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Activities 2.1–2.5 — Define, Assess, Align & Strategize

The 17 numbered activities form a structured body of governance work. Do not memorize them as an immutable one-time waterfall. Chapter 3 also emphasizes tailoring, iteration, incremental rollout, culture, maturity, funding and changing priorities.

2.1 Define Data Governance for the Organization

Clarify: - what is governed; - who/what parts of the organization are governed; - who governs; - enterprise scope and meaning of Governance.

Purpose: prevent governance from being an ambiguous slogan.

2.2 Perform Readiness Assessment

Ask “Can we adopt governance?” across four lenses:

Readiness area Diagnostic question
Data Management maturity What capabilities/capacity exist now?
Capacity to change Can people adopt required behavior changes? Where is resistance?
Collaborative readiness Can the organization work across functions?
Business alignment Are uses of data aligned with business strategy?

Readiness is about adoption capacity, not the business-problem inventory.

2.3 Perform Discovery and Business Alignment

Ask “What must governance solve, and why?”

Assess: - existing policies/guidelines/practices; - Data Quality and recurring issues; - risks and pain points; - benefits/opportunities; - governance requirements tied to measurable business value.

Readiness vs Discovery

  • Readiness: can we change/adopt?
  • Discovery: what problems/benefits/requirements justify governance?

Business alignment appears in both, but in different ways.

2.4 Develop Organizational Touchpoints

Governance should connect to normal enterprise processes instead of operating as an isolated council.

Major Chapter 3 touchpoints include:

  • Procurement/Contracts: standard data clauses for cloud/outsourcing/data purchase/sale/licensing, rights, retention and vendor handling.
  • Budget/Funding: reduce duplicate data acquisition and optimize shared data assets.
  • Regulatory Compliance: monitor obligations/impacts.
  • SDLC/Development: insert policy, standard, system-of-record, architecture, Data Quality and regulatory requirements early in planning/design.
  • Data Quality / Architecture: coordinate decision rights with quality and enterprise structure.

2.5 Develop Data Governance Strategy

Produce four distinct deliverables:

Deliverable Question answered
Data Governance Charter WHY? Drivers, vision, mission, principles, readiness/discovery context, current issues, success.
Operating Framework & Accountabilities WHO/HOW? Bodies, roles, responsibilities, interactions, issue paths.
Implementation Roadmap WHEN? Timeframes, sequencing and dependencies for rollout.
Plan for Operational Success HOW IT ENDURES? Target state for sustainable ongoing governance.

Memory hook: WHY → WHO/HOW → WHEN → STAY.

Source anchors: Chapter 3 pp. 81–86; Figure 18.

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