Establish data, information, and analytic governance
How establish data, information, and analytic governance are reshaped as AGI capability advances.
The bottom line
Roughly 90% of the work in Establish data, information, and analytic governance is information-shaped — already within reach of AI delivery. The question here is not whether it shifts, but which tasks go first and who staffs the residual.
Why: Derived from the APQC lens 'Manage information' and the process description, which centers entirely on creating guidelines and defining governance for IT and analytics. This is pure knowledge work consisting of policy creation and data management, mapping to a high digital scalar.
grounded in the economy graph · digital scalar 0.90 · digital
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How the work flows
Trigger: An organizational mandate requires standardized control, security, and quality standards for enterprise data and analytics.
- Assess current data architecture and identify governance gaps
- Define data domains, definitions, and ownership structures
- Establish data quality standards and usage policies
- Implement an operating model for data stewardship and issue resolution
- Deploy governance tools for data catalogs, lineage, and access control
- Communicate guidelines and train employees on data compliance
- Monitor governance adoption and enforce policy compliance
Outcome: A formalized governance framework is implemented, complete with data stewards, defined policies, and quality tracking mechanisms.