๐๐ญ๐๐ฅ๐ข๐๐ง ๐๐๐ฌ๐ก๐ข๐จ๐ง ๐ข๐ฌ๐งโ๐ญ ๐ฅ๐จ๐ฌ๐ข๐ง๐ ๐๐จ๐ฆ๐ฉ๐๐ญ๐ข๐ญ๐ข๐ฏ๐๐ง๐๐ฌ๐ฌ ๐จ๐ง ๐๐ซ๐๐ง๐. ๐๐ญโ๐ฌ ๐ฅ๐จ๐ฌ๐ข๐ง๐ ๐ข๐ญ ๐จ๐ง ๐ข๐ง๐ฏ๐๐ง๐ญ๐จ๐ซ๐ฒ.
#FashionTech hashtag #InventoryOptimization hashtag #AIFashion hashtag #RetailStrategy hashtag #DigitalTransformation hashtag #Workbloom hashtag #FutureOfFashion hashtag #MakeITHappen

In 2026, the sector is worth billions, but the real value drain remains invisible: ๐จ๐ฏ๐๐ซ๐ฌ๐ญ๐จ๐๐ค ๐๐ง๐ ๐ฌ๐ญ๐จ๐๐ค๐จ๐ฎ๐ญ๐ฌ ๐๐จ๐๐ฑ๐ข๐ฌ๐ญ ๐ข๐ง ๐ญ๐ก๐ ๐ฏ๐๐ซ๐ฒ ๐ฌ๐๐ฆ๐ ๐ฐ๐๐ซ๐๐ก๐จ๐ฎ๐ฌ๐.
โ ๏ธ ๐๐ก๐ ๐&๐ ๐ข๐ฌ ๐ฎ๐ง๐๐จ๐ซ๐ ๐ข๐ฏ๐ข๐ง๐ An average fashion brand with โฌ๐๐ ๐ข๐ง ๐ซ๐๐ฏ๐๐ง๐ฎ๐:
- spends 18โ22% on inventory โ โฌ๐๐๐๐โ๐.๐๐
- if ๐๐% ๐ข๐ฌ ๐จ๐ฏ๐๐ซ๐ฌ๐ญ๐จ๐๐ค, that means โฌ๐๐๐โ๐๐๐๐ ๐ข๐ง ๐ญ๐ข๐๐-๐ฎ๐ฉ ๐๐๐ฉ๐ข๐ญ๐๐ฅ
๐ก With AI inventory optimisation:
- overstock cut to ๐๐โ๐๐%
- โฌ๐๐๐โ๐๐๐๐ ๐๐ซ๐๐๐ ๐ฎ๐ฉ to reinvest in marketing,
new collections, digital channels And that is just cash flow.
๐ ๐๐ก๐ ๐ญ๐ซ๐ฎ๐ ๐ฏ๐๐ฅ๐ฎ๐ ๐จ๐ ๐๐ ๐ข๐ง ๐๐๐ฌ๐ก๐ข๐จ๐ง ๐ฅ๐ข๐๐ฌ ๐ข๐ง ๐๐๐๐ข๐ฌ๐ข๐จ๐ง-๐ฆ๐๐ค๐ข๐ง๐ Those who use it well donโt just โautomateโ. They make better decisions, sooner.
- ๐๐๐ฏ๐๐ง๐๐๐ ๐๐๐ฆ๐๐ง๐ ๐๐จ๐ซ๐๐๐๐ฌ๐ญ๐ข๐ง๐ : predictive models analyse
sales data, social trends, web demand, delivering 60โ90-day forecasts with ๐๐%+ ๐๐๐๐ฎ๐ซ๐๐๐ฒ
- ๐๐ฆ๐๐ซ๐ญ ๐๐ฅ๐ฅ๐จ๐๐๐ญ๐ข๐จ๐ง: which garment, in which city,
in which store for faster sell-through
- ๐๐ฒ๐ง๐๐ฆ๐ข๐ ๐ฉ๐ซ๐ข๐๐ข๐ง๐ & ๐ฆ๐๐ซ๐ค๐๐จ๐ฐ๐ง ๐จ๐ฉ๐ญ๐ข๐ฆ๐ข๐ฌ๐๐ญ๐ข๐จ๐ง: adaptive prices based on demand,
seasonality and competitors
- ๐๐ข๐ซ๐ญ๐ฎ๐๐ฅ ๐ญ๐ซ๐ฒ-๐จ๐ง & ๐๐: conversion +40%, return rate
โ5%
- ๐๐๐ฌ๐๐ฅ๐ & ๐๐ข๐ซ๐๐ฎ๐ฅ๐๐ซ ๐๐๐จ๐ง๐จ๐ฆ๐ฒ: integrated platforms = +3โ5%
incremental revenue
โ ๏ธ ๐๐ก๐ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ? ๐๐ ๐๐จ๐๐ฌ๐งโ๐ญ ๐ฐ๐จ๐ซ๐ค ๐ฐ๐ข๐ญ๐ก๐จ๐ฎ๐ญ ๐๐ฑ๐ฉ๐๐ซ๐ญ๐ข๐ฌ๐. Buying a tool is not enough. You need professionals who know how to:
- design the data pipeline
(POS, e-commerce, marketplaces, social)
- train models on the
brandโs actual historical data
- integrate AI with inventory
systems and PLM
- translate outputs into buying
and merchandising decisions
- set up continuous improvement
and testing
๐ An average fashion company ๐๐จ๐๐ฌ ๐ง๐จ๐ญ ๐ก๐๐ฏ๐ ๐๐ฅ๐ฅ ๐จ๐ ๐ญ๐ก๐ข๐ฌ ๐ข๐ง-๐ก๐จ๐ฎ๐ฌ๐. This is where the model shifts
๐ ๐๐จ๐ซ๐ค๐๐ฅ๐จ๐จ๐ฆ ๐๐จ๐ง๐ง๐๐๐ญ๐ฌ ๐๐๐ฌ๐ก๐ข๐จ๐ง ๐๐ซ๐๐ง๐๐ฌ ๐๐ง๐ ๐ซ๐๐ญ๐๐ข๐ฅ๐๐ซ๐ฌ ๐ฐ๐ข๐ญ๐ก ๐ฌ๐ฉ๐๐๐ข๐๐ฅ๐ข๐ฌ๐ญ๐ฌ ๐ก๐๐ฏ๐ข๐ง๐ ๐ฉ๐ซ๐จ๐ฏ๐๐ง ๐๐ฑ๐ฉ๐๐ซ๐ญ๐ข๐ฌ๐ ๐ข๐ง:
- AI demand forecasting & predictive analytics
- Inventory optimization & allocation planning
- Dynamic pricing and markdown strategy
- Virtual try-on & AR
- Omnichannel inventory
visibility
- Data architecture (POS +
e-commerce + marketplaces)
- Circular economy & resale
platform strategy
๐ ๐๐ง ๐๐๐๐, ๐๐ญ๐๐ฅ๐ข๐๐ง ๐๐๐ฌ๐ก๐ข๐จ๐ง ๐๐๐ง ๐ซ๐๐ฆ๐๐ข๐ง ๐ข๐๐จ๐ง๐ข๐ ๐ฐ๐ก๐ข๐ฅ๐ ๐๐ฅ๐ฌ๐จ ๐๐๐๐จ๐ฆ๐ข๐ง๐ ๐ก๐ข๐ ๐ก๐ฅ๐ฒ ๐ฉ๐ซ๐จ๐๐ข๐ญ๐๐๐ฅ๐. Discover how to transform inventory from a problem into a strategic lever with โworkbloom.io
Sources The Traceability Hub SDA Bocconi Nedap