Dead stock doesn't appear overnight—it accumulates gradually due to five common forecasting mistakes that many ecommerce brands continue to make. According to a recent analysis, 55–60% of dead stock stems from data input issues, not warehouse problems. Accurate inventory forecasting at the SKU level is key to preventing capital from being locked in unsold inventory, which can cost 22–35% of its value in carrying costs.
Brands using AI-driven demand forecasting are reducing overstock by 20–30% and cutting forecasting errors by 15–20% within a single replenishment cycle. The five root causes of dead stock include SKU-level blind spots, seasonal misweighting, ignored competitor stockouts, and fixed lead time assumptions. Top-performing brands achieve 95% inventory accuracy by employing advanced forecasting methods, compared to the industry average of 83%.
To break the cycle, businesses should prioritize ABC analysis and SKU segmentation, and implement AI tools that dynamically adjust to real-time data. The payoff: freed-up capital that can fuel new product launches, advertising, and supplier relationships.