Data Governance is often thought of as "nice to have" rather than a crucial business function. Executives frequently put other topics on the list of priorities, but Data Governance is essential for an effective data-driven strategy.
Mar 19, 2019

Let's start with a quick definition. Data Governance is a collection of practices and processes that help ensure the formal management of data assets within an organization. It's a "must have" and it's crucial to your data-driven success. Without governance, an organization's entire data set and the decisions that come from it are built on a weak foundation. It's "quality control" for your data, and it empowers companies with reliable and consistent data to make the right business decisions. Companies with strong Data Governance models gain remarkable benefits like substantial cost and time savings and confidence in their data. The right governance program supports and complements your overall data strategy, and it's key to deriving value from data.

Data Governance helps organizations save money. When there is a lack of confidence or confusion about data's meaning, organizations often blame their tools or technology. These problems are frequently because of data governance issues, not because of the technology. As a result, they'll make the mistake of ripping out and replacing functional systems. This is a massive waste of time and money. Data Governance also helps to save money because it minimizes data duplication and reduces duplicate management efforts. With better quality data, companies understand their data, avoid errors, increase data efficiency, and bring costs down.


In addition to saving money, governance can also help to generate new revenue. Having a firm grip on how you define core metrics and your targets, segments, and customer attributes, helps you better understand your data, which means a better understanding of customers. That's key to generating revenue.

Data Governance also ensures that data is reliable, consistent, and repeatable. Effective governance leads to a clear understanding of what metrics mean, which metrics are most important, and where there might be gaps and risks. With this clarity, organizations have the confidence to make data-related decisions quickly. Being data-driven is about generating and acting on insights in real-time, and data governance builds the confidence needed to get closer to that goal.


Compliance and ethics are also a factor that cannot be forgotten. There are growing legal and financial consequences for the mishandling of the collection, storage, and data use. Poor data management can lead to fines, upset customers, and a bad corporate reputation. Strong governance models ensure that these issues are avoided by following relevant privacy and security policies.


Conclusion:
A robust Data Governance model gives your organization access to quality data and empowers it to turn data into actionable insights. Although governance may not be a trending topic within your team, it's crucial to data-driven success, and it needs to move to the top of the list of priorities for executives..

You're one step closer to enabling a data-driven organization.

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