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scenario-planning

Analyze supply chain scenarios with Monte Carlo simulations and risk matrices.

56|16|Updated Oct 18, 2025
Search Tags:#scenario planning#contingency planning#risk analysis#supply chain#monte carlo#what-if analysis
One-click install
npx skills add https://github.com/kishorkukreja/awesome-supply-chain --skill scenario-planning-kishorkukreja
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scenario-planning
Source: https://github.com/kishorkukreja/awesome-supply-chain/tree/main/skills/scenario-planning
Command: npx skills add https://github.com/kishorkukreja/awesome-supply-chain --skill scenario-planning-kishorkukreja

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, matplotlib, scipy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps organizations analyze potential future supply chain scenarios, assess risks, and develop contingency plans to make more resilient decisions.

Core Features & Use Cases

  • Scenario Modeling: Build and evaluate 'what-if' scenarios, sensitivity analyses, and Monte Carlo simulations.
  • Risk Assessment: Identify, prioritize, and quantify supply chain risks using probability-impact matrices.
  • Contingency Planning: Develop business continuity plans and strategic responses to potential disruptions.
  • Use Case: A company can use this Skill to simulate the impact of a major port strike on their inventory levels and delivery times, then develop alternative shipping routes as a contingency.

Quick Start

Use the scenario-planning skill to analyze the impact of a 20% increase in demand on total supply chain costs.

Frequently Asked Questions about scenario-planning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I use Monte Carlo simulation for supply chain risk analysis?▼

Monte Carlo simulation models demand and supply reliability by running quantitative probability distributions. This skill uses numpy and scipy to evaluate what-if scenarios, generating statistical outputs that quantify potential supply chain disruptions.

What's the best way to build contingency plans for supply chain disruptions?▼

Contingency planning evaluates risk matrices and what-if scenarios to formulate strategic responses. This skill analyzes alternative routing and inventory levels, producing business continuity plans that navigate uncertainty using quantitative modeling frameworks.

Do I need pandas and numpy to perform what-if analysis for supply chain costs?▼

Yes, you need pandas and numpy for data manipulation and statistical analysis. This skill requires these Python libraries alongside matplotlib and scipy to model demand, calculate costs, and visualize sensitivity results.

How does sensitivity analysis evaluate supply chain scenarios under uncertainty?▼

Sensitivity analysis evaluates supply chain uncertainty by adjusting variables like demand and costs to observe outcome impacts. This skill performs quantitative what-if modeling, generating visual risk matrices to support decision-making.

Can I visualize probability-impact matrices for supply chain risk assessment in Python?▼

Yes, you can visualize probability-impact matrices using matplotlib. This skill quantifies supply chain risks, plots risk assessment matrices, and generates graphical outputs to prioritize potential disruptions and evaluate contingency plans.

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