In our previous blog post, we discussed data governance and when it is needed (or not). Today, we’ re going to delve in deeper on the goals of data governance.
Data Governance Goals
Every structured system helps us organize how we think and communicate about complicated or ambiguous concepts. The use of a formal framework can benefit all stakeholders, from managers to IT staff, data management and other disciplines, to come together to meet an end.
The use of a formal framework can encourage management and staff in general to make good decisions. It can help them reach an agreement about how to decide. In this way, rules can be created more efficiently, ensuring that rules are followed, and dealing with ambiguities, problems, and breaches.
The typical objectives of a data governance program are:
- Support better decision making
- Reduce operational friction
- Protect the needs of staff with interest in the data
- Train management and staff in general to adopt common approaches to data problems
- Build standard processes
- Reduce costs and increase efficiency by coordinating efforts
- Guarantee the transparency of the processes
It is likely that there are other objectives in your company, depending on the focus of your program. Some of these objectives will deal with the infrastructure and culture of the company in general, such as the identification of staff interested in the data and their specific value propositions.
But you have to handle expectations and goals with care. You have to be realistic to identify all those interested in a topic that is being examined by a data governance team, but it is possible that your resources may not be able to perform a thorough analysis of the problem, to analyze the processes and technology that is associated, or to recommend solutions. If your program is dependent on the resources of other groups to carry out activities for which your group is limited to facilitating monitoring, you should be clear about that.
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