Challenge:

Reduce inventory waste, improve demand forecasting accuracy, and streamline supply chain operations across global retail outlets.

AI Solution:

Levi’s partnered with AI firm [Nextail] to deploy machine learning models that predict demand at the store level. The system analyzes historical sales, local trends, weather, and promotional calendars to optimize inventory distribution and replenishment.

Implementation Highlights:

• AI forecasts demand per SKU per store
• Automated inventory allocation and restocking
• Integrated with ERP and POS systems across regions

Quantifiable Results:

• 90% inventory accuracy across stores
• 1% waste rate (down from 5–7%)
• Faster sell-through and reduced markdowns

Strategic Insight:

Levi’s shows how AI can align sustainability with profitability. By minimizing overproduction and improving shelf availability, they reduced waste and boosted margins—an ideal model for retail brands balancing ESG goals with commercial performance.