Strategic Portfolio Intelligence
Enterprise Portfolio Intelligence
Continuously evaluate the current and future value of bp's asset portfolio using finance, operations, carbon, market, and risk signals.
Core decision question
Which assets should bp grow, optimize, divest, or transform?
Every signal, context package, evidence pack, policy result, recommendation, human approval, action, replay, and learning artifact should serve this question.
North Star KPIs
Portfolio ROIEnterprise value growthAsset productivityCapital efficiencyAgent workforce
Portfolio Intelligence AgentAsset Performance AgentValue Creation AgentRisk AgentCarbon Intelligence AgentEnterprise integrations
Production systemsTrading systemsSAP S/4HANATreasuryCarbon systemsDatabricksFuture UDPMonitored domains
UpstreamLNGRefiningRetailEV ChargingHydrogenBioenergyCarbonReference signal ticker
Signal visibility must be more than the word signal. Each mission shows reference signal counts, severity, scenario REF-TICK ID, and current blocked/recommended state. These are scenario proof shapes until connected to live traversal.
Reference signal generated from the scenario library; REF-TICK IDs show the expected production trace shape and are not attested live events.
3131 reference signals / scenario
88 asset value movements
ScenarioScenario event REF-TICK-60418 at 14:17
44 portfolio actions pending
Reference signals and recommended responses
| Signal | Source | Impact | Recommended response |
|---|---|---|---|
| Asset performance deteriorated | Production system | ROACE -1.2 pts | Optimize or divest scenario |
| Commodity outlook changed | Market feed | Portfolio value shift | Re-rank assets |
| Carbon cost increased | Carbon system | Refining margin risk | Run transition exposure scenario |
Demo sequence
- Asset performance deteriorates
- Commodity outlook changes
- Carbon costs increase
- Sphere recommends hold, invest, optimize, or divest with evidence
Source-system traceability for major numbers
Every major value is tied to a source system, API object, data product, or source transaction. This answers where the number came from before BP asks.
Context pack: business unit: Group Finance · cost center: CC-1042 · entity code: BP-GROUP · owner: mission runtime.
| Number / metric | Source system or data product | Record / API object | Business context |
|---|---|---|---|
| ROACE -1.2 pts | Production system + SAP profitability | asset=REF-UK-440 | Business unit: Refining |
| Portfolio value shift | Reference portfolio model shape | scenario_run=REF-PORT-VAL-882 | Owner: Portfolio Lead |
| Carbon margin risk | Carbon system + asset economics | asset=REF-EU-221 | Policy: Transition risk |
Evidence, policy, replay, learning, and action artifacts
Decision memory
| Runtime artifact | Identifier | Credibility proof |
|---|---|---|
| Evidence pack | EP-PORT-60418 | data-evidence="pack" · source records and supporting documents |
| Policy ID | FIN-PORT-2026-04 | Policy runtime gate evaluated before recommendation |
| Replay ID | REPLAY-PORT-60418 | Replay available from signal through human judgment and action |
| Learning | patterns learned: 4 | Decision memory updates after accepted/rejected outcome |
| Action payload | Portfolio optimize/divest workflow | Next action: governed execution after approval limit $500K and human override check |
Alternative actions table
Alternative actions table. This is the concrete recommendation surface: bp Sphere shows what it recommends, what it rejected, the expected value, the risk, and the action path.
| Alternative action | Confidence | Expected value / impact | Risk / tradeoff | Action path |
|---|---|---|---|---|
| Optimize refining asset | 84% | +$180M EBITDA | Operational dependency | Asset optimization plan |
| Divest underperforming asset | 79% | +$1.2B capital released | Market timing | Board review |
| Increase LNG weighting | 82% | +0.3 ROACE | Portfolio concentration | Strategy scenario |
Runtime injection console
Use these controls during the workshop to show the mission changing state. Injection creates a named runtime event, updates mission KPI/readiness, adds a replay row, and opens the trace from signal to learning.
Mission KPI
Portfolio ROI
Awaiting scenario injection.
Mission readiness
Baseline
No injected blockers or opportunities yet.
Latest replay event
None
Click an injection below to create a replayable runtime event.
| Time | Event | Scenario | Decision impact |
|---|---|---|---|
| --:--:-- | Waiting | No scenario injected | No mission state change |
Decision portfolio
| Decision | Impact | Owner | Status |
|---|---|---|---|
| Optimize refining asset | +$180M EBITDA | Portfolio Lead | Recommended |
| Divest underperforming asset | +$1.2B capital released | CFO | Board review |
| Increase LNG portfolio weighting | +0.3 ROACE | Strategy Lead | Scenario ready |
Vertical operating-model audit
This validates that the mission is useful from frontline work through enterprise steering: Agent Runtime → Analyst → Supervisor → Function Leader/Controller → FB&T Leader → CFO.
| Role layer | What this layer can do | Executive credibility proof |
|---|---|---|
| Agent Runtime | Portfolio, asset performance, value creation, risk, and carbon agents monitor enterprise assets. | Asset-to-portfolio trace with value, risk, carbon, and recommendation. |
| Analyst | Review asset performance, drivers, and evidence. | Can explain why asset value changed. |
| Supervisor | Monitor asset-review workload and escalations. | Can see which analyses are blocked. |
| Function Leader / Portfolio Lead | Optimize asset portfolio and recommend hold, invest, optimize, or divest. | Can compare assets and scenario outcomes. |
| FB&T Leader | View portfolio health, value creation, and enterprise risk concentration. | Can identify where intervention improves returns. |
| CFO | Steer portfolio value and capital efficiency. | Can decide grow, hold, optimize, transform, or divest. |
Executive credibility scenarios
These are the scenarios BP can challenge live. The mission must show signal, context, evidence, policy, decision, action, replay, learning, and enterprise impact for each.
| Scenario | Inject | Expected runtime proof | Action |
|---|---|---|---|
| Asset underperformance | Asset performance deteriorates | Invest, hold, optimize, or divest recommendation is evidence-backed. | |
| Refinery margin collapse | Margin outlook changes | Portfolio value, asset ranking, and transition options update. | |
| LNG demand growth | Demand outlook improves | Growth/investment recommendation and scenario evidence are shown. |
12+ dimension BP credibility audit
| Dimension | Visible proof requirement | This mission's answer |
|---|---|---|
| Signal | Business event or market movement is visible and linked to a mission decision. | Asset performance deteriorated · Scenario event REF-TICK-60418 at 14:17 |
| Context | Entity, business unit, owner, system object, policy domain, and history are resolved. | Resolved through enterprise context graph: owner, system object, business unit, history, and policy domain. |
| Evidence | Source records, documents, approvals, and source-system snapshots are inspectable. | Evidence pack includes source system record, curated data snapshot, policy reference, and supporting document where applicable. |
| Policy | Authority, control, risk, accounting, tax, treasury, or investment policies are referenced. | Policy/runtime gate is evaluated before recommendation or action. |
| Decision | The mission produces a named decision object, not just a metric or chart. | Optimize refining asset |
| Recommendation | Recommended response and alternatives are shown with impact. | Optimize refining asset · confidence 84% · impact +$180M EBITDA |
| Human Override | Human approval, rejection, override, or escalation path is explicit. | Approval, rejection, override reason, and escalation owner are retained in replay. |
| Action | Action payload is traceable to workflow, system update, notification, hold, hedge, or approval. | Recommended |
| Replay | Event, context, evidence, policy, recommendation, human judgment, action, and outcome can be replayed. | Replay captures signal, context, evidence, policy, agent output, human judgment, action, outcome, and learning. |
| Learning | Accepted/rejected outcomes are captured as future pattern memory. | Outcome becomes pattern memory after human decision and realized impact are known. |
| Business Impact | Financial, risk, cash, control, or value impact is quantified. | +$180M EBITDA |
| Enterprise Integration | Systems of record, data products, APIs, and future UDP context layer are named. | Production systems · Trading systems · SAP S/4HANA · Treasury · example: Production system + SAP profitability |
| Source Drill-down | Users can drill from decision to source transaction, document, or curated data product. | Source drill-down points to SOR/API record, Databricks/UDP data product, document, or market feed behind the decision. |
| Confidence | The decision carries confidence and uncertainty drivers. | Confidence is shown in decision formation and decomposed into data freshness, evidence completeness, policy clarity, and model uncertainty. |
| Alternatives | At least two alternative actions or scenarios are available. | Optimize refining asset | Divest underperforming asset | Increase LNG weighting |
| Audit Trail | Every material step is retained with timestamp, actor/agent, evidence, and policy result. | Timestamped audit trail spans agent, human, policy, evidence, and action events. |
| Executive Narrative | The mission can produce an executive answer: what happened, why, what to do, and expected outcome. | Narrative answers what happened, why, recommended action, value, risk, and next owner. |
| Mission KPI | A mission-level KPI changes when the scenario changes. | Portfolio ROI |
| Readiness | Readiness or confidence updates when blockers, policies, or evidence status change. | Mission readiness/confidence updates when signals, evidence, policies, or blockers change. |
| Enterprise Impact | The mission shows enterprise-level consequence beyond one transaction. | Which assets should bp grow, optimize, divest, or transform? |
Runtime architecture
SignalBusiness event, market movement, policy breach, or performance variance.
ContextEntity, asset, customer, project, policy, historical pattern, and owner resolution.
Evidence + PolicySource records, documents, controls, authority, and data-quality checks.
Decision + ActionAlternatives, confidence, financial impact, owner, action payload, and approval path.
Replay + LearningFull trace, outcome, accepted/rejected recommendation, and pattern memory.