Smarter Forecasts, Fewer Stockouts, Better Margins
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Trafilea is a global e-commerce company that specializes in developing and operating niche-focused online stores. It is based in Uruguay and was founded in 2014. Trafilea owns and operates several e-commerce direct-to-consumer (DTC) brands, primarily in the fashion, shapewear, and wellness industries.
The Challenge
Trafilea operates a global supply chain with production in China and regional warehouses, but five-month lead times and volatile demand made planning a guessing game. Before this project, replenishment leaned on coarse aggregates and manual judgment, leading to partial/back orders, rush costs, and excess stock in the wrong places. We built data-driven demand forecasting and inventory optimization that learns patterns across products and markets, sets warehouse-level safety stocks, and tracks performance transparently—so the right items are available when customers want them, with fewer stockouts and overstocks.
The Solution
Muttdata designed and deployed an end-to-end demand planning service that replaced manual tweaks with a structured, automated approach. The system ingests sales, catalog, promo calendars, lead times, seasonality, and external signals; trains time-series and machine-learning models with hierarchical reconciliation; and produces weekly forecasts, safety-stock and reorder-point recommendations.
Operational rollouts showed a ~25% reduction in stockout-related losses, a 10% improvement in forecast error, and fewer partial/back orders and rush replenishments—while scaling coverage to 93% of DTC SKUs and 82% of Amazon SKUs without disrupting operations.
