Does it account for vendor constraints?

Yes, it incorporates Minimum Order Quantities (MOQ), Economic Order Quantities (EOQ), and lead time variability into its replenishment logic to ensure orders are realistic and cost-effective.

Which forecasting methods does this skill support?

It supports a wide range of methods including simple/weighted moving averages, triple exponential smoothing (Holt-Winters), seasonal decomposition (STL), and advanced machine learning models like LightGBM or XGBoost.

How is forecast accuracy measured?

The skill monitors performance using metrics like WMAPE (Weighted Mean Absolute Percentage Error), Bias, and Tracking Signals to identify model drift or structural forecasting errors.

Can it handle new products with no sales history?

Yes, it utilizes analog SKU mapping to borrow demand patterns and variability from similar existing products to generate initial forecasts and safety stock buffers.

How does it manage promotional events?

The skill calculates promotional lift based on historical elasticity, estimates cannibalization of sub-items, and plans for the expected post-promotion demand dip.

Inventory Demand Planning

Name: Inventory Demand Planning
Author: affaan-m

byaffaan-m

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156,033

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Data Science & ML

Optimizes retail inventory management through advanced demand forecasting, safety stock calculation, and strategic replenishment planning.

This skill equips Claude with the expertise of a senior demand planner, enabling it to manage complex supply chain scenarios for multi-location retailers. It leverages sophisticated forecasting models—ranging from Holt-Winters triple exponential smoothing to machine learning approaches—while integrating critical business logic like ABC/XYZ analysis and promotional lift estimation. It is designed to help users translate commercial intent into executable purchase orders, minimizing stockouts and excess inventory across hundreds of SKUs while navigating vendor constraints and lead time variability.

Key Features

01Multi-model demand forecasting including Exponential Smoothing and ML methods

02Promotional lift estimation and post-promo demand dip analysis

03156,033 GitHub stars

04Dynamic safety stock calculation based on demand and lead time variability

05ABC/XYZ classification for inventory prioritization and service level targeting

06Strategic replenishment planning with MOQ and EOQ optimization

Use Cases

01Planning seasonal transitions and promotional events for multi-store retail chains

02Generating initial forecasts and safety stock levels for new product launches using analog SKU mapping

03Adjusting replenishment strategies in response to shifting vendor lead times or supply chain disruptions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add affaan-m/everything-claude-code inventory-demand-planning

For use in Claude.ai and ChatGPT

Key Features

01Multi-model demand forecasting including Exponential Smoothing and ML methods

02Promotional lift estimation and post-promo demand dip analysis

03156,033 GitHub stars

04Dynamic safety stock calculation based on demand and lead time variability

05ABC/XYZ classification for inventory prioritization and service level targeting

06Strategic replenishment planning with MOQ and EOQ optimization

Use Cases

01Planning seasonal transitions and promotional events for multi-store retail chains

02Generating initial forecasts and safety stock levels for new product launches using analog SKU mapping

03Adjusting replenishment strategies in response to shifting vendor lead times or supply chain disruptions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add affaan-m/everything-claude-code inventory-demand-planning

For use in Claude.ai and ChatGPT