As mentioned in my post describing the major business processes that comprise a data governance function, the Measure and Monitor processes i) capture and measure the effectiveness and value generated from data governance and stewardship efforts, ii) monitors compliance and exceptions to defined policies and rules, and iii) enables transparency and auditability into data assets and their life cycle.
The most relevant processes that comprise the Measure & Monitor stage include:
Proactive Monitoring. Proactively monitor data quality or compliance exceptions as they are identified in real time as transactions and interactions are captured, in order to more quickly identify and mitigate critical issues that can cause costly process breakdowns.
Data Lineage Analysis. Perform root cause, impact and data lineage analysis of data throughout its lifecycle.
Reactive operational DQ audits. Provide data stewards with visibility to reactively mitigate any data quality-related issues routed to them through predefined stewardship workflows implemented in the Apply process stage.
Dashboard monitoring/audits. Data monitoring acts as an early warning system for catching data quality, security or privacy compliance problems before they wreak havoc on your dependent applications, reports, and processes. Combined with facilities to report on the state of data quality or data security problems, data monitoring ensures the right level of checks and balances are in place to quickly react to changes as needed.
Program Performance. Measure performance of the data governance efforts itself. For example, measure the number of lines of business, functional areas, system areas, project teams and other parts of the organization that have committed stewardship resources or sponsorship. In addition, categorize and track status of all issues that come in to the data governance function, and capture all other types of value-added interactions such as training, consulting and project implementation support.
Business Value/ROI. Measure business value from data governance investments ranging across a variety of benefits and can include, among others, reducing penalties by ensuring regulatory compliance; reducing enterprise risk (e.g., contractual, legal, financial, brand); lowering costs (e.g., business, labor, software, hardware); optimizing spending (e.g., procurement, supply chain, services, labor); improving operational efficiencies (e.g., employee, partner, contractor); increasing top-line revenue growth; and optimizing customer experience and satisfaction.