Best Practice Scribes
Mark McQueen, EDM Council, Senior Advisor-DCAM
Although this may differ from organization to organization, there are generally four steps that are needed to establish an effective data governance initiative.
Establish the Governance Structure
The governance structure objective is to identify and organize the critical stakeholders and link them to the necessary data management support components. The organization needs a formal deployment plan to ensure that the governance structure, organizational model, and oversight mechanism will work within the business environment. Interacting with executive management to ensure that adequate funding for data management is in place is critical to ensure that governance is successful.
Implement Policy & Standards
Formalizing policy is the foundation for Data Governance.
- Policy address how data is gathered, maintained, delivered and utilized. For policy to be effective, it must be enforced and made auditable across the enterprise. The data management initiative drives effective policy in collaboration with technology and business.
- Standards address uniform data alignment to common meaning, structure, and identification. Firms can align to internal standards (i.e.: for expediency or when industry-wide standards are not mature) and/or to external standards for broad comparability across many participants. Standards are often defined and driven by technology and business subject matter experts, coordinated through the Office of Data Management at all levels of the organization.
Develop the Governance Operating Model
The operating model must be implemented and deployed to ensure that the data management principles are fully defined, adopted and adhered. The model provides structure for managing the activities of the data governance function. The model defines the controls, checkpoints, and tollgates required to establish formal approval processes for the program.
Monitor and Measure
A formal process for adequately monitoring and measuring the effectiveness of the data management initiative must be deployed to ensure the program is meeting its stated objectives. The initiative must be evaluated to ensure ongoing consistency with organization policy and alignment with business strategy. Continuously measuring the data management initiative is essential. Metrics-based measurement criteria should be developed and used to track the progress and health of the initiative. Measurement criteria can include areas such as: measurement of compliance to policy and standards; the cost of correcting mismatches on trade repairs, the time spent on reconciliation, consolidation and better use of existing data sources, reduction in the number of transformations, consolidation of redundant systems, responsiveness to customers, acceleration of business, operational risk, etc.
Revision History
| Date | Author | Description |
| September 2018 | Mark McQueen | Initial Publication |
| March 2020 | Mark McQueen | Knowledge Portal Release |