FLO

FLO operates one of Europe's largest footwear retail networks — 800+ stores across 25 countries and three continents — managing millions of SKUs each season across highly seasonal, size-sensitive assortments. In retail supply chain, where fashion cycles are short and shelf availability directly drives revenue, inventory precision is critical. Yet FLO's planners worked from legacy spreadsheet processes that couldn't process real-time demand signals, leaving them perpetually reactive. Stock sat in isolated pools across central warehouses, regional hubs and online fulfillment with no mechanism for cross-location rebalancing. The result: chronic out-of-stocks on bestsellers, overstock on slow movers, expensive last-minute shipments from distant distribution centers, and markdown-driven clearance eroding margins.

FLO partnered with invent.ai to deploy a unified AI-driven platform on AWS, replacing spreadsheet-based planning with machine learning-powered demand forecasting. The system ingests sales data, web analytics, promotion calendars and external signals — including local weather and events — to generate real-time forecasts at SKU, store and day granularity across the full network. A financial optimization engine moves beyond fill-rate KPIs to calculate trade-offs between lost sales and inventory holding costs, then recommends optimal allocation, replenishment and inter-store transfers automatically. The platform also incorporates markdown timing optimization, size-level pack customization by store cluster, and distribution network modeling. By unifying inventory visibility across all channels and automating decision logic, invent.ai shifted FLO from reactive, siloed planning to a predictive, revenue-focused operating model.

Product availability jumped from 71% to 94%, while out-of-stocks fell from 15% to 3% — a measurable transformation in shelf presence across the global store network. Lost sales decreased by 12%, and overall revenue grew by 4.7% through improved markdown strategy and stockout prevention. At the financial level, sales revenue increased 2.7%, gross profit by 1.1%, and net profit by 0.9%. Operationally:

• Supply chain network expanded from 62 to 360 locations
• Shipment duration reduced by 17%, accelerating fulfillment speed

These outcomes reflect a structural shift — from chronic inventory imbalance to demand-aligned availability at every node in a 25-country network.

• Real-time forecasting at SKU-store-day granularity is non-negotiable for footwear retailers managing seasonally volatile, size-sensitive assortments across diverse geographies and channels.
• Inventory silos between warehouses, regional hubs and e-commerce fulfillment actively destroy margin — unified visibility and automated transfers are foundational, not optional.
• Financially optimized decision-making — balancing lost sales against carrying costs — consistently outperforms fill-rate-only KPIs by aligning inventory decisions directly to revenue and margin outcomes.
• Expanding distribution network granularity (62 to 360 locations in FLO's case) is often a prerequisite for translating forecast accuracy into actual shelf availability at scale.