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S/4 Transformation:

Data, Costs, Risks!

The S/4 Transformation poses a series of challenges in terms of data, costs, and risks. The importance of data is particularly noteworthy as it represents a central component of the transformation. In our view, companies looking to avoid negative impacts on their finances should start with the S/4 Transformation no later than 2025. This is especially crucial when aiming for a migration within a timeframe of maximum two years. However, it should be noted that for companies in the upper midsize segment, migrations typically take longer, around 2-3 years or even more.

The assertion that data presents the greatest risk in the S/4 Transformation is indeed accurate. When migrating from an existing system to SAP S/4HANA, data must be transferred from the old system to the new one.

Various challenges can arise in the process:

  1. Data Quality: The quality of data in the existing system may vary, and inconsistencies, redundancies, or erroneous data may occur. These issues need to be identified and addressed before the migration to ensure that the data in the new system is accurate and reliable.
  2. Data Complexity: Companies often possess a large volume of data in different formats and structures. Migrating these complex data structures to the new system requires careful planning, and potentially data cleansing and transformation.
  3. Data Integration: Companies frequently work with different systems and data sources. Integrating this data into the new S/4HANA system can be challenging, particularly when it comes to data harmonization and alignment of data schemas.
  4. Data Migration Tools and Processes: Selecting and implementing the appropriate data migration tools and processes is crucial to ensure a smooth and efficient migration process. Choosing the wrong tools or inadequate preparation can result in data loss or inconsistencies.

To minimize the risks associated with data in the S/4 Transformation, the following measures are recommended:

  1. Data analysis and cleansing: Conduct a thorough analysis of data quality and cleanse the data before starting the migration. Identify inconsistencies, duplicates, and erroneous data, and resolve these issues.
  2. Data mapping and transformation: Develop clear rules and guidelines for data mapping and conversion between the old and new systems. Consider differences in data structures and formats.
  3. Data migration testing: Perform extensive testing to ensure that the data is migrated correctly and completely into the new system. Verify data integrity and ensure that all business processes function properly.
  4. Training and change management: Ensure that employees working with the data have the necessary training and educational materials to handle the new system. Support them during the change process to ensure a smooth implementation.

The S/4 Transformation is a complex endeavor, and data migration plays a crucial role in the project’s success. Through thorough planning, preparation, and execution, companies can minimize the risks associated with data and achieve a successful transformation.

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