February 21, 2011 // By: Marina Titova, Christoph Zeidler
SAP.info Interviews DSAG
Those involved in IT projects often only focus on data quality for specific purposes – when cleansing data during ERP migrations, for example. As soon as their systems are live, they tend to turn their attention to other matters.
Companies that neglect data quality management, however, soon find themselves working with inaccurate information. To find out how to do things right and what the advantages are, we sat down for a chat with Reiner Schaaf and Martin Nußbaumer, the spokesmen of the German-speaking SAP User Group’s work group for master data management, data quality, and data governance.
SAP.info: Your work group has been dealing with the topic of master data management in SAP products for many years, but you recently extended your focus to include data quality and data governance. Why are these subjects so important?
Reiner Schaaf: Generally speaking, every company collects and manages data; the better they do so, the more reliably they can control their business processes. High-quality data is essential for centralized reporting and consistent workflows, and if you’re looking to fine-tune your business processes to one another, there’s no way around master data management and the corresponding procedures, rules, and responsibilities.
Martin Nußbaumer: Improving processes is key. The resulting competitive advantage companies can gain enables them to respond faster both in and to the market – and benefit from their increased data quality in the form of fewer errors downstream.
SAP.info: How is your work group structured? How do your members approach your subject matter?
Reiner Schaaf: It’s very heterogeneous; our work group is a network platform that constantly evolves as it provides best practices and potential solutions.
Some companies are already using products in this field, while others are observing their experiences and trying to find their own orientation. This is why it’s important that our work group not focus too closely on particular products. Compared to larger midsize companies, which have an eye on the quality of their master data, it’s difficult to get smaller businesses interested in the subject.
In the case of the biggest corporations, meanwhile, implementations of master data management depend on their distributed IT landscapes and the wide variety of systems used for data storage.
Next page: Areas where companies need to take action