Cathy Morrow-Roberson

When healthcare supply chains break down, the consequences are measured in more than missed delivery windows or higher procurement costs. They can show up as delayed procedures, frustrated clinical teams, wasted inventory, and, most importantly, compromised patient care. That urgency is at the center of a new Supply Chain Now conversation featuring Mark Holmes, Head of Global Supply Chain Market Strategy at InterSystems, and Michael LaRocca, Founder and CEO of Ready Computing. Together, they explore why healthcare organizations need a new level of supply chain intelligence—and how integrated data, automation, and AI can help hospitals move from reactive problem-solving to proactive orchestration. Why Healthcare Supply Chain Disruption Is Different In retail, a stockout may mean a customer chooses a different store. In healthcare, a missing item can mean a surgery is delayed or canceled. As Holmes puts it in the episode, not having the right product at the right time for the right procedure is a fundamentally different kind of failure—one that affects lives, outcomes, and hospital economics all at the same time. The business impact is significant. Holmes notes that globally, procedure cancellations related to supply availability can average around 10%, with some regions experiencing even higher rates. A…

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…