Herb Shear

Special Guest Blog Post written by Chris Cunnane with InterSystems   In a world defined by rapid market shifts, volatile supply chains, and unpredictable customer behavior, traditional forecasting methods often fall short. Relying primarily on historical data is no longer enough. To stay competitive, organizations are increasingly turning to demand sensing and forecasting, an approach that blends real-time data, advanced analytics, and AI to anticipate demand more accurately and respond faster to change. This shift is not limited to retail or manufacturing. Demand sensing is transforming how organizations across industries plan operations, allocate resources, and improve service levels. Below, we explore key industry use cases where demand sensing is delivering measurable value, and why businesses should care.   Why Demand Sensing Matters Demand sensing moves beyond static historical trends. It incorporates current, high-velocity data signals such as sales transactions, weather patterns, logistics feeds, economic indicators, and even social sentiment to generate short-term demand forecasts that reflect real-world conditions. The benefit is clear. Organizations gain better visibility and responsiveness across procurement, production, inventory, and distribution. Instead of reacting to outdated forecasts, they can make timely decisions that reduce costs, prevent stockouts, and improve customer satisfaction. FMCG, CPG, Retail, & E-Commerce Fast-moving…

In today’s increasingly complex global supply chain landscape, Tom Moore keeps his message refreshingly straightforward: ProvisionAI helps large companies discover hidden costs and eliminate them. Organizations such as Procter & Gamble, Nestlé, and Unilever have leveraged the company’s technology to uncover and eliminate inefficiencies—particularly in transportation and warehousing—that traditional systems fail to detect. The outcome is significant and often delivers immediate savings. But Moore believes many of these problems stem from misunderstandings about the very technologies companies rely on.   Misnamed Systems & Misaligned Expectations Before the interview officially began, Moore reflected on the surprisingly inaccurate names assigned to modern supply chain technologies. ERP systems rarely plan resources across the enterprise, despite what their name suggests. Warehouse Management Systems, while certainly used in warehouses, don’t actually “manage” much at all. People behind keyboards still make most of the critical decisions. This disconnect in terminology shapes faulty expectations. Many organizations believe their planning systems will truly plan the supply chain, yet most tools merely react to demand signals. If ABC Company orders ten cases, the system automatically replenishes—without considering warehouse capacity, transportation availability, downstream implications, or cost-to-serve. Moore characterizes this as both an old problem and a new one, and it…