How to Enhance Data Quality in S/4HANA: A Comprehensive Guide

As the 2027 end-of-maintenance deadline for transitioning to SAP S/4HANA rapidly approaches, recent findings from SAPinsider research indicate that only 55% of SAP organizations have either completed the move or are currently in progress of migrating to S/4HANA. These organizations may lack the time, skills, or resources to make the move just yet. Additionally, data quality plays a vital role in the success of an SAP S/4HANA migration.

Importance of Data Quality in S/4HANA Migration

Data quality impacts every business process, decision-making, and the overall outcome of the digital transformation initiative. Poor data quality can result in inaccurate reporting, inefficient processes, and ineffective decision-making. Therefore, it is crucial to prioritize and maintain high data quality during the S/4HANA migration journey.

High data quality ensures accurate reporting, streamlined processes, and informed decision-making. It helps businesses leverage the full potential of S/4HANA and maximize the benefits of the migration. By investing time and resources in assessing data quality before the migration, planning for process redesign, transforming and validating data during the migration, and continuously improving data quality after the migration, businesses can enhance data quality in their S/4HANA migration and drive successful outcomes.

Additionally, the pre-migration phase is an excellent opportunity to plan how S/4HANA can provide structure and governance for business processes. Tasks previously managed using Microsoft Excel or other ungoverned systems should be given special consideration. By planning for process redesign, businesses can ensure a smooth transition to S/4HANA and maximize the benefits of the migration.

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During Migration

During the migration process, data transformation is not just about moving data from one point to another. It presents an opportunity to transform the data to fit into the new system’s structure. Automation tools like Data360Analyze can assist in transforming data sets to accommodate new schemas or data structures that support the ongoing needs of the business.

Validating data is another crucial step during migration. Ensuring that the migrated data conforms to the business rules in S/4HANA is essential for accurate reporting and efficient processes. Tools capable of validating every record and returning an SAP error message if the data is incomplete or does not conform to the required format are invaluable in this stage. By validating data during migration, businesses can prevent data quality issues and ensure a successful transition to S/4HANA.

After Migration

After the migration to S/4HANA, continuous improvement and ongoing business agility are essential. Automation tools continue to be valuable for supporting these objectives. They enable the export, quick editing, and import of data back to SAP S/4HANA, streamlining the process while ensuring alignment with security standards set up by the SAP solution manager.

By leveraging automation tools for continuous improvement after migration, businesses can optimize data quality, enhance processes, and adapt to evolving business needs. This ongoing focus on data quality and agility ensures that the benefits of the S/4HANA migration are sustained in the long run.

Case Study: Tuomi Logistiikka

Tuomi Logistiikka Oy, a Finnish-based company undergoing a migration to SAP S/4HANA, successfully leveraged Precisely Automate for data cleansing and transformation. Despite a short-time frame and a large amount of data, the company achieved a successful migration by utilizing the powerful capabilities of automation tools. This case study highlights the importance of automation in enhancing data quality before and during the S/4HANA migration process.

Success Story of S/4HANA Migration with Automate Studio at Tuomi Logistiikka

Conclusion

Maintaining high data quality is crucial in the modern digital business environment, especially during the SAP S/4HANA migration process. Poor data quality can lead to inaccurate reporting, inefficient processes, and poor decision-making. By following the simple steps, businesses can enhance data quality and ensure the success of their S/4HANA migration.

Using automation tools like Precisely Automate Studio and Data360Analyze can help in assessing data quality, planning for process redesign, transforming data, validating data, and supporting continuous improvement after the migration. The case study of Tuomi Logistiikka demonstrates the power of automation tools in achieving a successful migration despite time constraints and a large amount of data.

In conclusion, prioritizing data quality throughout the three stages of migration – before, during, and after – is essential for a seamless and effective S/4HANA migration process.

E-Book: 4 Keys to Improving Data Quality