Data governance: Basic framework for master data management

Every company depends on using data and information profitably. Efficient master data management establishes company-wide standards and creates clearly defined, automated processes to ensure correct, reliable master data. A stable strategic foundation can provide the best possible support for the challenge of operational data management and maintenance. This foundation for master data management in the company is known as data governance.

Create the right framework for successful master data management

Data governance ensures that data is managed in a consistent and disciplined manner. The term describes a holistic system that determines, among other things, who in an organization has access and authorizations with regard to master data. Data governance extends to people, processes and the tools used for this purpose. It defines clear responsibilities, establishes data ownerships, ensures a stringent security concept, and appoints data stewards who are responsible for maintaining data quality and implementing the strategic requirements from a professional perspective. With these features, data governance not only helps companies in the present, but also enables them to solve future problems and challenges.

Goals of data governance

There are many goals associated with establishing data governance. For example, data quality and thus the value of master data for the company are to be continuously increased. Furthermore, data governance establishes clear rules for changing processes and data so that the company as a whole becomes more agile and scalable. The ability to reuse processes and data increases efficiency. At the same time, data governance increases confidence in data quality and data process documentation throughout the enterprise. Data regulations and legal requirements are easier to comply with and implement.

Relevant to every phase of a data record’s life

Data governance plays an important role in sustaining high data quality throughout the lifecycle of a master data record. This becomes clear when you consider the importance of data governance at each stage of the lifecycle.

Creating a data record

Even before a data record is created, data governance determines which roles must exist and which roles have which tasks. Based on previous experience, it shows how the processes can be optimized. In this phase, the basic structures are created to ensure that the entire lifecycle of a master data record runs successfully and the processes required for this are defined.

During the creation itself, data governance clarifies whether the data record is needed at all. In addition, it regulates the procedure for creation and determines the process participants. If problems arise, data governance helps to make the right decisions. And it provides answers to the question of how to document the process.

Changing a data record

If it is necessary to change a data record, the provisions of data governance determine who has the authority to do so. Planned changes are identified and the relevant decisions on these are sometimes made in advance. In the event of unforeseen events, data governance develops escalation paths and decision paths for resolution.

Deduplication of a data record

Duplicates in master data have a lasting negative impact on data quality. Data governance creates a suitable framework for deduplication, i.e., the identification and elimination of redundant data. This includes, for example, rules that define when a duplicate exists. It also specifies when duplicate checks should be performed – for example, before the data record is created or at regular cyclical intervals in order to keep data quality permanently high. Data governance also regulates the merging of data records: Which is the leading field? What information is transferred? Who has the decision-making power in the event of conflicts?

Locking a data record

Here, data governance determines the rules for a lock, who is involved in it, and how it proceeds in detail. It also helps identify critical cases where quick action is required – for example, an ad hoc lock when a supplier is no longer solvent. Who can unlock the data record in which situation is also specified.

Deletion of a data record

Data governance defines the rules for the correct procedure, outlines possible scenarios for deletion and determines the parties involved. It also clarifies who must be informed and what additional steps may be required. Data governance also regulates possible archiving of the data record and its history. Locking, deleting and archiving a data record are often closely related. Here it is necessary to decide whether the associated processes should be automated.

Reactivating a data record

Sometimes a data record needs to be reactivated (unmark for deletion). In this case, data governance clarifies the advantages and disadvantages of such a step compared to a new creation of the data record and thus provides the basis for deciding whether a new data record should be created. Among other things, the focus is on the questions of the authorized role, the other parties involved, and the documentation.

Structures for a dynamic environment

Data governance must prove its worth in a challenging environment in which the framework conditions are constantly changing. An enterprise is a dynamic organization with employees changing positions and tasks, as well as occasional restructuring. Consequently, it is important that data governance tasks are linked to roles and not to people. New rules of the game and legal requirements are constantly being added. Likewise, new IT systems are introduced and existing systems are dropped.

Accordingly, decision-making paths and structures must be established that allow the company to react to changing conditions. General rules for master data management in the organization help to maintain an overview and the ability to act. Data governance creates a holistic framework that enables the system to find solutions on its own, even in the event of changes.