Alan Seid

Prospects of supply chain automation have the industry abuzz. It’s even become a major sticking point in the International Longshoremen’s Association contract negotiations with the United States Maritime Alliance. The dockworkers do not want ports to automate processes out of fear they will lose their jobs to machines. Today, there are seemingly endless possibilities for optimization. Terms like generative artificial intelligence and machine learning have become commonplace in discussions about ways to gain efficiencies and reduce costs. Can man and machine work together as businesses leverage automation for optimization? Beyond the Buzz: Understanding the Automation Imperative Machine learning, a subset of artificial intelligence (AI), is described by Business News Daily as a later-stage development in which machines take in data on their own and then analyze it. Automation, on the other hand, is fixed on repetitive tasks; after a job is performed, an automation system “thinks no further.” The Business News Daily article explained that “automation involves an entire category of technologies that provide activity or work without human involvement,” while AI involves “a machine exhibiting and practicing something similar to what we describe as human thinking – that is, the ability to interact in thousands of ways with the…

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…