Kurt Albertson

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…

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…