Brad Mitcheller
Key takeaways
- 11:23Standardizing replenishment across a retail chain replaces inconsistent store-manager judgment with a common planning process that responds to demand, seasonality, promotions, and supplier conditions.
- 14:26Dynamic item-location buffers adjust inventory protection to consumption trends, demand volatility, lead-time variability, critical-item status, and shelf-facing requirements.
- 20:31The demonstration shows 97% replenishment automation, while mature LEAFIO clients commonly automate more than 90–95% of their ordering.
- 24:37Fresh-food replenishment must account for remaining shelf life, daily and intraday demand patterns, delivery timing, promotions, availability targets, and acceptable shrink.
- 37:52The Baltic Petroleum case study reports a 62% sales increase, a 50% reduction in excess inventory, 9% lower lost sales, and an 8% increase in average SKU availability across 86 locations carrying 2,500 SKUs.
Questions Brad Mitcheller answered
Decisions such as assortment changes flow into store execution and replenishment, while planogram facings inform minimum shelf-stock requirements. Connecting merchandising and supply-chain processes reduces manual coordination and keeps inventory plans aligned with shelf decisions.
How AI Fixes Inventory, Fresh Waste & Stockouts in Convenience Retail43:58
Yes. The planning logic considers short lead times, delivery time of day, intraday demand, weekly variation, forecasts, and continuously changing buffers so replenishment can respond quickly while protecting availability.
How AI Fixes Inventory, Fresh Waste & Stockouts in Convenience Retail48:02
In Brad Mitcheller's words
“It’s not about ordering more or less; it’s about ordering smarter.”
How AI Fixes Inventory, Fresh Waste & Stockouts in Convenience Retail27:38
“Here’s how you planned last year. Here’s how we would have planned. Here’s the difference. Here’s the delta.”
How AI Fixes Inventory, Fresh Waste & Stockouts in Convenience Retail40:54