FP&A Context Explorer
Business ontology, financial truth, external signals, and trust posture for one forecast decision
Live trust drill
Context explorer
Explain the business situation
Context Explorer
Use this page when the room asks, “What knowledge exists inside Sphere?” The answer must show internal finance truth, external signals, business ontology, policies, historical decisions, and trust posture for one concrete forecasting problem.
Upstream Revenue Variance Context Stack
This is the object-level view the room expects to inspect before trusting the narrative or the forecast.
Internal Finance Truth
- Actual revenue
- Plan revenue
- Budget
- Prior year
- Close snapshot
- Flash estimate
External Signals
- Brent strip
- Natural gas index
- LNG demand
- FX
- Freight pressure
- Outage watch
Business Knowledge
- Asset hierarchy
- Segment hierarchy
- Margin structure
- Volume drivers
- Customer mix
- Trading offsets
Trust posture
| Dimension | Status | Comment |
|---|---|---|
| Freshness | High | Actuals and plan are current-period aligned. |
| Completeness | High | Forecast-critical internal drivers mapped. |
| External volatility | Moderate | Commodity and LNG outlook are less stable. |
| Steward ownership | Explicit | FP&A, Treasury, and Trading ownership visible. |
Context-driven action
- If Brent and LNG remain the dominant explanation, confidence stays high enough for director review.
- If external-driver freshness slips or novelty rises, the forecast confidence ceiling falls automatically.
- If policy or historical-decision context conflicts with the current narrative, the forecast routes to explicit human challenge.
Trust rule: context quality is not background metadata. It is a first-class input to confidence and review routing.