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Conducting business in the digital age shifted many of the fundamental concerns of the internal operations of an organization. Among the most crucial was how organizations approached data. Time and again the value placed on this aspect of business has proven to be an ultimate determiner of success. Even today, businesses still striving to find optimal approaches to the flow of data in a rapidly advancing business world.
What is Data Governance?
To understand what is data governance one must completely understand the principles and practices that govern data. Governance will only be as good as the quality of its implementation throughout an operational life cycle. A high standard must be maintained throughout. Consistency is also an imperative. In whatever way an organization chooses to define its data governance, it must consider all aspects of management involved in the flow and security of high quality data.
The Data Governance Framework
A data governance framework is an established set of rules outlined by an organization. It is less philosophical and more concerned with ensuring a plan of action. Framework processes target the entirety of an organization in terms of the flow of data. It also defines roles throughout an organization. Assigning duties to team members under the direction of the governance office is a good example of a framework process. Because every organization has unique problems, many different frameworks exist.
Data Stakeholders
Broadly speaking, several parties will maintain a vested interest in an organization’s data. Obviously the owners of data will have the most stake since they will be ultimately accountable. A committee is often used to set governing policies, establish standards, and mitigate the impact of issues that may arise. Stewards and custodians will ensure the flow and care of data assets. A dedicated governance office and team is often important to support the vested parties. Teams should be comprised of management, oversight, analysts, strategists and compliance specialists.
Improvement Opportunities for Businesses
Action oriented governance plans can be based on tangible outcomes. However, data planning will tend to be geared toward either growth or meeting regulatory requirements. In either case, data is essential for decision making. The most pressing concerns include:
- trust within a system
- documenting the lineage of records
- ownership security
- verifying distribution
- assigning responsibility
- establish quality thresholds
- monetizing data
- eliminate redundancies
- evaluate appropriately
The outcome of each of these aspects can benefit or limit operations. How much each affects an individual organization should be weighed carefully.
3 Tips for Better Governance
There are several expectations that can be drawn from an action plan. Three of the most important areas to focus upon are:
- Limit mistakes of business outputs by solidifying data practices from the start.
- Optimize staff roles through proper assignment and emphasizing quality.
- Verify and evaluate data for optimum practices that ensure an action plan.
Improving an organization’s approach to data can instantly improve business operations. These are just a few recommendations, but every business will need to tailor a plan of their own.
Conclusion
Data governance is a funnel point for the outcome of business operations. By increasing operational efficiency and improving analytics, governance allows for better decision making. This benefits market positions, consumer confidence, reputations, and the bottom line. Establishing a high level of governance for an organization’s data is a fundamental aspect of every business.
