AI in Supply Chains: Trusted Data Makes AI Work

Demand sensing and demand forecasting are both crucial aspects of optimizing supply chains, but they do have slightly different functions in their approach and focus. Demand sensing uses real-time data and analytics to identify and respond to immediate demand fluctuations, while demand forecasting uses historical data to predict future demand over a longer period (months or years). Different methods, such as statistical modeling and machine learning, are used to enhance the accuracy and adaptability of these processes. Both areas are crucial for companies when it comes to projecting sales, managing inventory, and coordinating replenishment. In the end, the goal is to accurately predict customer demand by using predictive models to forecast future demand.

Healthcare Supply Chains Need More Than Visibility — They Need Orchestration

At MODEX 2026 in Atlanta, Scott Luton sat down with Andre Luecht, Global Strategy Lead for Transportation, Logistics & Warehousing at Zebra Technologies, to explore how synchronization, visibility, and practical innovation are shaping the next phase of supply chain performance.

Accelerating Decision Velocity: Why the Future Belongs to Faster, Smarter Supply Chain Decisions

Here is a diagnostic question I use with supply chain leaders: when disruption hits, do your teams spend most of their time debating the data, debating the scenarios, debating the plan, or debating the decision? Or all of the above?

The Buzz: Copper & Chemicals, Tariffs & Trade Tensions

Today we dive into the intricate dynamics of supply chain orchestration, drawing a compelling analogy between the orchestration of supply chains and the harmonious and complex performance of a symphony. Welcome to The Buzz!