Data governance involves defining roles, responsibilities, policies, standards, and procedures for data collection, storage, analysis, and sharing. But how do you audit and review data governance to ensure that it is effective and aligned with your business goals and regulatory requirements? Here are some key steps and best practices for conducting data governance audits and reviews.
Assess your current level of data governance maturity, which is the degree to which your organization has implemented data governance principles and practices. Use a data governance maturity model, such as the one developed by the Data Governance Institute (DGI), to evaluate your performance across different dimensions, such as data quality, data security, data architecture, data literacy, and data governance organization. A data governance maturity assessment can identify your strengths and weaknesses, as well as the gaps and opportunities for improvement.
Define the specific goals and measures that you want to achieve and monitor through data governance. Your objectives and metrics should align with your business strategy and stakeholder expectations, as well as the industry standards and regulatory frameworks that apply to your data. Possible goals could include to improve customer satisfaction, reduce operational costs, comply with data privacy laws, or increase data innovation. Also establish the baseline and target values for your metrics, as well as the frequency and method of reporting.
Define the scope, criteria, and methodology of your audit, as well as the roles and responsibilities of the audit team and the auditees. Collect and analyze relevant evidence, such as data governance policies, standards, procedures, documents, records, reports, interviews, surveys, and observations. The purpose of your audit is to verify the compliance and effectiveness of your data governance, as well as to identify any risks, issues, or non-conformities.
Prepare a clear and concise audit report that summarizes the objectives, scope, criteria, methodology, evidence, results, and recommendations of your audit. Also communicate your audit results to the relevant stakeholders, such as the data governance council, the data owners, the data stewards, the senior management, and the external regulators. Use appropriate channels and formats to deliver your audit report and feedback, such as presentations, meetings, emails, or dashboards.
Incorporate the actions and improvements that you suggest to enhance your data governance. Prioritize and assign your recommendations based on their urgency, impact, feasibility, and cost. Define the roles, timelines, resources, and deliverables for implementing your recommendations. Monitor the progress of your recommendations, as well as report them to the stakeholders. Evaluate the effectiveness and sustainability of your recommendations, as well as the lessons learned and best practices.
Periodically review your data governance framework periodically or whenever there are significant changes in your business environment, stakeholder expectations, or regulatory requirements. Also update your data governance framework based on the feedback and insights from your data governance audits and reviews, as well as the emerging trends and best practices in data governance. This ensures your data governance framework remains relevant, effective, and adaptable.
The article seems to bounce between overall data governance applications & purposes to evaluation of the data governance framework. Is the goal of this to define: 1. the pillars of data governance and their application to data management, or 2. the evaluation of an entity’s process for auditing the effectiveness of data governance?