Allison Krache Giddens

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…

Inventory audits may be one of retail’s most overlooked revenue opportunities. Every large retailer has invested in software that predicts demand, triggers replenishment, and manages shelf space with precision. Almost none of that software questions whether the inventory number it’s reading is actually correct. A recent study in the Journal of Business Logistics suggests that blind spot is expensive, and that fixing it is one of the more overlooked levers a retailer has for growing sales. The researchers, working with a major UK grocery chain, examined roughly 24,000 products across 11 stores to understand why inventory records drift from what’s physically on the shelf, a problem known in the industry as inventory record inaccuracy. They then ran a field experiment to measure what happens to sales when a store corrects those records through a full audit. The results reframe a task most retailers treat as a nuisance into something closer to a growth strategy. Start with why the records go wrong in the first place. The study found that products carrying more inventory and products replenished more often were significantly more prone to inaccuracy. That makes intuitive sense: every case broken down, every unit moved from backroom to shelf, is…