How FLO cut lost sales by 12% with AI-driven inventory optimization

FLO, one of Europe's largest footwear retailers operating 800+ stores across 25 countries with 11,000+ employees and 15 distribution centers, deployed invent.ai's AI-driven inventory optimization platform to address chronic overstock and out-of-stock problems across its multi-brand e-commerce network and physical footprint. The solution, built on AWS scalable infrastructure, integrates sales data, web analytics, promotion schedules, and external signals such as local weather and events to produce real-time demand forecasts at SKU-store-day granularity, while a financial optimization engine weighs lost sales against inventory carrying costs to recommend allocation, replenishment, and markdown decisions. A separate agentic AI module handles size-level pack customization by clustering stores with similar demand patterns and tuning case packs accordingly. Since implementation, FLO has reduced lost sales by 12%, grown revenue by 4.7%, raised product availability from 71% to 94%, cut out-of-stocks from 15% to 3%, and expanded its supply chain network from 62 to 360 locations. Sales revenue grew 2.7%, gross profit 1.1%, and net profit 0.9%, with a 17% reduction in shipment duration achieved without adding inventory. The deployment replaces legacy spreadsheet-driven planning that had left stores overstocked on slow-moving styles and empty on bestsellers. "Invent.ai's margin-driven, profit-optimizing science, tailor-fit algorithms and AI-powered probabilistic demand forecasting offer everything we're looking for," said Hakan Ugur, Chief Merchandising Officer at FLO. "Their solutions enable us to achieve the most profitable inventory levels using a sophisticated economic model that analyzes demand patterns, inventory costs, margins and other parameters."