Crisis Detector

Identify early warning signs of potential crises before they escalate through pattern recognition, signal monitoring, and risk assessment.

When to Use This Skill

• Setting up early warning systems
• Assessing crisis probability
• Training teams on signals
• Building escalation criteria
• Post-crisis prevention planning

Methodology Foundation

Based on Institute for Crisis Management research and Burson crisis frameworks, combining:

• Signal identification
• Pattern recognition
• Risk assessment matrices
• Escalation protocols

What Claude Does vs What You Decide

Instructions

Step 1: Map Crisis Types

Crisis Categories:

Step 2: Identify Early Signals

Signal Types:

Step 3: Build Detection Matrix

Signal Strength Assessment:

Step 4: Create Escalation Triggers

Trigger Framework:

Step 5: Document and Improve

Post-Detection Review:

• How early did we detect?
• What signals did we miss?
• How accurate was assessment?
• What should we add to monitoring?

Examples

Example 1: Crisis Detection System Design

Input:

Design a crisis detection system for:
- E-commerce company (clothing)
- 500K customers
- Active on Instagram, TikTok, Twitter
- Past issue: Shipping delays during holiday

Output:

## Crisis Detection System: E-Commerce Fashion

### Crisis Risk Map

| Crisis Type | Probability | Impact | Priority |
|-------------|-------------|--------|----------|
| Shipping delays | High | High | P1 |
| Product quality issue | Medium | High | P1 |
| Social media backlash | Medium | High | P1 |
| Data breach | Low | Critical | P1 |
| Influencer controversy | Medium | Medium | P2 |
| Supply chain disruption | Medium | High | P2 |
| Payment fraud | Low | Medium | P3 |

---

### Early Warning Signals

#### P1: Shipping Delays

**Leading Indicators (3-5 days before crisis):**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Carrier delay reports | Logistics API | >10% delayed |
| Warehouse backlog | WMS data | >24hr processing |
| Weather events | News/weather | Storm in hub |
| "Where's my order" tickets | Support | +50% daily |

**Lagging Indicators (crisis starting):**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Social mentions | Social listening | "shipping" +100% |
| Review mentions | Trustpilot/G2 | Shipping 3/5 stars |
| Refund requests | Payment system | +30% |
| Chargeback rate | Payment processor | >1% |

---

#### P1: Product Quality Issue

**Leading Indicators:**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Return rate spike | Returns data | >10% on SKU |
| Quality complaints | Support tickets | 3+ same issue |
| Photo complaints | Social | "damaged", "wrong color" |
| Batch-specific issues | QC data | Same lot number |

**Lagging Indicators:**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Viral unboxing | TikTok/Instagram | >10K views negative |
| Review bomb | Product pages | Multiple 1-stars |
| Media inquiry | PR inbox | Journalist question |

---

#### P1: Social Media Backlash

**Leading Indicators:**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Sentiment shift | Social tools | -20% in 24hr |
| Controversial post | Your social | Negative comments >10% |
| Influencer complaint | Social | >50K follower post |
| Screenshot spreading | Twitter/Reddit | Same image 5+ times |

**Lagging Indicators:**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Viral negative | Any platform | >50K engagements |
| Hashtag trending | Twitter | Brand + negative |
| Media pickup | News sites | Article published |
| Competitor amplification | Social | Competitor sharing |

---

### Detection Dashboard

┌──────────────────────────────────────────────────────────┐ │ CRISIS DETECTION DASHBOARD 🟢 NORMAL │ ├──────────────────────────────────────────────────────────┤ │ │ │ SHIPPING STATUS 🟢 Normal │ │ ├─ Carrier delays: 3% (threshold: 10%) │ │ ├─ Backlog: 4 hours (threshold: 24hr) │ │ └─ “Where’s my order”: 45 (baseline: 50) │ │ │ │ PRODUCT QUALITY 🟢 Normal │ │ ├─ Return rate: 5.2% (threshold: 10%) │ │ ├─ Quality tickets: 2 (threshold: 3+ same) │ │ └─ Photo complaints: 1 (threshold: 5) │ │ │ │ SOCIAL SENTIMENT 🟡 Watch │ │ ├─ Sentiment: -15% (threshold: -20%) │ │ ├─ Volume: +40% (threshold: +50%) │ │ └─ Influencer: None flagged │ │ │ │ SECURITY 🟢 Normal │ │ ├─ Login anomalies: Normal │ │ └─ Payment fraud: 0.3% │ │ │ └──────────────────────────────────────────────────────────┘

---

### Escalation Matrix

| Level | Criteria | Notification | Response |
|-------|----------|--------------|----------|
| 🟢 Normal | All metrics in range | None | Standard ops |
| 🟡 Watch | 1 metric at threshold | Slack alert | Increased monitoring |
| 🟠 Alert | 2+ metrics or 1 exceeded | Team notification | Standby team |
| 🔴 Crisis | Critical threshold breached | All-hands alert | Activate protocol |

---

### Alert Routing

| Signal Type | Primary | Backup | Escalation |
|-------------|---------|--------|------------|
| Shipping | Operations | COO | CEO |
| Product quality | Product | VP Ops | CEO |
| Social media | Marketing | CMO | CEO |
| Security | IT | CTO | CEO + Legal |
| Legal/PR | Legal | CEO | Board |

---

### Holiday Season Adjustments

During high-volume periods (Nov 15 - Dec 31):

| Metric | Normal Threshold | Holiday Threshold |
|--------|------------------|-------------------|
| Carrier delays | 10% | 15% |
| Support volume | +50% | +100% |
| Social volume | +50% | +75% |
| Response time | 4 hours | 8 hours |

**Rationale:** Higher baseline expected; adjust to avoid false alerts
while maintaining genuine crisis detection.

Example 2: Real-Time Crisis Assessment

Input:

Assess this situation:
- Support tickets up 80% in 2 hours
- Twitter mentions up 150%
- Hashtag #[Brand]Scam trending locally
- 3 refund requests mentioning "charged twice"
- No known system issues

Output:

## Crisis Assessment: Potential Payment Issue

### Alert Level: 🔴 CRISIS

---

### Signal Analysis

| Signal | Value | Normal | Status |
|--------|-------|--------|--------|
| Support spike | +80% | <25% | CRITICAL |
| Social spike | +150% | <50% | CRITICAL |
| Trending hashtag | Yes | No | CRITICAL |
| Duplicate charge reports | 3 | 0 | CONCERNING |

---

### Probable Cause

**Most likely: Payment processing error**

Evidence:
1. Multiple "charged twice" complaints
2. No known system issues rules out outage
3. Sudden spike suggests batch problem
4. #Scam hashtag = customers think fraud

---

### Immediate Actions

| Priority | Action | Owner | Timeline |
|----------|--------|-------|----------|
| 1 | Check payment processor logs | Engineering | NOW |
| 2 | Identify affected transactions | Finance | 30 min |
| 3 | Prepare holding statement | Comms | 15 min |
| 4 | Alert customer service team | CX Lead | NOW |
| 5 | Monitor hashtag spread | Social | Ongoing |

---

### Holding Statement (Draft)

We’re aware some customers may have experienced duplicate charges. Our team is investigating urgently. If you’ve been affected, please DM us or email [support] – we’ll make this right immediately.

Updates to follow shortly.

---

### Escalation Path

**Now:** CTO + CFO + CMO notified
**+30 min:** CEO briefing if not resolved
**+1 hour:** External statement if ongoing

---

### Crisis Trajectory

**If unaddressed (next 2-4 hours):**
- Hashtag goes national
- Media inquiries begin
- Trust pilot review bomb
- Social influencers amplify

**If addressed quickly (next 1-2 hours):**
- Contain to affected customers
- Flip narrative to "responsive company"
- Prevent media escalation
- Build goodwill through fast resolution

---

### Resolution Checklist

- [ ] Root cause identified
- [ ] Affected customers identified
- [ ] Refunds initiated
- [ ] Proactive communication sent
- [ ] Social response deployed
- [ ] Hashtag monitoring active
- [ ] Post-incident review scheduled

Skill Boundaries

What This Skill Does Well

• Identifying early warning signals
• Creating detection frameworks
• Assessing crisis probability
• Designing escalation systems

What This Skill Cannot Do

• Access your actual systems
• Monitor in real-time
• Make response decisions
• Know your specific thresholds

Iteration Guide

Follow-up Prompts:

• “Design detection for [specific crisis type]”
• “Create escalation protocol for [scenario]”
• “What signals should we add for [risk]?”
• “How do we prevent [past crisis] from recurring?”

References

• Institute for Crisis Management
• Burson Crisis Playbook
• Harvard Business Review Crisis Research
• Edelman Trust Barometer

Related Skills

• social-listening – Monitoring systems
• response-coordinator – Crisis response
• reputation-recovery – Post-crisis rebuild

Skill Metadata

• Domain: Crisis
• Complexity: Intermediate-Advanced
• Mode: centaur
• Time to Value: 2-4 hours for system design
• Prerequisites: Access to metrics, stakeholder alignment