Scenarios 16–20
Scenario 16 — Improvement During Assessment
Situation: during interviews the assessment team starts rewriting standards and workflows before current-state evidence collection is complete.
- Primary problem: assessment/remediation mixed.
- Leading KA: DMMA.
- Supporting: Data Governance; affected KAs.
- Roles: assessment team, process owners.
- Best action: finish defined assessment, interpret, then sequence improvements.
- Weaker response: fix immediately; changes the state being measured and harms comparability.
- Changed fact: assessment is complete and team is now in targeted improvement program → redesign is appropriate.
- Source: pp. 510, 514–516.
Scenario 17 — Roadmap Is a Wish List
Situation: recommendation says “improve governance, quality, metadata, security” but has no sequence, timeline, expected maturity movement, or oversight.
- Primary problem: roadmap lacks operational structure.
- Leading KA: DMMA.
- Supporting: Data Governance; multiple KAs.
- Roles: roadmap owners, executives, governance.
- Best action: add sequenced activities, timeline, expected capability/rating change, oversight, progress measures.
- Weaker response: topic list cannot allocate resources or track change.
- Changed fact: if this is merely executive directional summary and detailed roadmap exists elsewhere, the summary may be sufficient for that audience.
- Source: p. 515.
Scenario 18 — Reassessment Changed Scope
Situation: second DMMA reports +1 level but covers half the systems and different business units.
- Primary problem: trend comparability failure.
- Leading KA: DMMA.
- Supporting: Data Governance; metrics.
- Roles: assessment team, executives.
- Best action: qualify/redesign comparison; define parameters supporting meaningful trend.
- Weaker response: higher score automatically means improvement.
- Changed fact: framework-defined normalization/weighting validly accounts for differences → trend may be usable with documentation.
- Source: pp. 515–516, 519–520.
Scenario 19 — No Formal Data Governance
Situation: organization wants DMMA but has no formal Data Governance function.
- Primary problem: accountable oversight still required.
- Leading KA: DMMA.
- Supporting: Data Governance.
- Roles: initiating steering/management body, executive sponsor.
- Best action: assign oversight to initiating steering/management layer; secure sponsor.
- Weaker response: postpone all maturity work until DG office exists.
- Changed fact: formal DG established → normal oversight moves there.
- Source: p. 519.
Scenario 20 — High Score, Rising Manual Cost
Situation: DMMA ratings improve while employees spend more time manually reconciling data.
- Primary problem: maturity rating alone hides resource/value cost.
- Leading KA: DMMA.
- Supporting: Data Governance; operations; Data Quality.
- Roles: governance, finance, process owners.
- Best action: track resource utilization and spend/value beside ratings; test sustainability.
- Weaker response: celebrate score alone.
- Changed fact: manual effort falls while ratings/business outcomes improve → stronger evidence of sustainable progress.
- Source: pp. 519–520.