Data Governance – the Key to Improved Data Quality

Study by the University of St. Gallen on corporate data quality management

With corporate master data management, data not only has to be maintained but also has to undergo quality inspection. This is where data governance comes in. A study by the University of St. Gallen in Switzerland confirms its benefit for strategy and operations.

The ability to access consistent, reliable, and up-to-date data at any time and from any place is crucial in today’s fast-paced business world. Solutions such as SAP NetWeaver Master Data Management (SAP NetWeaver MDM) are deployed to maintain data in master data management. SAP NetWeaver MDM consolidates, synchronizes, distributes, publishes, and manages master data from IT systems both within companies and with business partners across company boundaries.

This gives organizations a standardized view of all strategic data, enabling them to make informed decisions. The task of data governance is to specify roles and responsibilities and to define standards and guidelines for data quality management (DQM).

Better quality, lower costs

With a team led by Dr. Boris Otto, the Competence Center Corporate Data Quality (CC CDQ) of the Institute of Information Management at the University of St. Gallen investigated corporate data management. Also involved in the study were the Institute of Information Systems of the University of Hamburg, Germany, headed by Prof. Stefan Voss, plus the German-speaking SAP User Group (DSAG) and the SAP consulting unit SAP Business Transformation Consulting. Companies from different industries and of different sizes participated in the study.

And what did the team discover? Data governance combined with DQM results in better quality data. In addition to ensuring that business processes are aligned, DQM saves costs – because there are no more multiple entries and processes do not have to be repeated (for example, in the search for data). Nevertheless, the benefit of data quality initiatives is seldom measured.

Roles and responsibilities

The main drivers for active DQM are the integration and harmonization of business processes. In practice, however, the topic is still largely overlooked. Only 17 percent of the companies surveyed have implemented data quality management measures. However, 75 percent of them plan to make greater investments in DQM initiatives in the next few years.

The responsibilities connected with DQM comprised a key focal point of the study. The team of experts and academics identified five roles with specific tasks:

• Data quality committee: Responsible for data quality strategy. The committee defines DQM initiatives, plans their implementation, and reconciles DQM goals with corporate objectives.
• Corporate data steward: Defines the key performance indicators and measurement methods for DQM and is responsible for quality standards, processes, and guidelines.
• Specialist data steward: Implements the measures in user departments and business areas. Also defines data management, data maintenance processes, and business metadata.
• Technical data steward: Implements authorization system; defines technical metadata and system architecture.
• Sponsor: Is involved in defining a DQM strategy.

SAP NetWeaver MDM helps companies to execute the many data governance tasks.

Functions of SAP NetWeaver MDM for data governance

• Defines clear rules for tables, fields, and properties in the databases
• Ensures data quality with many functions
• Simple mapping of data administration using a role model
• Simple development of workflows for efficient business processes and compliance