Branch Business & Information Systems Engineering

The quality of master data is a critical success factor for companies, yet faulty material master data often hinders the efficiency and automation of business processes. To tackle this challenge, SAP is leveraging innovative data-driven approaches. In a joint project, the potential of combining algorithmic methods with domain expertise is being explored to identify and resolve quality issues in material master data. The solution aims to enable companies to achieve significant process improvements and drive operational excellence. 

In an increasingly digital business environment, the quality of material master data plays a pivotal role in automating and optimizing enterprise processes. Inaccurate or inconsistent data often results in time-consuming workarounds, manual rework, and inefficient workflows. To address these challenges, SAP has launched an innovative project in collaboration with the Branch Business & Information Systems Engineering. The initiative focuses on the systematic identification and quantification of quality issues in material master data.

Using SAP Signavio Process insights, large volumes of material master data are analyzed to uncover common patterns and parameter configurations. By applying algorithms and a human-in-the-loop approach, companies are empowered not only to assess the quality of their data but also to derive concrete recommendations for improvement.

A central element of the project is the development of a functional prototype solution. This solution provides an automated approach to detecting quality issues, assessing their impact, and proposing targeted corrective actions. Key project milestones include defining success criteria for the prototype, developing personas to reflect diverse stakeholder perspectives, and identifying suitable metrics to be applied to sample and customer data.

Initial evaluations conducted with SAP experts and customers confirm the high relevance of the topic and the practical applicability of the proposed metrics. The prototype not only analyzes the current status of material master data but also highlights long-term improvement potential through data quality measures. With this project, SAP is laying the foundation for data-driven optimization of material master data and delivering a scalable solution that can benefit a wide range of companies.