Apparel and Footwear Supply Chain Planning

Apparel, footwear and luxury buys are placed months ahead, by style, color and size, for a season that may not sell through. DemandLabs forecasts new styles from look-alikes, proposes size transfers between stores and ranks factory orders by risk.

What Shapes Apparel, Footwear and Luxury Planning

Fashion demand is planned at the size and color level and committed before the first sale.

Season buys

The Buy Comes Before the Season

Factories need orders months before the season opens, and reorders on fashion styles rarely arrive in time. The buy rests on how similar styles sold in past seasons.

Size curves

Each Style Splits Into Sizes

A style sells across sizes, colors and widths, each with its own demand. A store can hold plenty of a style and still turn shoppers away for want of a size.

Markdowns

Leftover Stock Costs Margin

Apparel retailers clear the season with markdowns, and each one cuts into the margin the buy was planned on. Luxury houses limit discounting, so excess stock has few exits.

Solutions for Apparel, Footwear and Luxury

The DemandLabs applications that fit apparel, footwear and luxury, and how each one handles the planning.

New styles take their launch curves from look-alike styles that share category, fabric, color and price point. Forecasts run by item and store, so each size of a style gets its own number.

Explore demand planning

Push and lateral transfer proposals are refreshed daily for the DC and every store, showing freight cost and fill-rate gain side by side, so a broken size run can be filled from stock you already own.

Explore inventory optimization

Season targets cascade by brand and region, each level showing its gap to plan, and style units tie out to the finance view period by period, so the merchandise budget and the style buy agree.

Explore IBP

Each factory is scored on financial filings, news, port congestion, weather and ESG ratings, and open purchase orders for the season are ranked by that score across factories and lanes.

Explore supplier risk

How Apparel, Footwear and Luxury Planning Connects

Each style in the season buy links to its size forecast by store, the factory making it and the margin it carries.

Merchandise

Season Buy

  • New styles
  • Carryover styles
  • Price points
Demand

Size and Store Forecast

  • Store sales
  • Online orders
  • Look-alike styles
Sourcing

Factory Orders

  • Factory lead times
  • Ocean lanes
  • ESG ratings
Inventory

Store Stock

  • Size availability
  • Transfers
  • DC holdback
Finance

Season Margin

  • Full-price sales
  • Markdowns
  • Stock value

Built for Apparel, Footwear and Luxury

Apparel planning is decided style by style and size by size, long before the season sells.

New Styles From Past Seasons

Each new style is forecast from past-season styles with similar attributes, before it sells a unit.

A Forecast for Every Size

Each size and color is forecast by store, so the buy can follow where each size actually sells.

Broken Size Runs Refilled

Transfer proposals show which store holds the missing size, with freight cost and fill-rate gain next to each move.

Limited Pieces Allocated by Tier

When a luxury style runs short, allocation follows account tier and wholesale commitments, with each account's fill rate shown.

Apparel, Footwear and Luxury Planning FAQs

Can DemandLabs forecast styles with no history?

A new style takes its launch curve from look-alike styles with similar attributes, such as category, fabric and price point, from your own past seasons.

Does it forecast by size?

Forecasts run at item level by store, so each size and color of a style carries its own number for the buy and for in-season transfers.

Can it rebalance sizes between stores?

The daily transfer proposals point to the store or DC holding the missing size and price the freight against the fill-rate gain.

How long does implementation take?

Eight weeks to the first live cycle for one planning area, with a value review with your CFO in week 10.

See Your Next Season by Style and Size

A 45-minute walkthrough on your own data.