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Enterprise project manager

Skill findscripter/everything-skills/07-productivity/enterprise-project-manager

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Install
npx -y skills add findscripter/everything-skills --skill enterprise-project-manager

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当需要做企业软件/SaaS/数字化转型的多项目组合管理、量化风险评估、资源产能规划或高管级汇报时使用;做组合健康打分、EMV/蒙特卡洛风险量化、WSJF/RICE/ICE 优先级排序与董事会级 RAG 报告(产出健康仪表盘、风险矩阵、产能方案、高管报告);不适用于单 sprint 敏捷执行、产品需求设计或个人待办管理;触发词:项目组合管理、portfolio、风险评估、EMV、蒙特卡洛、WSJF、RICE、ICE、资源产能、RAG 状态、高管汇报、项目健康

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SKILL.md

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何时使用

适用于企业软件、SaaS、数字化转型等多工作流、复杂依赖、千万级预算的项目组合(portfolio)。典型场景:组合健康复盘、量化风险评估、资源产能优化、跨项目优先级排序、董事会/高管级 RAG 汇报、风险调整后的预算与 ROI 测算。

不该用边界:单个 Sprint 的敏捷执行交给 Scrum Master;产品需求/路线图细节交给 Product Owner;个人任务/待办管理无需本技能。本技能聚焦组合层的策略、量化与治理,不替代具体研发执行。

步骤

采用三层分析法,每层对应一个脚本(输入为组合数据 JSON)。

第一层 · 组合健康评分project_health_dashboard.py

python3 scripts/project_health_dashboard.py current_portfolio.json

加权维度:进度 25% / 预算 25% / 范围 20% / 质量 20% / 风险敞口 10%。 RAG 判定:🟢 综合分 >80 且各维度 >60;🟡 综合分 60-80 或任一维度 40-60;🔴 综合分 <60 或任一维度 <40。

第二层 · 风险矩阵与应对risk_matrix_analyzer.py

python3 scripts/risk_matrix_analyzer.py current_portfolio.json

流程:概率(1-5) × 影响(1-5) × 类别权重(技术 1.2 / 资源 1.1 / 财务 1.4 / 进度 1.0),再算 EMV。 应对策略按风险分阈值:规避 >18 / 缓解 12-18 / 转移 8-12 / 接受 <8。

第三层 · 资源产能优化resource_capacity_planner.py

python3 scripts/resource_capacity_planner.py current_portfolio.json

目标利用率 70-85%(可持续);识别关键路径瓶颈;做 what-if 重分配场景。

周度健康复盘的硬性闸门(务必遵守)

  • 任一项目综合分 <60 或关键字段缺失 → ,先修复数据完整性。
  • 任一风险分 >18(规避阈值)→ ,升级至项目发起人。
  • 任一团队利用率 >90% 或 <60% → 标记,进入重分配讨论后再出报告。

指令

EMV 与风险调整预算

def calculate_emv(risks):
    category_weights = {"Technical": 1.2, "Resource": 1.1, "Financial": 1.4, "Schedule": 1.0}
    total_emv = 0
    for risk in risks:
        risk["score"] = risk["probability"] * risk["impact"] * category_weights[risk["category"]]
        total_emv += risk["probability"] * risk["financial_impact"]
    return total_emv

def risk_adjusted_budget(base_budget, portfolio_risk_score, risk_tolerance_factor):
    return base_budget * (1 + portfolio_risk_score * risk_tolerance_factor)

优先级模型(按场景选用,勿混用)

def wsjf(user_value, time_criticality, risk_reduction, job_size):
    return (user_value + time_criticality + risk_reduction) / job_size   # 资源受限敏捷组合、可量化延迟成本

def rice(reach, impact, confidence_pct, effort_pm):
    return (reach * impact * (confidence_pct / 100)) / effort_pm          # 面向客户、reach 可量化

def ice(impact, confidence, ease):
    return (impact + confidence + ease) / 3                               # 头脑风暴/快速排序

选型决策:资源受限+敏捷+延迟成本可量化→WSJF;面向客户+有 reach 指标→RICE;需快速排序/构思阶段→ICE;多方诉求冲突→MoSCoW;跨不可通约维度的复杂权衡→MCDA。

蒙特卡洛三点估算 + 组合风险相关性

def three_point_estimate(o, m, p):
    return (o + 4*m + p) / 6, (p - o) / 6          # 期望, 标准差

import math
def portfolio_risk(individual_risks, correlations):
    sum_sq = sum(r**2 for r in individual_risks)
    sum_corr = sum(2*c*individual_risks[i]*individual_risks[j] for i, j, c in correlations)
    return math.sqrt(sum_sq + sum_corr)

风险偏好与应急储备:保守(分 0-8) 25-30% / 适中(分 8-15) 15-20% / 激进(分 15+) 10-15%。

示例

周度组合健康复盘:

  1. project_health_dashboard.py → 项目 A 综合分 58(🔴)且预算维度缺失 → 触发闸门,停,补数据后重跑。
  2. risk_matrix_analyzer.py → 某集成风险分 20 >18 → 停,升级发起人,定规避方案。
  3. resource_capacity_planner.py → 后端团队利用率 94% → 标记重分配。
  4. 汇总为高管报告:RAG 仪表盘 + 财务表现 vs 战略目标 + 风险热力图 + 含 ROI 的前瞻建议。

注意事项

  • 三脚本输出互补,需综合而非孤立解读;高管报告要落到「关键问题 + 可执行建议」。
  • 类别权重、RAG 阈值、应对阈值是源约束,勿随意改动,否则失去可比性。
  • 组合 KPI 参考线:准时交付 >80%、预算偏差 <5%、质量分 >85、风险覆盖 >90%、利用率 75-85%;高风险问题解决 <7 天、中风险 <30 天。
  • 交接:向 Scrum Master 传战略优先级/资源/需关注风险;向 Product Owner 传 ROI/市场优先级;接收高管团队的目标变更与风险偏好调整。
  • 可借 MCP 接入 Jira(组合看板、跨项目指标)/ Confluence(战略文档、高管报告)自动取数与生成报告。

互见

  • assets/project_charter_template.md(12 段项目章程)、executive_report_template.md(董事会级报告)、raci_matrix_template.md(RACI + 升级路径)、sample_project_data.json(示例组合数据)。
  • references/portfolio-prioritization-models.mdrisk-management-framework.mdportfolio-kpis.md

本条采编自 alirezarezvani/claude-skills(MIT 许可证)。

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