools offer better ways to analyze and merge multiple sources of data, providing valuable insights that might be difficult to achieve within the ERP system. By leveraging these tools, businesses can help ensure that their data migration process is efficient and effective.

Best practices for data integration and maintenance

To support reporting and analytics, businesses must adopt best practices for data integration. This starts with assembling a dedicated team responsible for the data migration process. By involving key team members, businesses can help ensure that all important data and touchpoints are considered.

Performing test migrations with small subsets of data is another best practice. This allows businesses to validate the data for completion and accuracy before fully migrating it into the ERP system.

Once the data migration process is complete, the continuous monitoring and maintenance of data quality is essential. Businesses should establish a regular review plan, whether monthly or quarterly, with standardized best practices to help ensure that the data remains accurate and up to date.

Using tools like duplicate detection—and making certain fields required—can help maintain data integrity. Monitoring custom fields and ensuring that users enter data correctly are also critical steps in maintaining clean data, and they help ensure that the rewards of an otherwise successfully implemented system are not lost down the road.

Improving decision-making and operational success

Clean data in ERP systems significantly improves decision-making and operational success. Accurate and relevant data ensures that businesses can generate meaningful reports and gain valuable insights. When running reports, having clean data prevents the inclusion of irrelevant information that can skew results. This allows businesses to make informed decisions based on reliable data, ultimately driving operational success.

Clean data is the foundation of a successful ERP implementation. By identifying and removing obsolete data, addressing common data quality issues, assessing data needs and using external data tools, businesses can achieve a smooth and efficient data migration process. Adopting best practices for data integration and continuously monitoring data quality helps ensure that businesses can leverage their ERP systems to make informed decisions and achieve success.

Clean data is not just a one-time effort but an ongoing commitment to maintaining data integrity and driving business growth.

About the Author:
Zoey Majewski is a manager with over 7 years of experience in providing NetSuite implementation and optimization services. As a CPA, Zoey focuses on understanding an individual company’s overall business and financial processes to develop optimized solutions. She is responsible for analyzing business processes as well as designing and configuring best practice solutions within clients’ NetSuite environments.

www.wipfli.com

Subscribe to Industry Today