Data governance can ensure quality, prevent compliance issues, and deliver better business results. Conversely, poor data hygiene can damage a business in today’s data-driven world. Unfortunately, some enterprises are failing with their data governance programs.
Why does this happen? Let’s explore the top five reasons and areas that can impact your data governance program and what you can do about it.
What and Why of Data Governance
Data governance pertains to managing and controlling data via a data governance framework and rules, including data policies, protocols, and guidelines. A robust data governance program’s primary goal is to ensure data integrity, security, and quality while staying compliant with government regulations.
Top Five Reasons Why Data Governance Programs Fail
Here are the top five reasons why data governance programs fail.
Poor Understanding and Inadequate Preparations
One of the leading reasons why data governance programs fail is because enterprises approach data governance with a poor understanding of what it is and what needs to be done.
What most enterprises fail to understand is that data governance should be viewed as a program that supports the day-to-day running of a business and not as an additional overhead or cost burden.
The best approach is to start small and slow and scale up with your data governance program. Enterprises can begin by focusing on one type of data and its life cycle and concentrate on its management from beginning to end. Be clear about assigning roles and responsibilities in data management.
Look at common and specific areas of trouble and the areas that can cause the most damage when testing and validating data instead of attempting problem-solving on a comprehensive level.
Consider adding new testing and approval processes as you move along. You can then expand your tech and processes to different data types.
Lack of Support from Senior Management
Unless the entire management is on-board with the implementation of a data governance program, failure is inevitable. Data governance should not be considered an overhead or a waste of time. However, in several cases, the senior management of a business views data governance only in terms of cost to the company.
So, in addition to implementation issues, due to additional costs associated with upgrades or necessary critical improvements, senior management may decide to shelve the program or shut it down completely.
Given that compliance regulations such as GDPR justify data governance programs as essential, senior management will have to seriously consider allocating long-term resources to cover the different data governance functions and roles on an ongoing basis.
Data Governance in Silos
Data governance is an enterprise-wide endeavor – so unless every department, including the IT department, communicates with each other, data governance will fail.
New data governance solutions and initiatives will have to be included on an ongoing basis. Expanding governance will require the support and cooperation of every department and employee involved in the data governance process. Inclusive efforts will also require that each department work on its own goals and targets in addition to the overall goals of effective data governance. Furthermore, these goals and targets should be effectively captured and the responsibility shared for all successes, gains, or failures if they happen.
Lack of Clarity on Goals and Poor System of Reporting
Specifying goals for your data governance program can be the difference between the program succeeding or failing. Your data governance program can have multiple goals such as cost savings, reduced internal errors, improved compliance, etc. Capture all data about your data governance program goals and targets, so you know where you are going with your program and judiciously compare the data to see if it is helping you achieve your overall business goals.
In addition to constantly monitoring your targets, you must share the results with all stakeholders in your data governance program to boost collective ownership and continued interest in the success of your program.
Failure to Identify Responsibilities Assign Roles
The success of your data governance program will largely depend on the teams assigned with the requisite roles, responsibilities, and authority. Lack of clarity in the duties and deliverables can cause your data governance program to fail.
Establishing data ownership is necessary at different stages or levels of your data governance program. The broader team must know who is responsible for making changes, who is responsible for approving those changes, who can access which data type, and who is responsible for ensuring or maintaining data quality and security. Each of these roles and responsibilities should be laid out and defined within the organization’s structure.
The Bottom Line
Data governance has become essential given the increased government scrutiny and the need to ensure complete regulatory compliance. As enterprise data evolves and new data challenges arise, the risks in data management are bound to grow. DataGovOps is an emerging operating model that ensures your business is prepared and armed for the upcoming data challenges by focusing on implementing a robust data governance program in your data management and storage.
