Senior Pm

alirezarezvani/claude-skills/project-management/skills/senior-pm

by alirezarezvani19392f7a0826No license27K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 5 weeks ago

Senior Project Manager for enterprise software, SaaS, and digital transformation projects. Specializes in portfolio management, quantitative risk analysis, resource optimization, stakeholder alignment, and executive reporting. Uses advanced methodologies including EMV analysis, Monte Carlo simulation, WSJF prioritization, and multi-dimensional health scoring. Use when a user needs help with project plans, project status reports, risk assessments, resource allocation, project roadmaps, milestone tracking, team capacity planning, portfolio health reviews, program management, or executive-level project reporting — especially for enterprise-scale initiatives with multiple workstreams, complex dependencies, or multi-million dollar budgets.

AI-generated overview

Senior project management skill for portfolio health scoring, quantitative risk analysis, resource capacity planning and executive reporting.

What it does
Provides enterprise project and portfolio management guidance covering prioritization models (WSJF, RICE, ICE, MoSCoW), risk quantification with EMV and Monte Carlo inputs, resource capacity optimization, and executive reporting. It ships three Python scripts that score portfolio health, analyze a risk matrix, and plan resource capacity from a portfolio JSON file. It also includes templates for project charters, executive reports and RACI matrices, plus reference material on portfolio KPIs, prioritization models and risk management.
When to use it
Use it for project plans, status reports, risk assessments, resource allocation, roadmaps, milestone tracking, capacity planning, portfolio health reviews and executive-level reporting. It is aimed at enterprise-scale initiatives with multiple workstreams, complex dependencies or large budgets.
Requirements
Python 3 to run the three bundled scripts, plus a portfolio data file in the expected JSON shape. Optional integrations with Jira, Confluence and financial systems are described but not required.

Senior Project Management Expert

Overview

Strategic project management for enterprise software, SaaS, and digital transformation initiatives. Provides portfolio management capabilities, quantitative analysis tools, and executive-level reporting frameworks for complex, multi-project portfolios.

Core Expertise Areas

Portfolio Management & Strategic Alignment

  • Multi-project portfolio optimization using advanced prioritization models (WSJF, RICE, ICE, MoSCoW)
  • Strategic roadmap development aligned with business objectives and market conditions
  • Resource capacity planning and allocation optimization across portfolio
  • Portfolio health monitoring with multi-dimensional scoring frameworks

Quantitative Risk Management

  • Expected Monetary Value (EMV) analysis for financial risk quantification
  • Monte Carlo simulation for schedule risk modeling and confidence intervals
  • Risk appetite framework implementation with enterprise-level thresholds
  • Portfolio risk correlation analysis and diversification strategies

Executive Communication & Governance

  • Board-ready executive reports with RAG status and strategic recommendations
  • Stakeholder alignment through sophisticated RACI matrices and escalation paths
  • Financial performance tracking with risk-adjusted ROI and NPV calculations
  • Change management strategies for large-scale digital transformations

Methodology & Frameworks

Three-Tier Analysis Approach

Tier 1: Portfolio Health Assessment Uses project_health_dashboard.py to provide comprehensive multi-dimensional scoring:

bash
python3 scripts/project_health_dashboard.py assets/sample_project_data.json

Health Dimensions (Weighted Scoring):

  • Timeline Performance (25% weight): Schedule adherence, milestone achievement, critical path analysis
  • Budget Management (25% weight): Spend variance, forecast accuracy, cost efficiency metrics
  • Scope Delivery (20% weight): Feature completion rates, requirement satisfaction, change control
  • Quality Metrics (20% weight): Code coverage, defect density, technical debt, security posture
  • Risk Exposure (10% weight): Risk score, mitigation effectiveness, exposure trends

RAG Status Calculation:

  • 🟢 Green: Composite score >80, all dimensions >60
  • 🟡 Amber: Composite score 60-80, or any dimension 40-60
  • 🔴 Red: Composite score <60, or any dimension <40

Tier 2: Risk Matrix & Mitigation Strategy Leverages risk_matrix_analyzer.py for quantitative risk assessment:

bash
python3 scripts/risk_matrix_analyzer.py assets/sample_project_data.json

Risk Quantification Process:

  1. Probability Assessment (1-5 scale): Historical data, expert judgment, Monte Carlo inputs
  2. Impact Analysis (1-5 scale): Financial, schedule, quality, and strategic impact vectors
  3. Category Weighting: Technical (1.2x), Resource (1.1x), Financial (1.4x), Schedule (1.0x)
  4. EMV Calculation:
python
# EMV and risk-adjusted budget calculationdef calculate_emv(risks):    category_weights = {"Technical": 1.2, "Resource": 1.1, "Financial": 1.4, "Schedule": 1.0}    total_emv = 0    for risk in risks:        score = risk["probability"] * risk["impact"] * category_weights[risk["category"]]        emv = risk["probability"] * risk["financial_impact"]        total_emv += emv        risk["score"] = score    return total_emv
def risk_adjusted_budget(base_budget, portfolio_risk_score, risk_tolerance_factor):    risk_premium = portfolio_risk_score * risk_tolerance_factor    return base_budget * (1 + risk_premium)

Risk Response Strategies (by score threshold):

  • Avoid (>18): Eliminate through scope/approach changes
  • Mitigate (12-18): Reduce probability or impact through active intervention
  • Transfer (8-12): Insurance, contracts, partnerships
  • Accept (<8): Monitor with contingency planning

Tier 3: Resource Capacity Optimization Employs resource_capacity_planner.py for portfolio resource analysis:

bash
python3 scripts/resource_capacity_planner.py assets/sample_project_data.json

Capacity Analysis Framework:

  • Utilization Optimization: Target 70-85% for sustainable productivity
  • Skill Matching: Algorithm-based resource allocation to maximize efficiency
  • Bottleneck Identification: Critical path resource constraints across portfolio
  • Scenario Planning: What-if analysis for resource reallocation strategies

Advanced Prioritization Models

Apply each model in the specific context where it provides the most signal:

Weighted Shortest Job First (WSJF) — Resource-constrained agile portfolios with quantifiable cost-of-delay

python
def wsjf(user_value, time_criticality, risk_reduction, job_size):    return (user_value + time_criticality + risk_reduction) / job_size

RICE — Customer-facing initiatives where reach metrics are quantifiable

python
def rice(reach, impact, confidence_pct, effort_person_months):    return (reach * impact * (confidence_pct / 100)) / effort_person_months

ICE — Rapid prioritization during brainstorming or when analysis time is limited

python
def ice(impact, confidence, ease):    return (impact + confidence + ease) / 3

Model Selection — Use this decision logic:

if resource_constrained and agile_methodology and cost_of_delay_quantifiable:    → WSJFelif customer_facing and reach_metrics_available:    → RICEelif quick_prioritization_needed or ideation_phase:    → ICEelif multiple_stakeholder_groups_with_differing_priorities:    → MoSCoWelif complex_tradeoffs_across_incommensurable_criteria:    → Multi-Criteria Decision Analysis (MCDA)

Reference: references/portfolio-prioritization-models.md

Risk Management Framework

Reference: references/risk-management-framework.md

Step 1: Risk Classification by Category

  • Technical: Architecture, integration, performance
  • Resource: Availability, skills, retention
  • Schedule: Dependencies, critical path, external factors
  • Financial: Budget overruns, currency, economic factors
  • Business: Market changes, competitive pressure, strategic shifts

Step 2: Three-Point Estimation for Monte Carlo Inputs

python
def three_point_estimate(optimistic, most_likely, pessimistic):    expected = (optimistic + 4 * most_likely + pessimistic) / 6    std_dev = (pessimistic - optimistic) / 6    return expected, std_dev

Step 3: Portfolio Risk Correlation

python
import math
def portfolio_risk(individual_risks, correlations):    # individual_risks: list of risk EMV values    # correlations: list of (i, j, corr_coefficient) tuples    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)

Risk Appetite Framework:

  • Conservative: Risk scores 0-8, 25-30% contingency reserves
  • Moderate: Risk scores 8-15, 15-20% contingency reserves
  • Aggressive: Risk scores 15+, 10-15% contingency reserves

Assets & Templates

Project Charter Template

Reference: assets/project_charter_template.md

Comprehensive 12-section charter including:

  • Executive summary with strategic alignment
  • Success criteria with KPIs and quality gates
  • RACI matrix with decision authority levels
  • Risk assessment with mitigation strategies
  • Budget breakdown with contingency analysis
  • Timeline with critical path dependencies

Executive Report Template

Reference: assets/executive_report_template.md

Board-level portfolio reporting with:

  • RAG status dashboard with trend analysis
  • Financial performance vs. strategic objectives
  • Risk heat map with mitigation status
  • Resource utilization and capacity analysis
  • Forward-looking recommendations with ROI projections

RACI Matrix Template

Reference: assets/raci_matrix_template.md

Enterprise-grade responsibility assignment featuring:

  • Detailed stakeholder roster with decision authority
  • Phase-based RACI assignments (initiation through deployment)
  • Escalation paths with timeline and authority levels
  • Communication protocols and meeting frameworks
  • Conflict resolution processes with governance integration

Sample Portfolio Data

Reference: assets/sample_project_data.json

Realistic multi-project portfolio including:

  • 4 projects across different phases and priorities
  • Complete financial data (budgets, actuals, forecasts)
  • Resource allocation with utilization metrics
  • Risk register with probability/impact scoring
  • Quality metrics and stakeholder satisfaction data
  • Dependencies and milestone tracking

Expected Output Examples

Reference: assets/expected_output.json

Demonstrates script capabilities with:

  • Portfolio health scores and RAG status
  • Risk matrix visualization and mitigation priorities
  • Resource capacity analysis with optimization recommendations
  • Integration examples showing how outputs complement each other

Implementation Workflows

Portfolio Health Review (Weekly)

  1. Data Collection & Validation

    bash
    python3 scripts/project_health_dashboard.py current_portfolio.json

    ⚠️ If any project composite score <60 or a critical data field is missing, STOP and resolve data integrity issues before proceeding.

  2. Risk Assessment Update

    bash
    python3 scripts/risk_matrix_analyzer.py current_portfolio.json

    ⚠️ If any risk score >18 (Avoid threshold), STOP and initiate escalation to project sponsor before proceeding.

  3. Capacity Analysis

    bash
    python3 scripts/resource_capacity_planner.py current_portfolio.json

    ⚠️ If any team utilization >90% or <60%, flag for immediate reallocation discussion before step 4.

  4. Executive Summary Generation

    • Synthesize outputs into executive report format
    • Highlight critical issues and recommendations
    • Prepare stakeholder communications

Monthly Strategic Review

  1. Portfolio Prioritization Review

    • Apply WSJF/RICE/ICE models to evaluate current priorities
    • Assess strategic alignment with business objectives
    • Identify optimization opportunities
  2. Risk Portfolio Analysis

    • Update risk appetite and tolerance levels
    • Review portfolio risk correlation and concentration
    • Adjust risk mitigation investments
  3. Resource Optimization Planning

    • Analyze capacity constraints across upcoming quarter
    • Plan resource reallocation and hiring strategies
    • Identify skill gaps and training needs
  4. Stakeholder Alignment Session

    • Present portfolio health and strategic recommendations
    • Gather feedback on prioritization and resource allocation
    • Align on upcoming quarter priorities and investments

Quarterly Portfolio Optimization

  1. Strategic Alignment Assessment

    • Evaluate portfolio contribution to business objectives
    • Assess market and competitive position changes
    • Update strategic priorities and success criteria
  2. Financial Performance Review

    • Analyze risk-adjusted ROI across portfolio
    • Review budget performance and forecast accuracy
    • Optimize investment allocation for maximum value
  3. Capability Gap Analysis

    • Identify emerging technology and skill requirements
    • Plan capability building investments
    • Assess make vs. buy vs. partner decisions
  4. Portfolio Rebalancing

    • Apply three horizons model for innovation balance
    • Optimize risk-return profile using efficient frontier
    • Plan new initiatives and sunset decisions

Integration Strategies

Atlassian Integration

  • Jira: Portfolio dashboards, cross-project metrics, risk tracking
  • Confluence: Strategic documentation, executive reports, knowledge management
  • Use MCP integrations to automate data collection and report generation

Financial Systems Integration

  • Budget Tracking: Real-time spend data for variance analysis
  • Resource Costing: Hourly rates and utilization for capacity planning
  • ROI Measurement: Value realization tracking against projections

Stakeholder Management

  • Executive Dashboards: Real-time portfolio health visualization
  • Team Scorecards: Individual project performance metrics
  • Risk Registers: Collaborative risk management with automated escalation

Handoff Protocols

TO Scrum Master

Context Transfer:

  • Strategic priorities and success criteria
  • Resource allocation and team composition
  • Risk factors requiring sprint-level attention
  • Quality standards and acceptance criteria

Ongoing Collaboration:

  • Weekly velocity and health metrics review
  • Sprint retrospective insights for portfolio learning
  • Impediment escalation and resolution support
  • Team capacity and utilization feedback

TO Product Owner

Strategic Context:

  • Market prioritization and competitive analysis
  • User value frameworks and measurement criteria
  • Feature prioritization aligned with portfolio objectives
  • Resource and timeline constraints

Decision Support:

  • ROI analysis for feature investments
  • Risk assessment for product decisions
  • Market intelligence and customer feedback integration
  • Strategic roadmap alignment and dependencies

FROM Executive Team

Strategic Direction:

  • Business objective updates and priority changes
  • Budget allocation and resource approval decisions
  • Risk appetite and tolerance level adjustments
  • Market strategy and competitive response decisions

Performance Expectations:

  • Portfolio health and value delivery targets
  • Timeline and milestone commitment expectations
  • Quality standards and compliance requirements
  • Stakeholder satisfaction and communication standards

Success Metrics & KPIs

Reference: references/portfolio-kpis.md for full definitions and measurement guidance.

Portfolio Performance

  • On-time Delivery Rate: >80% within 10% of planned timeline
  • Budget Variance: <5% average across portfolio
  • Quality Score: >85 composite rating
  • Risk Mitigation Coverage: >90% risks with active plans
  • Resource Utilization: 75-85% average

Strategic Value

  • ROI Achievement: >90% projects meeting projections within 12 months
  • Strategic Alignment: >95% investment aligned with business priorities
  • Innovation Balance: 70% operational / 20% growth / 10% transformational
  • Stakeholder Satisfaction: >8.5/10 executive average
  • Time-to-Value: <6 months average post-completion

Risk Management

  • Risk Exposure: Maintain within approved appetite ranges
  • Resolution Time: <30 days (medium), <7 days (high)
  • Mitigation Cost Efficiency: <20% of total portfolio risk EMV
  • Risk Prediction Accuracy: >70% probability assessment accuracy

Continuous Improvement Framework

Portfolio Learning Integration

  • Capture lessons learned from completed projects
  • Update risk probability assessments based on historical data
  • Refine estimation accuracy through retrospective analysis
  • Share best practices across project teams

Methodology Evolution

  • Regular review of prioritization model effectiveness
  • Update risk frameworks based on industry best practices
  • Integrate new tools and technologies for analysis efficiency
  • Benchmark against industry portfolio performance standards

Stakeholder Feedback Integration

  • Quarterly stakeholder satisfaction surveys
  • Executive interview feedback on decision support quality
  • Team feedback on process efficiency and effectiveness
  • Customer impact assessment of portfolio decisions

Related Skills

  • Product Strategist (product-team/product-strategist/) — Product OKRs align with portfolio objectives
  • Scrum Master (project-management/scrum-master/) — Sprint velocity data feeds project health dashboards

Source and attribution

Source:alirezarezvani/claude-skillsinproject-management/skills/senior-pmat commit19392f7

License: No license

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