During an organization’s SAP S/4HANA journey, a lack of attention to data can be a common pitfall causing significant delays and cost overruns.
With a good testing program data issues can often be discovered during testing before go-live. However, this is very late in the program and will often require a delay or additional budget to correct any found data issues.
Protiviti recommends that companies lay the foundation for a strong data conversion strategy well in advance of the start of the implementation. If data preparation and data conversion are addressed and well planned before the start of the project, then one of the key risk areas for most projects will be largely mitigated before resource bandwidth is stretched too thin.
The first step in the process is to take stock of the data quality in the current system by analyzing existing master data pain points, issues with the chart of accounts, customer master, vendor master and other key data elements.
When migrating from ECC to S/4, it is important to develop a strategy for those specific master data elements that structurally differ between the two systems (e.g., Customer and Vendor Master data elements). It is also important to take inventory of all reports, determine which legacy custom reports will remain, which of those can be replaced by native S/4 reporting or analytics capabilities, and what additional reports need to be supported, including existing challenges with data and reporting outside of core systems (e.g., through spreadsheets or other tools).
Often there are unrealistic expectations of high data quality in existing systems, however, it is not uncommon to find a lack of clear data definitions, poor data quality and historical business process changes that have impacted data in the legacy system that have not been addressed.
The business should then consider what can be archived or eliminated to reduce the cleansing workload and cloud-related costs. It is critical to understand the tools that the organization may already own that can help with choosing a data cleansing method such as SAP licenses sitting on the shelf for products like SAP Data Services or SAP Information Steward.
Data cleansing is one of several critical activities that will need to take place pre-migration. Once an effective extraction process has been determined, the next step is data profiling and cleansing. The strategy here should not lose sight of the relevant business processes and in fact, those processes should drive the strategy around data profiling and cleansing for key master data elements (e.g., customer and material master in the order-to-cash process). A remediation plan and data quality scorecards, such as a data readiness index (DRI), should be instituted to manage the process.
The final step in the pre-migration process is to perform data mapping from the old data structures to the to-be structures in S/4. With this pre-work completed, the remaining activities during the project are limited to developing the conversion process (business rule analysis), testing the conversion process (data transformation and remediation) and the conversion execution (data load) significantly reducing the overall workstream risk.
After go-live, it is of paramount importance to ensure that data governance processes are in place to maintain quality data moving forward.
Whether the organization is coming from ECC or a non-SAP legacy environment, it is cheaper and simpler to address data readiness before the project begins and will set everyone up for a successful S/4 project.
Additional reporting by Don Loden, managing director and Chris Hanson, director and Rohan Bhatia, associate director