The shipping of packages has exploded over the past few years and this time of year drives that point home. Supply Chain Dive brought this topic to our attention in their article, “Fast, easy item classification? It’s possible with machine learning and automation.”
More than 87 billion packages were sent globally last year in the 13 major countries tracked by the Pitney Bowes Parcel Shipping Index. Putting that into perspective – it’s more than 2,700 per second, 24 hours a day, 7 days a week. For an entire year.
These numbers will continue to grow as will the expectations of consumers for free or low-cost shipping with a short turn-around. Many organizations are looking for ways to streamline the process by using classification and machine learning to handle the logistics.
Assigning codes to each product for each and every country can be time-consuming and expensive. Doing the process manually takes specialized knowledge of tariff codes and how to classify items. Using machine learning to evaluate each product’s composition, form and function, then applying that data to assign the right codes for the applicable country allows for an accurate determination of customs charges, making it easier for exporters to ship goods and importers to create customs entries.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
