Internal Data Governance – Part 3: The Seven Steps to Effective Data Governance

In this third part of the internal data governance series, we present the seven key steps that guide organizations toward an effective data governance framework.

1. Establish a Data Governance Organization

The first step is to evaluate various data governance models and select the one that best fits your organization. While roles differ across models, establishing ownership, processes, and procedures is universal. Common responsibilities include defining master‑data maintenance procedures, clarifying rules for business functions such as sales, procurement, and finance, specifying and developing tools that support master‑data maintenance, and supporting day‑to‑day execution of master‑data processes.

2. Identify Strategic Master Data Objects

Not every data element should be governed. Identify the data objects that require governance based on strategic importance to the company, global usage across the organization, impact of poor maintenance, data complexity, and whether maintaining the object is a core activity for its users.

3. Assign Ownership

Define clear ownership for each data element to eliminate confusion. Ownership can be global for strategic data objects and local for others. Ownership should be assigned for data fields, user guides, governance (definition and modification of field values), and technical aspects (adding, deleting, updating values).

4. Define Master Data Maintenance Rules

Document comprehensive maintenance rules, including field‑value rules across business scenarios, organizational dependencies, data cross‑dependencies, and configuration files (especially when automation tools are used) to simplify maintenance and improve consistency.

5. Establish Master Data Maintenance Procedures

Based on the documented rules, create procedures that guide data stewards on who maintains data, when and how often, the basis for changes, special requirements, organizational and functional differences, site selection, and field‑value specifics. Keep these procedures updated with business input.

6. Build Master Data Maintenance Tools

Develop or adopt tools that facilitate data maintenance, workflow approvals, bulk changes, regular health‑check audits, and overall compliance. Examples include SAP MDG, Itelligence it.mds, and SAP Information Steward.

7. Define Archiving Rules and Jobs

Complete the governance lifecycle by establishing archiving policies that specify which records to archive, criteria for deletion or inactivity, archiving frequency, storage locations, and retention periods. Proper archiving helps maintain system performance, reduce database size and maintenance costs, and simplify data search.

For more details, refer to the original article at https://architect.pub/7-steps-steer-you-towards-effective-data-governance-plan.