# Real-Time Supply Chain Risk Control Tower with Bob and Confluent — Demo Script

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## Overview

NorthStar Energy Systems has a strategic 900-unit order worth $750K with a four-day ship window. A critical part, BRG-9004, is at risk. This demo walks through how IBM Bob, Confluent, and IBM watsonx.ai correlate live signals, score business risk continuously, and recommend mitigation before customers are impacted.

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## Step 1 — Set the Scene with the Strategic Order

**Present the customer order context:**

1. Show the 900-unit order totalling $750K revenue with a four-day ship window.
2. Highlight the critical part **BRG-9004** and explain why it is the single point of failure.
3. Explain that without signal correlation, the risk is invisible in any single system.

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## Step 2 — Show the Three Independent Risk Signals

**Walk through each signal in isolation:**

1. Show **low inventory** at the plant — insufficient units to fulfil the order without resupply.
2. Show the **supplier shipment delay** increasing from 12 hours to 96 hours — a 8× degradation.
3. Show **severe port congestion** on the primary logistics route — blocking the fastest path to the customer.

Emphasise that each signal alone looks manageable, but their combination is what drives the escalation.

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## Step 3 — Show the Confluent Streaming Backbone

**Demonstrate real-time event correlation:**

1. Open the **Confluent topics view** and show inventory, shipment, and port-risk events streaming in real time.
2. Explain that the **risk engine** subscribes to all three topics simultaneously and recalculates a multidimensional risk score on every new event.
3. Point out that this is the reusable **Confluent Building Block** orchestrated by IBM Bob — new signal sources can be added without redesigning the pipeline.

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## Step 4 — Watch the Risk Escalate

**Trace the risk lifecycle from MEDIUM to CRITICAL:**

1. Show the business risk indicator move from **MEDIUM → HIGH** as the shipment delay worsens.
2. Show it escalate to **CRITICAL** as port congestion combines with the inventory shortfall.
3. Highlight the continuous recalculation — this is not a batch report; risk is visible the moment conditions change.

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## Step 5 — Review the Recommended Mitigation at CRITICAL

**Show the automated recommendation engine:**

1. At CRITICAL risk, show the three recommended actions published to the alerts topic:
   - **Activate alternate supplier SUP-221** to bypass the delayed primary supplier.
   - **Expedite shipment SHP-33019** to recover the delivery timeline.
   - **Notify procurement** to initiate purchase order approval for the alternate source.
2. Explain that these recommendations are derived from the correlated risk score, not hardcoded rules.

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## Step 6 — Show IBM watsonx.ai-Generated Communications

**Demonstrate AI-assisted human communication:**

1. Open the **Executive Summary** draft generated by IBM watsonx.ai — a concise briefing of the risk situation, financial exposure, and recommended actions.
2. Open the **Supplier Escalation Communication** — a pre-drafted message to the alternate supplier SUP-221 ready for human approval and send.
3. Explain that a human approves before anything is dispatched — AI drafts, humans decide.

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## Step 7 — Replay the Recovery Scenario

**Show the system returning to normal:**

1. Trigger the recovery conditions: shipment delay returns to **12 hours** and inventory rises to **820 units**.
2. Watch the risk indicator automatically return to **MEDIUM** as the risk engine recalculates.
3. Emphasise that the recovery is as automatic and continuous as the escalation.

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## Step 8 — Close with the Reusable Pattern

**Highlight extensibility:**

1. Explain that the pattern is specification-driven: adding a new signal (weather, tariffs, supplier quality scores) requires only:
   - Updating the spec.
   - Adding an event contract to the Schema Registry.
   - Replaying the acceptance scenario in IBM Bob.
2. Show the architecture diagram and point out the clean separation between the streaming backbone, the risk engine, and the IBM watsonx.ai communication layer.
3. Summarise: **any industry with multi-source risk signals** — retail, pharma, defence — can adopt this pattern.