demand-supply-matching

Balance demand and supply with Python ATP calculations and optimization-based allocation.

56|16|Updated Oct 18, 2025

Search Tags:#optimization #matching #allocation #supply #fulfillment #demand #ATP

Ready to run

npx skills add https://github.com/kishorkukreja/awesome-supply-chain --skill demand-supply-matching

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: demand-supply-matching
Source: https://github.com/kishorkukreja/awesome-supply-chain/tree/main/skills/demand-supply-matching
Command: npx skills add https://github.com/kishorkukreja/awesome-supply-chain --skill demand-supply-matching

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps organizations resolve supply-demand mismatches, optimize fulfillment allocation, and ensure efficient distribution of available resources.

Core Features & Use Cases

Demand-Supply Balancing: Analyzes and reconciles discrepancies between customer demand and available supply.
Fulfillment Optimization: Determines the best way to allocate limited supply to meet demand, considering various strategies like priority-based or optimization-based allocation.
Available-to-Promise (ATP): Calculates and provides visibility into future product availability.
Use Case: A retailer faces a shortage of a popular product. This Skill can help decide which customer orders to fulfill first based on priority or optimize allocation to maximize overall customer satisfaction and revenue.

Quick Start

Use the demand-supply-matching skill to balance demand and supply for PROD001.

Frequently Asked Questions about demand-supply-matching

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

FAQPage Schema

How do I optimize fulfillment allocation when supply is constrained?▼

You can optimize fulfillment allocation under constrained supply by applying strategies like First-Come, First-Served, Pro-Rata, or Priority-Based allocation. The Skill uses SciPy to resolve mismatches and maximize distribution efficiency.

How does Available-to-Promise (ATP) calculation work for demand-supply balancing?▼

Available-to-Promise (ATP) calculation works by analyzing current inventory and reconciling discrepancies against future customer demand. This provides clear visibility into future product availability for accurate fulfillment planning.

Can I use SciPy and pandas for multi-objective demand allocation?▼

Yes, you can use SciPy and pandas for multi-objective demand allocation. The Skill integrates these libraries to calculate ATP and execute optimization-based allocation across unconstrained, constrained, and balanced supply scenarios.

What is the best way to balance demand and supply for limited inventory?▼

The best way to balance demand and supply for limited inventory is using optimization-based allocation. This approach determines how to allocate scarce supply to demand, maximizing overall customer satisfaction and revenue.

What allocation strategies handle supply shortages across multiple customer orders?▼

Allocation strategies that handle supply shortages across multiple orders include First-Come, First-Served, Pro-Rata, and Priority-Based allocation. These methods determine which customer orders to fulfill first during constrained supply situations.