For organizations to have reliable, understandable, and easy-to-find data, they need to manage their data effectively. Therefore, a data governance strategy that sets a standard for how data should be handled within the organization should be an essential part of every business. A crucial objective of implementing a data governance strategy should be to align the benefits of such a strategy with the business objectives of senior stakeholders. Establishing this sponsorship early on allows for a clear and concise approach to be communicated across the business.
When explaining the benefits of data governance, ensure the response consists of two outlooks. The first is that data governance is a necessary function to help businesses comply with external regulations by confirming that data is being effectively managed to a given standard. The second, which is often overlooked, is that it is fundamental in enabling organizations to make more reliable decisions.
Any data governance capability should be based on the objective of increasing the value of the data that an organization owns. This focuses the function of data governance to align with the business.
If your organization values your data as a strategic asset and hasn’t yet implemented data governance, I suggest you consider what value you could create by having more accurate, better-suited data—and how that will allow you to further help your customers. Tom White, Data Management consultant
Once sponsorship has been obtained, you can start to build out the strategy and focus on areas that will be most beneficial. As part of my Business Data Analyst development program, I have considered various elements of data governance at different points of the data lifecycle. For me, some of the most applicable and essential points for organizations to implement are:
Data Quality
A data quality program focuses on assessing the current state of data within an organization and identifying ways to correct errors to improve its overall value. This delivers significant added value for the organization and enables users to trust the data, which, in turn, drives an increase in data-driven insights across the company.
Roles and Responsibilities
To ensure that a governance framework is effective, there must be clear ownership within an organization. This ownership will provide the level of responsibility required to ensure data issues are resolved quickly and effectively.
Governance Tools
In my opinion, integrating a data governance tool to visualize data lineage and simplify workflows that help resolve data issues should be considered for all data governance frameworks, as these tools ensure business users get the most benefit from a governance initiative.
When implementing a data governance strategy, it is important to remember there are several common mistakes that can be more of a hindrance than a help, these are the don’ts. The following should always be remembered:
Stakeholder buy-in: Like most business initiatives, data governance needs to be implemented top-down. Without a senior sponsor, processes will not be followed and tools will not be effectively adopted by the business.
Business orientation: Whenever a decision is made, you must ask the question, “How is this valuable?” Without considering this, you may be building a framework that will never be implemented by the business. If the answer is complicated, consider how to break it down and explain it to various stakeholders before making the decision.
Treat data governance as a project: To ensure data is effectively understood, trusted, and leveraged within an organization, data governance should be a continuous and well-established process. A structured approach to embedding a governance framework needs to be implemented to allow for continuous ownership as new data enters the organization.
In addition to avoiding these common mistakes, organizations should further consider the challenges around data governance engagement across the business. Two common challenges are:
Embedding responsibility: If there is no stewardship currently in place, it will take time to engage relevant stakeholders to ensure data stewards and owners are established. Once in place, measuring how they are accountable for data quality is the next step to promoting a healthy data culture. All of this requires senior stakeholder engagement to support effective implementation.
Resource allocation: Ultimately, organizations will need to set aside resources to enable these changes. Often, governance programs are established within existing IT departments that have their own data initiatives to execute, leading to governance priorities not being addressed. Ideally, a data governance team should be separate from those functions with executive buy-in. This will ensure people are dedicated to making changes and have the authority to make the required decisions.
By implementing an effective data governance program, you will make your data more fit for purpose and provide data owners the clarity they need to do their jobs effectively. If your organization values your data as a strategic asset and hasn’t yet implemented data governance, I suggest you consider what value you could create by having more accurate, better-suited data—and how that will allow you to better serve your customers.
