Machine Learning and Artificial Intelligence (AI)

See how a small parcel shipper found out how to save money by adjusting their decision making

A parcel shipping company was analyzing their annual spend and whether there were opportunities to save money on their shipping. They had policies in place that they would only use overnight shipping in certain circumstances, and 2 or 3 day shipping for most circumstances, and ground shipping for anything else. In shipping overnight, and 2 and 3 day services are air services which cost considerably more than ground shipping.

We took their shipping data and their rules system and built a system to learn their shipping data and how it applied to their rules. After running three years of their shipping data through the learning algorithm, we determined that not only did they violate their own policies quite frequently, which created a coaching opportunity for them to get immediate cost savings, but we also concluded that their rules needed revision, as most shipping destinations they shipped to were within a 2-3 day ground shipping zone from their facility. This means, they were overpaying in instances where they would choose 2 or 3 day shipping as an option in any case where the destination was close enough to ship ground at a lower cost with no real delay of delivery.

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