This Week at Supply Chain Now: April 27th – May 1st

The first podcast available for download reportedly was Queen Elizabeth’s 2004 Christmas address. Apparently, people were hungry to download anything they could. Social media influencers, true crime aficionados, comedians, scholars, and business leaders all have stepped up to meet demand. There are now more than 4 million registered podcasts around the world – and more than 100 million listeners in the United States alone. And according to Edison Research, as of June 2024, podcasts occupied 9% of Americans’ total audio consumption time. “From podcast to podcast, thought leadership is everywhere, educating the masses in innovative ways,” Nancy Marshall – aka The PR Maven – wrote in a Forbes Council post. Supply chain-focused podcasts, in particular, have evolved into powerful platforms for building brand authority, sharing thought leadership, and achieving deeper audience engagement. The State of Supply Chain Podcasts in 2025 Podcasts today cover everything from the arts to zoology. In January, several of the top podcasts on Spotify were devoted to crime, self-help, and relationships. The Joe Rogan Experience, ranked No. 5, is categorized as a culture podcast. How I Built This, No. 9, is all about entrepreneurship. Notably, two-thirds of listeners say they hear news discussed on podcasts and…

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…