crisis-detector

危机检测

通过模式识别、信号监控和风险评估，识别潜在危机升级前的早期预警信号。

何时使用此技能

• 搭建早期预警系统
• 评估危机发生的概率
• 培训团队识别信号
• 制定升级标准
• 制定危机后的预防计划

方法论基础

基于 Institute for Crisis Management 的研究和 Burson 危机框架，结合：

• 信号识别
• 模式识别
• 风险评估矩阵
• 升级协议

Claude 负责什么，哪些由你决定

Claude 负责	你决定
识别预警信号	风险承受度
评估危机发生的概率	响应资源
制定检测标准	升级权限
设计监控系统	沟通策略
建议响应触发条件	最终行动决策

说明

步骤 1：梳理危机类型

危机类别：

类别	示例	预警时间
运营	服务中断、产品故障	数小时至数天
声誉	高管丑闻、投诉迅速传播	数分钟至数小时
法律/监管	诉讼、调查	数天至数周
财务	未达到盈利预期、欺诈	数小时至数天
人员	工作场所事故、骚扰	数小时至数天
外部	自然灾害、市场崩盘	不定

步骤 2：识别早期信号

信号类型：

信号类型	示例	监控方式
内部	员工投诉、支持工单	人力资源、支持数据
客户	评论模式、客户流失激增	CX 指标
社交媒体	提及量、情绪变化	社交媒体工具
媒体	媒体问询、记者关注	公关收件箱
监管	合规通知、审计发现	法务
财务	付款争议、退款申请	财务

步骤 3：建立检测矩阵

信号强度评估：

信号	弱	中等	强	严重
数量激增	+25%	+50%	+100%	+300%
情绪变化	-10%	-20%	-30%	-50%
媒体问询	1	2-3	4-5	6+
支持工单	+10%	+25%	+50%	+100%
社交媒体影响者	10K	50K	100K	500K+

步骤 4：创建升级触发条件

触发条件框架：

级别	出现的信号	行动
观察	1 个中等信号	密切监控
警报	2 个以上中等信号或 1 个强信号	通知团队
警告	多个强信号	召集团队
危机	出现任何严重信号	启动预案

步骤 5：记录并改进

检测后复盘：

• 我们提前多久检测到？
• 我们漏掉了哪些信号？
• 评估有多准确？
• 我们应在监控中增加什么？

示例

示例 1：危机检测系统设计

输入：

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

输出：

## 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

┌──────────────────────────────────────────────────────────┐ │ 危机检测仪表板 🟢 正常 │ ├──────────────────────────────────────────────────────────┤ │ │ │ 物流状态 🟢 正常 │ │ ├─ 承运商延误：3%（阈值：10%） │ │ ├─ 积压：4 小时（阈值：24 小时） │ │ └─ “我的订单到哪了”：45（基准：50） │ │ │ │ 产品质量 🟢 正常 │ │ ├─ 退货率：5.2%（阈值：10%） │ │ ├─ 质量工单：2（阈值：同类问题 3+） │ │ └─ 照片投诉：1（阈值：5） │ │ │ │ 社交情绪 🟡 关注 │ │ ├─ 情绪：-15%（阈值：-20%） │ │ ├─ 数量：+40%（阈值：+50%） │ │ └─ 影响者：未发现需要标记的对象 │ │ │ │ 安全 🟢 正常 │ │ ├─ 登录异常：正常 │ │ └─ 支付欺诈：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.

示例 2：实时危机评估

输入：

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

输出：

## 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)

我们了解到，部分客户可能遇到了重复扣款的情况。我们的团队正在紧急调查。如果您受到影响，请给我们发私信或发送邮件至 [support]——我们会立即妥善处理。

我们很快会发布后续消息。

---

### 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

技能边界

此技能擅长的事项

• 识别早期预警信号
• 创建检测框架
• 评估危机发生概率
• 设计升级处理系统

此技能无法做到的事项

• 访问您的实际系统
• 实时监控
• 做出响应决策
• 了解您的具体阈值

迭代指南

后续提示词：

• “为[具体危机类型]设计检测机制”
• “为[场景]制定升级处理协议”
• “我们应该为[风险]添加哪些信号？”
• “我们如何防止[过去的危机]再次发生？”

参考资料

• 危机管理协会
• Burson 危机手册
• 《哈佛商业评论》危机研究
• Edelman 信任度晴雨表

相关技能

• social-listening - 监控系统
• response-coordinator - 危机响应
• reputation-recovery - 危机后的重建

技能元数据

• 领域：危机
• 复杂度：中级至高级
• 模式：centaur
• 价值实现时间：系统设计需 2-4 小时
• 前置条件：可访问指标、利益相关者达成一致