Supply Chain Consultant

サプライチェーン最適化コンサルティングスキル。需要予測、在庫最適化、調達戦略、 物流ネットワーク設計、S&OP(Sales and Operations Planning)を支援。 Use when optimizing supply chain operations, improving inventory management, designing logistics networks, or conducting supply chain risk assessments. Triggers: “supply chain”, “在庫最適化”, “inventory optimization”, “demand forecasting”, “S&OP”, “procurement strategy”, “logistics network”.

No API Required

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

Professional supply chain management consulting: demand forecasting, inventory optimization, procurement strategy, logistics network design, and S&OP.

Primary language: Japanese (default), English supported Frameworks: SCOR (Supply Chain Operations Reference), S&OP best practices, Lean Supply Chain, Theory of Constraints Output format: Supply chain analysis reports, optimization recommendations, S&OP plans, network design proposals

Use this skill when:

  • Optimizing inventory levels and reducing carrying costs
  • Improving demand forecasting accuracy
  • Designing or redesigning logistics networks
  • Developing procurement strategies
  • Implementing or improving S&OP processes
  • Conducting supply chain risk assessments
  • Reducing supply chain costs while maintaining service levels

2. Prerequisites

  • API Key: None required
  • Python 3.9+ recommended

3. Quick Start

Workflow 1: Demand Forecasting Optimization

Purpose: Improve demand forecast accuracy to reduce stockouts and excess inventory.

4. How It Works

Workflow 1: Demand Forecasting Optimization

Purpose: Improve demand forecast accuracy to reduce stockouts and excess inventory.

Decision Procedure:

  1. Assess current forecasting method, horizon, frequency, and ownership
  2. Measure forecast accuracy (MAPE, Bias, Tracking Signal)
  3. Segment products via ABC-XYZ analysis to determine forecasting approach per segment
  4. Select forecasting technique:
    • AX/BX: Statistical methods (Moving Average, Exponential Smoothing)
    • AY/BY: Statistical + collaborative (Holt-Winters, consensus)
    • AZ/BZ: Demand sensing, safety stock buffers
    • CX/CY/CZ: Simple rules, Min-Max, or make-to-order
  5. Design S&OP-integrated forecasting process
  6. Monitor forecast KPIs and adjust

Detail: Load references/demand_forecasting_guide.md for formulas, segmentation matrix, KPI dashboard template. Script: Run scripts/generate_demand_kpi_dashboard.py to generate a KPI dashboard from data.

5. Usage Examples

  • Use Supply Chain Consultant when you need a structured workflow rather than an ad-hoc answer.
  • Start with a small representative input before applying the workflow to production data or assets.
  • Review the helper scripts and reference guides to tailor the output format to your project.

6. Understanding the Output

  • A structured response or artifact aligned to the skill’s workflow.
  • Reference support from 6 guide file(s).
  • Script-assisted execution using 3 helper command(s) where applicable.
  • Reusable output that can be reviewed, refined, and incorporated into a wider project workflow.

7. Tips & Best Practices

  • Begin with the smallest realistic sample input so you can validate the workflow before scaling up.
  • Keep skills/supply-chain-consultant/SKILL.md open while working; it remains the authoritative source for the full procedure.
  • Review the most relevant reference files first instead of scanning every guide: kpi_reference.md, sop_planning_guide.md, procurement_strategy_guide.md.
  • Run helper scripts on test data before using them on final assets or production-bound inputs: generate_demand_kpi_dashboard.py, generate_sop_agenda.py, generate_inventory_policy.py.
  • Preserve intermediate outputs so you can explain assumptions, diffs, and follow-up actions clearly.

8. Combining with Other Skills

  • Combine this skill with adjacent skills in the same category when the work spans planning, implementation, and review.
  • Browse the broader category for neighboring workflows: category index.
  • Use the English skill catalog when you need to chain this workflow into a larger end-to-end process.

9. Troubleshooting

  • Re-check prerequisites first: missing runtime dependencies and unsupported file formats are the most common failures.
  • If a helper script is involved, run it with a minimal sample input before applying it to a full dataset or repository.
  • Compare your input shape against the reference files to confirm expected fields, sections, or metadata are present.
  • Confirm the expected Python version and required packages are installed in the active environment.
  • When output looks incomplete, inspect the script arguments and rerun with explicit input/output paths.

10. Reference

References:

  • skills/supply-chain-consultant/references/demand_forecasting_guide.md
  • skills/supply-chain-consultant/references/inventory_optimization_guide.md
  • skills/supply-chain-consultant/references/kpi_reference.md
  • skills/supply-chain-consultant/references/logistics_network_guide.md
  • skills/supply-chain-consultant/references/procurement_strategy_guide.md
  • skills/supply-chain-consultant/references/sop_planning_guide.md

Scripts:

  • skills/supply-chain-consultant/scripts/generate_demand_kpi_dashboard.py
  • skills/supply-chain-consultant/scripts/generate_inventory_policy.py
  • skills/supply-chain-consultant/scripts/generate_sop_agenda.py