Data Governance Program Metrics

To measure the effectiveness of your data governance program, you can track the following metrics:

• Data quality: Track metrics such as the percentage of complete and accurate data, the number of data errors, and the average time it takes to resolve data errors.

• Data security: Track metrics such as the number of security incidents, the average time it takes to detect and respond to security incidents, and the percentage of data that is encrypted.

• Data compliance: Track metrics such as the number of data compliance violations, the average time it takes to resolve data compliance issues, and the percentage of data that is compliant with all applicable regulations.

• Data accessibility: Track metrics such as the percentage of data that is accessible to authorized users, the average time it takes to access data, and the number of data access requests.

• Data governance adoption: Track metrics such as the percentage of employees who have been trained on data governance policies and procedures, the number of data governance processes that are in place, and the number of data governance audits that have been conducted.

• Data quality metrics: Track deficiencies found in accuracy, completeness, consistency, timeliness, etc. Declines indicate governance programs improving data.

• Policy adherence: % of processes, projects adhering to data policies shows employee conformance and awareness.

• Training completion: Measure % of employees completing data governance training programs as an adoption metric.

• Compliance violations: Decline in breaches, exposure incidents and policy infractions demonstrates controls working.

• Data accessibility: % of authorized requests for data fulfilled shows proactive governance enabling access.

• Issue resolution: Speed to resolve requests, disputes and fix errors indicates governance efficiency.

• Cost savings: Lower costs from less duplicate data, cleanup, scrapped projects due to governance.

• Risk reduction: Fewer compliance fines, incidents traced to better data hygiene.

• Business enablement: Faster analytic insights, algorithm performance due to reliable data.

• Stakeholder feedback: Surveys on data satisfaction, policy clarity, enforcement give qualitative insights.

• Benchmarking: Compare data governance metrics year over year or against industry standards.

You can also track metrics that are specific to your organization's data governance goals. For example, if one of your goals is to improve the efficiency of your data governance processes, you could track metrics such as the average time it takes to complete a data governance task and the number of data governance tasks that are completed on time.

In addition to tracking metrics, you should also conduct regular surveys of stakeholders to get their feedback on the effectiveness of your data governance program. This feedback will help you to identify areas where the program is working well and areas where it can be improved.

By tracking metrics and conducting surveys, you can get a comprehensive view of the effectiveness of your data governance program. This information can then be used to make informed decisions about how to improve the program and achieve your data governance goals. A combination of quantitative metrics and qualitative feedback will reveal how effective data governance policies, processes and controls are embedded and maturing across the organization. The key is tracking metrics consistently over time.

​Here are some additional tips for measuring the effectiveness of your data governance program:

• Set clear goals and objectives for your data governance program. This will help you to identify the metrics that you need to track.

• Establish a baseline for each metric that you are tracking. This will help you to measure your progress over time.

• Collect data on a regular basis. This will help you to identify trends and patterns.

• Analyze the data to identify areas where the program is working well and areas where it can be improved.

• Share the results of your analysis with stakeholders. This will help to get buy-in for the data governance program and to ensure that it is meeting the needs of the organization.

By following these tips, you can measure the effectiveness of your data governance program and make informed decisions about how to improve it.

​Here are some examples of how companies have measured the effectiveness of their data governance programs:

• Google measures the effectiveness of its data governance program by tracking the following metrics:

• Data quality: Google measures the accuracy and completeness of its data by conducting regular data quality audits.

• Data security: Google measures the security of its data by tracking the number of security incidents and the average time it takes to detect and respond to those incidents.

• Data compliance: Google measures its compliance with data privacy and security regulations by conducting regular compliance audits.

• Data accessibility: Google measures the accessibility of its data by tracking the percentage of data that is accessible to authorized users.

• Data governance adoption: Google measures the adoption of its data governance policies and procedures by conducting regular surveys of employees.

• Netflix measures the effectiveness of its data governance program by tracking the following metrics:

• Data privacy: Netflix measures its ability to protect the privacy of its customers by tracking the number of privacy complaints it receives and the average time it takes to resolve those complaints.

• Responsible data use: Netflix measures its responsible use of data by tracking the number of data ethics complaints it receives and the average time it takes to resolve those complaints.

• Data governance awareness: Netflix measures the awareness of its data governance policies and procedures by conducting regular surveys of employees.

• Walmart measures the effectiveness of its data governance program by tracking the following metrics:

• Data quality: Walmart measures the accuracy and completeness of its data by conducting regular data quality audits.

• Data security: Walmart measures the security of its data by tracking the number of security incidents and the average time it takes to detect and respond to those incidents.

• Data compliance: Walmart measures its compliance with data privacy and security regulations by conducting regular compliance audits.

• Data accessibility: Walmart measures the accessibility of its data by tracking the percentage of data that is accessible to authorized users.

• Data governance adoption: Walmart measures the adoption of its data governance policies and procedures by conducting regular surveys of employees.

Sash Barige

Oct/24/2019

Photo Credit: Unsplash.com