Executive Performance Intelligence
Enterprise Performance Intelligence
Replace retrospective performance reporting with continuous root-cause, forecast, and action intelligence for enterprise leadership.
Core decision question
What actions should leadership take right now?
Every signal, context package, evidence pack, policy result, recommendation, human approval, action, replay, and learning artifact should serve this question.
North Star KPIs
Decision velocityPerformance predictabilityExecutive productivityValue realizationAgent workforce
Performance Intelligence AgentVariance Intelligence AgentCausal Analysis AgentExecutive Narrative AgentRecommendation AgentEnterprise integrations
SAP S/4HANADatabricksHR systemsSupply chain systemsTrading systemsRetail systemsProject systemsFuture UDPMonitored domains
Enterprise KPIsRoot causeCross-functional correlationBusiness driversNarrative generationExecutive simulationDecision recommendationsReference 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.
7373 reference signals / scenario
1111 KPI driver movements
ScenarioScenario event REF-TICK-70442 at 14:20
66 executive actions pending
Reference signals and recommended responses
| Signal | Source | Impact | Recommended response |
|---|---|---|---|
| Revenue misses target | SAP + retail + trading | -$420M forecast gap | Identify driver and action set |
| Cost-to-serve rises | Supply chain + finance | Margin -80 bps | Recommend intervention |
| Project portfolio slips | Project system | Capex phasing risk | Escalate portfolio decision |
Demo sequence
- Revenue misses target
- Causes identified
- Impact quantified
- Future outcomes predicted
- Actions recommended
- Executive narrative generated
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 |
|---|---|---|---|
| -$420M forecast gap | SAP revenue + retail POS + trading P&L | driver=REV-MISS-441 | Business unit: Customers & Products |
| Margin -80 bps | Supply chain + SAP costing | driver=COST-SERVE-118 | Owner: Performance Lead |
| Capex phasing risk | Project system + finance forecast | portfolio=CAP-SLIP-229 | Owner: FB&T |
Evidence, policy, replay, learning, and action artifacts
Decision memory
| Runtime artifact | Identifier | Credibility proof |
|---|---|---|
| Evidence pack | EP-PERF-70442 | data-evidence="pack" · source records and supporting documents |
| Policy ID | FIN-PERF-2026-03 | Policy runtime gate evaluated before recommendation |
| Replay ID | REPLAY-PERF-70442 | Replay available from signal through human judgment and action |
| Learning | patterns learned: 7 | Decision memory updates after accepted/rejected outcome |
| Action payload | Executive intervention 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 |
|---|---|---|---|---|
| Rebalance regional spend | 88% | +$90M margin recovery | Execution coordination | FB&T intervention |
| Escalate segment gap | 85% | $420M risk governed | Executive attention needed | CFO decision |
| Publish board narrative | 94% | QBR ready | Narrative review | Board pack draft |
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
Decision velocity
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 |
|---|---|---|---|
| Rebalance regional spend | +$90M margin recovery | FB&T Leader | Recommended |
| Escalate underperforming segment | $420M revenue gap | CFO | Executive attention |
| Publish board narrative | QBR ready | Executive Narrative Owner | Drafted |
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 | Performance, variance, causal analysis, executive narrative, and recommendation agents monitor enterprise KPIs. | KPI-to-action trace with drivers, causes, forecasts, and narrative. |
| Analyst | Investigate variance drivers and source records. | Can explain what happened and why. |
| Supervisor | Monitor analysis workload and recurring performance issues. | Can see which issues need escalation. |
| Function Leader / Performance Lead | Optimize process and business performance. | Can compare business units, functions, and root causes. |
| FB&T Leader | View enterprise operational performance and value realization. | Can see which missions are underperforming. |
| CFO | Choose strategic actions based on enterprise performance signals. | Can see expected outcome and enterprise value impact. |
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 |
|---|---|---|---|
| Revenue miss | Revenue below target | Root cause, impact, forecast, recommendation, and executive narrative are generated. | |
| Margin deterioration | Margin drops | Driver attribution and intervention options are visible. | |
| Market disruption | External market shock | Enterprise performance impact and actions update. |
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. | Revenue misses target · Scenario event REF-TICK-70442 at 14:20 |
| 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. | Rebalance regional spend |
| Recommendation | Recommended response and alternatives are shown with impact. | Rebalance regional spend · confidence 88% · impact +$90M margin recovery |
| 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. | +$90M margin recovery |
| Enterprise Integration | Systems of record, data products, APIs, and future UDP context layer are named. | SAP S/4HANA · Databricks · HR systems · Supply chain systems · example: SAP revenue + retail POS + trading P&L |
| 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. | Rebalance regional spend | Escalate segment gap | Publish board narrative |
| 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. | Decision velocity |
| 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. | What actions should leadership take right now? |
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.