Migration to SAP S/4HANA: How companies ensure the best data quality in the new system

The migration to SAP S/4HANA cannot be delayed much longer. But before companies start the actual migration, they should take the time to check and clean up their data in the old system. This is the only way they can take full advantage of the new ERP system. We explain which analytics are advisable and how to perform these checks.
 

Why optimize data quality before migration?

The SAP S/4HANA data model (see past article) differs from the data models of older SAP ERP versions. To ensure that the migration of the previous master data to the new system runs as smoothly as possible, the quality of the data and processes should be optimal beforehand to avoid errors in data transfer to the new system. Instead of cleaning up the data stock at a later point in time, it brings both time and cost advantages to do this in advance and thus ensure the efficiency of the migration project.
 

What checks should companies consider before migration?  

Analyse the master data is a recommended first step. However, in addition to pure data, companies should also examine user processes and authorizations. 

Master data audit 

Over the years, data quality declines: test data enters the system, typing errors and new entries of already existing customer or supplier master data create duplicates. Some data records are incomplete but can easily be added manually. If you want to speed up the search for duplicates, erroneous data and incorrect data, you will find 15 different analytics in the dab:AnalyticSuite that display results for master data checks of customers and suppliers at the push of a button. 

A frequent indication of incorrect master data are outliers. However, it is not always easy to determine the right range of which values should be considered outliers. This is where artificial intelligence can help. dab:DEAN, for example, analyses data tables fully automatically and identifies outliers without users having to enter rules.

SAP authorization management 

To maintain the new data quality in SAP S/4HANA, SAP authorizations should be audited. Often, authorizations have not been revoked over the years or SoD violations have crept in. Companies need to define which authorization combinations are critical so that analytics identify appropriate profiles. If you're not sure whether you're capturing all the critical combinations, using AI can help to detect outliers.

Multiple relations

Previously, for different business relations with the same companies, the customer and supplier master data were stored in separate tables. For example, if a customer was also a supplier, the LIFNR field was filled with the supplier number in the customer table KNA1. Conversely, LFA1 was also filled with the LFA1_KUNNR field if a supplier was also a customer. 

In the new system, master data is only recorded in one table under the Business Partner category, where users can assign different roles to companies. To avoid duplicate master data being created in the new system, companies with multiple relationships must be identified beforehand.

Processes 

Evolved processes do not always run optimally. Before you transfer inefficient processes to the new system, analyse workflows using a process mining solution. Decide on the basis of facts how you can achieve shorter throughput times and lower error rates in the future with automations. 

You can minimize the effort for process analytics with dab:neXus and dab:AnalyticSuite. With these, you extract and transform SAP data into event logs in just a few steps. These can be forwarded to the process mining tool of your choice and analysed there.
 

Using the migration to SAP S/4HANA as an opportunity 

Every migration involves the risk of technical complications. Therefore: Prepare the migration to SAP S/4HANA sufficiently. Use the switch proactively to review your existing data, optimize your data management processes, and improve your data quality. 

After all, if companies want to compete with data-driven organizations, they need the best possible data quality. If you save the effort for optimization before migration, you will pay later with higher costs, for example, through double-booked invoices due to duplicates in the supplier master record.