SAP-Solution: Datenqualität

Valid financial figures and realistic forecasts are a top priority for companies. If you want to meet this demand, you have to establish end-to-end processes and ensure that everything meshes when it comes to automation.

Streamlining processes, cutting out old habits, and using new technologies and innovations - these are the typical leitmotifs for the changeover to S/4. In particular, the question arises here of how to proceed with CRM after the changeover.

Although the change to S/4 is inevitable, many companies are still hesitant. One reason for avoiding the transformation could be the high number of master data with poor data quality in the various data silos.

Corporate data can be the new gold. In any case, poor data management causes high costs - regardless of whether an S/4 release change is pending or not. Stefan Riess and Hendrik Becker talk about data quality and what companies can do to safeguard it.

Industry 4.0 digitization projects place high demands on data quality. These can be met in three consistent, successive steps. In the process, more efficient tools should complement the ERP system.

Up-to-date data, fully automated processes, seamlessly connected customer/supplier pipelines—for many companies, digital transformation still seems like a faraway future. Digitalization in procurement has to start at the top.

It is often not clear how IT managers are to make the switch to S/4 in concrete terms and what happens to the legacy systems. The question of data quality and data reduction is also often neglected.

Many software providers offer "something with AI". Most of the time, these are announcements or explanations of what AI should be able to do at some point in the future. A lot of effort and (learning) experience is needed to make AI practical.

A successful, cost-efficient and mostly effortless migration to S/4 Hana does not start with the migration per se. It starts with the architecture of the application landscape.

For companies to be able to develop and test digital offerings under realistic conditions, they need real information assets as a basis, i.e., productive data from SAP systems. In practice, however, administrators will hesitate to copy complete production data sets.

In its "Digital Strategy 2025," the German government identifies data as the central raw material of the digital transformation. In the long term, key competencies will lie in the collection, processing and protection of data, as well as in the derivation of concrete measures and methods.

In its "Digital Strategy 2025," the German government identifies data as the central raw material of the digital transformation. In the long term, key competencies will lie in the collection, processing and protection of data, as well as in the derivation of concrete measures and methods.