Bottom line: Machine learning makes it possible to discover patterns in supply chain data by relying on algorithms that quickly pinpoint the most influential factors to a supply networks’ success — while constantly learning in the process.
Even after winter storms left East Coast harbors thick with ice, some of the country's top chefs and trendy restaurants were offering sushi-grade tuna supposedly pulled in fresh off the coast of New York.
Artificial intelligence promises to have a profound impact on the way in which shippers and carriers do business together. Assuming, of course, that they’re able to make use of the wealth of data that the technology offers.
Home Depot Inc. plans to spend $1.2bn over the next five years to speed up delivery of goods to homes and job sites as the rise of online shopping resets consumer expectations.
It’s lazy to think that a manufacturing process is better just because it’s automated. While the effort going on right now at the Tesla factory in Fremont is anything but lazy, it brings into the spotlight one of the core problems with the simplistic “automation for automation’s sake” strategy: processes that aren’t stable to begin with cannot be made stable with robots.
One year ago this week, Amazon.com Inc. loudly declared its intention to become a grocery industry heavyweight by announcing its agreement to buy Whole Foods Market.
Three years into the Iraq war, facing a spike in casualties from roadside bombings, the Pentagon turned to a steel mill in Coatesville, Pennsylvania, to supply emergency armor for combat vehicles.
Forklift sales are up and continuing to rise. In the North American market, 2017 sales were up 9.5 percent over 2016, reaching a new benchmark of 253,146 units sold.