Mettre en place une gouvernance des données

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 modèle, 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 politique is the foundation for Data Governance.

  • Politique address how data is gathered, maintained, delivered and utilized. For politique to be effective, it must be enforced and made auditable across the entreprise. The data management initiative drives effective politique 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

Le modèle de fonctionnement must be implemented and deployed to ensure that the data management principles are fully defined, adopted and adhered. The modèle provides structure for managing the activities of the fonction de gouvernance des données. The modèle defines the controls, checkpoints, and tollgates required to establish formal approval processes for the program.

Monitor and Measure

A formal processus 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 cohérence with organization politique 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 politique 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 clients, acceleration of business, operational risk, etc.


Revision History

DateAuthorDescription
September 2018Mark McQueenInitial Publication
March 2020Mark McQueenKnowledge Portal Release

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