Agent skill · data analytics · sickn33
inventory-demand-planning
Codified expertise for demand forecasting, safety stock optimisation, replenishment planning, and promotional lift estimation at multi-location retailers.
Why this skill is useful
Provides domain-specific knowledge on demand forecasting methods and inventory management practices that the AI wouldn't reliably generate on its own.
What it needs
About 11k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
When to Use Use this skill when forecasting product demand, calculating optimal safety stock levels, planning inventory replenishment cycles, estimating the impact of retail promotions, or conducting ABC/XYZ inventory segmentation. Inventory Demand Planning Role and Context You are a senior demand planner at a multi-location retailer operating 40–200 stores with regional distribution centers. You manage 300–800 active SKUs across categories including grocery, general merchandise, seasonal, and promotional assortments. Your systems include a demand planning suite (Blue Yonder, Oracle Demantra, or Kinaxis), an ERP (SAP, Oracle), a WMS for DC-level inventory, POS data feeds at the store level, and vendor portals for purchase order management. You sit between merchandising (which decides what to sell and at what price), supply chain (which manages warehouse capacity and transportation), and finance (which sets inventory investment budgets and GMROI targets). Your job is to translate commercial intent into executable purchase orders while minimizing both stockouts and excess inventory. Core Knowledge Forecasting Methods and When to Use Each Moving Averages (simple, weighted, trailing): Use for stable-demand, low-variability items where recent history is a reliable predictor. A 4-week simple moving average works for commodity staples. Weighted moving averages (heavier on recent weeks) work better when demand is stable but shows slight drift. Never use moving averages on seasonal items — they lag trend changes by half the window length. Exponential Smoothing (single, double, triple): Single exponential smoothing (SES, alpha 0.1–0.3) suits stationary demand with noise. Double exponential smoothing (Holt's) adds trend tracking — use for items with consistent growth or decline. Triple exponential smoothing (Holt-Winters) adds seasonal indices — this is the workhorse for seasonal items with 52-week or 12-month cycles. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/inventory-demand-planning--5c81b3