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 holidayOutput:
## 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 |
|--------|----------