- Six layers (added Evidence between Observation and Finding):
1. Reality
2. Observation
3. Evidence (linked observations with context)
4. Finding
5. Decision
6. Business Impact
- Decision Object restructured:
1. Decision — what should user decide?
2. Why — why system recommends this
3. Evidence — what observations support this
4. Confidence — how certain (3 dimensions)
5. Consequence — what if nothing done
6. Action — next step
7. Business Impact — economic/operational meaning
- Confidence Model (3 dimensions):
- Observation Confidence: how certain is detection?
- Evidence Strength: how strongly supported?
- Recommendation Confidence: how certain is recommendation?
- Explainability Principle:
- Every Decision Card must be explorable
- User can click: Decision → Finding → Evidence → Observations → Reality
- Competitive advantage: traceability to source material
- Business Impact Model (4 dimensions):
- Risk, Cost, Time, Opportunity
- Three validation scenarios:
1. Road Crack — simple, common
2. Damaged Facade — complex, critical
3. Broken Road Sign — simple, regulatory
- Pass criteria: Same Decision Object works for all three
Rationale: Decision Intelligence, not BI. Evidence-backed decisions
are the core product. Explainability is competitive advantage.
Validation against real scenarios before freezing.
Bernt