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Data readiness assessment

Template id: data-readiness-assessment

Responsible skill: data-governance:data-product-readiness. Quality, classification, access and lineage results come from data-governance:ai-data-quality, data-governance:data-classification-for-ai, data-governance:ai-data-access-model and data-governance:ai-data-lineage.

Every fact the organisation must supply is marked [To confirm: ...]. Example rows are fictional. Readiness is assessed for a stated AI use, not for all uses, and the verdict is ready, ready with conditions or not ready.

1. Data product and use

FieldEntry
Data product name[To confirm]
Type (curated tables, semantic model, dataset, other)[To confirm]
Location and platform[To confirm]
Data owner (role)[To confirm]
Business owner (role)[To confirm]
AI use: questions or tasks, audience and route[To confirm]
Risk tier of the AI use[To confirm]
Assessors and date[To confirm]

2. Criteria

CriterionMet / Partly / Not metEvidenceCondition or fixOwnerDue
Ownership accepted for AI use[To confirm][To confirm][To confirm][To confirm][To confirm]
Purpose fit for the AI questions[To confirm][To confirm][To confirm][To confirm][To confirm]
Meaning: descriptions, units, synonyms, definitions[To confirm][To confirm][To confirm][To confirm][To confirm]
Quality of critical fields against requirements[To confirm][To confirm][To confirm][To confirm][To confirm]
Currency: refresh pattern and data age shown[To confirm][To confirm][To confirm][To confirm][To confirm]
Classification with AI-use rules applied[To confirm][To confirm][To confirm][To confirm][To confirm]
Access pattern approved; outputs within entitlement[To confirm][To confirm][To confirm][To confirm][To confirm]
Lineage at the depth the tier needs[To confirm][To confirm][To confirm][To confirm][To confirm]
Change commitment to dependent AI solutions[To confirm][To confirm][To confirm][To confirm][To confirm]
Test questions run with accepted answers[To confirm][To confirm][To confirm][To confirm][To confirm]

3. Test questions

IDQuestion as users would ask itAccepted answer (from business owner)AI answerCorrect?Cause if wrong
Fictional example Q1How many open cases are older than 30 days in the north region?Fictional example: 42Fictional example: 57NoClosed-pending status counted as open; description added
[To confirm][To confirm][To confirm][To confirm]Yes / No[To confirm]

Acceptance threshold agreed with the business owner: [To confirm]

4. Verdict

FieldEntry
VerdictReady / Ready with conditions / Not ready
Conditions and dated fixes[To confirm]
Re-assessment triggers (structural change, new AI use, quality breach)[To confirm]
Next review date[To confirm]
Data owner acceptance (role and date)[To confirm]

Credit: Template from CopilotForge by Simon Foote (https://github.com/SimonFoote-greensparx/CopilotForge), licensed under CC BY 4.0. Keep this credit when you share or adapt the template; in your own completed document you may keep it as a footer or remove it.

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