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Franchisees face excessive time spent on manual ordering processes, leading to inadequate product quantities, frequent stockouts of popular items, and overstocking of slow-moving goods. Lack of predictive analytics causes supply chain bottlenecks, expiration-related losses, and inefficient logistics planning. Existing systems fail to account for dynamic factors like seasonality, promotions, location-specific demand patterns, and external variables affecting sales.
A major retail franchise network operating across Poland with extensive logistics operations and over several thousand stores
Implementation of AI-driven ordering system is projected to reduce manual ordering efforts by 70%, decrease expiration-related losses by 40-60%, and improve inventory turnover ratio by 25%. The solution will enable franchisees to focus on customer service while ensuring optimal stock levels, with centralized logistics planning capabilities reducing transportation costs by 15-20% through better demand aggregation.