Angie Taylor

Supply chains today are drowning in data but still struggling to answer critical questions. Inventory is visible but not always explainable. Lead times exist in the system, but don’t always reflect reality. Improvement opportunities are identified, yet often fail to translate into action. In this white paper, explore four common challenges that prevent organizations from turning supply chain data into better decisions, and learn where AI can provide real value by improving diagnostics, prioritizing action, and uncovering patterns across complex operations. What You’ll Learn Where AI really improves supply chain outcomes and where it doesn’t How to turn “visible” inventory into something you can actually explain and act on Why many AI initiatives fail and what it takes to drive real impact How to spot hidden inefficiencies in lead times, planning settings, and governance Download the White Paper Discover how leading organizations are moving beyond dashboards to create greater visibility, stronger alignment, and more effective supply chain decisions.

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 Instead of reacting to outdated forecasts, they can make timely decisions that reduce costs, prevent stockouts, and improve customer satisfaction.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…