Inventory Demand Planning
Run demand forecasts, safety-stock math, replenishment cycles, and promo lift estimates when you operate or build multi-SKU retail inventory.
Overview
Inventory Demand Planning is an agent skill for the Operate phase that codifies retail demand forecasting, safety stock, replenishment, and promotional lift planning for multi-location assortments.
Install
npx skills add https://github.com/affaan-m/everything-claude-code --skill inventory-demand-planningWhat is this skill?
- Demand forecasting method selection for grocery, GM, seasonal, and promotional assortments
- Safety stock optimization and multi-location replenishment planning frameworks
- ABC/XYZ analysis and seasonal transition management playbooks
- Promotional lift estimation tied to merchandising and finance targets
- Vendor negotiation frameworks for PO management at 40–200 store scale
- Informed by planners with 15+ years of multi-SKU retail experience
- Scoped for 40–200 stores and roughly 300–800 active SKUs
- Covers forecasting selection, ABC/XYZ, seasonal transitions, and vendor negotiation frameworks
Adoption & trust: 4.2k installs on skills.sh; 210k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You manage hundreds of SKUs across stores and DCs but lack a structured way to pick forecast methods, safety stock, and replenishment without over- or under-stocking.
Who is it for?
Retail operators, ecommerce operators with wide assortments, or solo builders modeling inventory logic for multi-location commerce products.
Skip if: Single-SKU digital products, pure software teams with no physical inventory, or builders who only need a one-off PO calculator with no forecasting discipline.
When should I use this skill?
Forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.
What do I get? / Deliverables
You get planner-grade frameworks for forecasts, ABC/XYZ segmentation, seasonal transitions, and vendor-aligned replenishment decisions you can apply to the next planning cycle.
- Forecast method recommendation with rationale for the assortment
- Safety stock and replenishment plan outline aligned to promo and seasonality
- ABC/XYZ segmentation and negotiation talking points for vendors
Recommended Skills
Journey fit
Canonical shelf is Operate because the skill encodes day-to-day planning cadence—forecasting, replenishment, and GMROI-aligned stock targets—not greenfield product design. Iterate fits ongoing tuning of forecasts, ABC/XYZ classes, seasonal transitions, and vendor terms as sell-through and lead times shift.
How it compares
Use instead of generic spreadsheet tips when you need retail-grade demand planning process, not a lightweight stock-count snippet.
Common Questions / FAQ
Who is inventory-demand-planning for?
Demand planners, retail ops leads, and solo or indie builders shipping ecommerce or retail tooling who need structured forecasting, safety stock, and replenishment guidance across many SKUs and locations.
When should I use inventory-demand-planning?
Use it during Operate when tuning forecasts and stock levels, during Grow when promotional lifts affect buy quantities, or during Build when embedding planning rules into an inventory or WMS-facing product.
Is inventory-demand-planning safe to install?
It is procedural knowledge without built-in shell or network tools in the skill itself; review the Security Audits panel on this Prism page before enabling it in your agent workspace.
SKILL.md
READMESKILL.md - Inventory Demand Planning
# 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. ## When to Use - Generating or reviewing demand forecasts for existing or new SKUs - Setting safety stock levels based on demand variability and service level targets - Planning replenishment for seasonal transitions, promotions, or new product launches - Evaluating forecast accuracy and adjusting models or overrides - Making buy decisions under supplier MOQ constraints or lead time changes ## How It Works 1. Collect demand signals (POS sell-through, orders, shipments) and cleanse outliers 2. Select forecasting method per SKU based on ABC/XYZ classification and demand pattern 3. Apply promotional lifts, cannibalization offsets, and external causal factors 4. Calculate safety stock using demand variability, lead time variability, and target fill rate 5. Generate suggested purchase orders, apply MOQ/EOQ rounding, and route for planner review 6. Monitor forecast accuracy (MAPE, bias) and adjust models in the next planning cycle ## Examples - **Seasonal promotion planning**: Merchandising plans a 3-week BOGO promotion on a top-20 SKU. Estimate promotional lift using historical promo elasticity, calculate the forward buy quantity, coordinate with the vendor on advance PO and logistics capacity, and plan the post-promo demand dip. - **New SKU launch**: No demand history available. Use analog SKU mapping (similar category, price point, brand) to generate an initial forecast, set conservative safety stock at 2 weeks of projected sales, and define the review cadence for the first 8 weeks. - **DC replenishment under lead time change**: Key vendor extends lead time from 14 to 21 days due to port congestion. Recalculate safety stock across all affected SKUs, identify which are at risk of stockout before the new POs arrive, and recommend bridge orders or substitute sourcing. ## 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.