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

Claude Does	You Decide
Identifies warning signals	Risk tolerance
Assesses crisis probability	Response resources
Creates detection criteria	Escalation authority
Designs monitoring systems	Communication strategy
Suggests response triggers	Final action calls

Instructions

Step 1: Map Crisis Types

Crisis Categories:

Category	Examples	Warning Time
Operational	Outage, product failure	Hours to days
Reputational	Executive scandal, viral complaint	Minutes to hours
Legal/Regulatory	Lawsuit, investigation	Days to weeks
Financial	Earnings miss, fraud	Hours to days
Human	Workplace incident, harassment	Hours to days
External	Natural disaster, market crash	Variable

Step 2: Identify Early Signals

Signal Types:

Signal Type	Examples	Monitoring
Internal	Employee complaints, support tickets	HR, Support data
Customer	Review patterns, churn spikes	CX metrics
Social	Mention volume, sentiment shift	Social tools
Media	Press inquiries, journalist interest	PR inbox
Regulatory	Compliance notices, audit findings	Legal
Financial	Payment disputes, refund requests	Finance

Step 3: Build Detection Matrix

Signal Strength Assessment:

Signal	Weak	Moderate	Strong	Critical
Volume spike	+25%	+50%	+100%	+300%
Sentiment shift	-10%	-20%	-30%	-50%
Media inquiries	1	2-3	4-5	6+
Support tickets	+10%	+25%	+50%	+100%
Social influencer	10K	50K	100K	500K+

Step 4: Create Escalation Triggers

Trigger Framework:

Level	Signals Present	Action
Watch	1 moderate signal	Monitor closely
Alert	2+ moderate or 1 strong	Notify team
Warning	Multiple strong signals	Assemble team
Crisis	Any critical signal	Activate protocol

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