A Guide for SAP S/4HANA Data Conversions

Your company has decided to implement SAP S/4HANA. One of the first steps in implementing S/4HANA is to identify whether it will be a system conversion, new implementation, or selective data transition. Irrespective of the type of implementation one decides to do, you want to be sure that you have a full data conversion plan in place as part of the project. 

Data conversion is a major part of a successful SAP project. If you don’t start working on data cleaning and conversion early and continue that work throughout the project, it can sneak up on you and become a last-minute crisis. A well-designed and executed system will not provide the value that your company is looking for if the data loaded into it isn’t clean and accurate. This piece serves as a guide for SAP S/4HANA data conversions. 

SAP S/4HANA DATA CONVERSION GUIDE 

Follow these SAP S/4HANA data conversion best practices to ensure that your data strategy is thorough and robust. 

1. Identify Critical Master Data Objects 
The first step in data conversion is to identify the critical master data objects, the sources of that data, and current and future system(s) of record for these objects. Master data includes all the data that is required to do business – customers, vendors, employees, locations, parts, products, etc.  

Not only does the master data need to be identified, but it needs to be clean and accurate. We recommend using data profiling tools to analyze the quality of data and start the cleansing process. Data profiling tools will allow you to find duplication of data, missing data elements, data format consistency, wrong data, and outdated data. 

2. Determine What Transaction Data to Migrate 
Next, determine what transaction data needs to be migrated. It’s critical to reduce the amount of historical data that will be moved to the new system. Migration of transactional data creates additional complexities when moving to a new system that leverages more streamlined processes. We typically recommend only migrating master data, open transactions, and G/L balances for new implementations. 

3. Create Data Archiving Strategy  
You will want to find a place and process for holding and referencing your historical data. Before you migrate data to your new system, create a data archiving strategy and archive systems, message, and change logs before migration. Historical data can be archived to file systems, document management systems, or into a data warehouse while documents and attachments should be archived to a document management system. Make sure that your archiving strategy follows the audit requirements of your company and industry.  

4. Define a Data Governance Strategy  
Identify key business stakeholders for each data object. These individuals will own the data object(s) and be responsible for making critical data-related decisions about those objects. You need to create a process flow for creating, maintaining, and approving master data and harmonizing data across systems. You should also explore technological options to automate and enhance the data creation, maintenance, and integration. In many cases, your business’s data migration project is the catalyst for creating a data governance strategy. 

5. Prepare a Data Migration Strategy 
Data migration is a three-part process. The first part includes extracting data from the current system(s), and the second part is cleaning and transforming that data into the new SAP format. The third part involves determining the load and data validation process. It’s important to identify suitable tools for extraction, data cleansing, transformation, loading, and reconciliation for different data objects. Create a detailed plan for migration, data validation, reconciliation, load simulations, testing, and test cycles and incorporate the converted data into integration test cycles.  

ENSURING A SUCCESSFUL DATA MIGRATION  

According to one study, 66% of SAP users said data management is the major challenge when moving from SAP ECC to SAP S/4HANA. Data is the critical cog for an intelligent enterprise, and it starts with successfully extracting, transforming, and loading clean data.  These five steps to data migration listed above will provide your organization with an effective strategy to manage data migration projects efficiently and successfully. 

For more guidance on SAP data migrations, our team can help. 

This piece was originally published by a partner in our business ecosystem, Clarkston Consulting, and written by Anand Vidhyasekaran. Learn more about Clarkston here.