Supply Chain Pocket Change?

As a company’s supply chain network evolves over time, information needed for adaptive efficiency becomes isolated in hard-to-find data pockets. In those instances, data required to drive modern efficient operations is isolated and not instantly accessible—usually housed on old world siloed spreadsheets. Do you have supply chain data points in hidden pockets?

Modernized business operations require that fragmented data be unified and presented in a cohesive and relational format, on demand. AI can help connect these sources and light up decision-making needed to reduce operational inventory and better match supply to quickly changing sources, prices, and demand.

This exact challenge recently faced 6,000+ Wendy’s restaurants. Before implementing AI and combining that with a digital twin of its complex network, Wendy’s reportedly had a piecemeal and disconnected spreadsheet-based logistics network, which led to many manual processes that slowed response time and created higher transport and inventory costs.

That legacy management process resulted in higher inventory levels as a hedge against customer service risk, but also repeatedly resulted in unsustainable inventory bloat given high storage and labor costs.

In February 2025, Wendy’s launched a new Thin Mints Frosty flavor, and its popularity took off thanks to consumers who bought Thin Mints cookies from the Girl Scouts for decades. It wasn’t long before a demand imbalance was made evident: Wendy’s had sufficient inventory but not where customer demand spiked.

A digital twin of the network, coupled with AI inventory, prompted Wendy’s to immediately move enough product to prevent a customer service fail. The Thin Mints Frosty example brings the benefits of a modern AI supply chain regime into focus. Specifically:

• Fragmented, spreadsheet-based logistics systems and manual processes led to slow response, costing money in stock outs, unbalanced inventory, and lost sales.
• Wendy’s held $370 million in inventory across its network—a strategy driven by risk aversion but unsustainable due to rising labor and storage costs. AI offered the same low risk without the cost.
• Slow reaction times to disruptions and unexpected demand shifts.

Data was available for Wendy’s to resolve its inventory challenge in a few minutes. But spreadsheet data hidden in distributed pockets? That would have taken a team one day to achieve the same result.

AI can help you find pocket change in your supply chain.