A parcel shipping company was examining their annual shipping expenses to identify potential savings. They had policies for using overnight shipping in certain situations, 2-3 day shipping for most cases, and ground shipping for everything else. Since air services for overnight and 2-3 day shipping cost significantly more than ground shipping, they wanted to find ways to reduce these costs.
We analyzed their shipping data and rules system, building a learning algorithm to evaluate how their shipping practices aligned with their policies. By running three years of shipping data through the algorithm, we discovered two key insights. First, they frequently violated their own policies, presenting a coaching opportunity for immediate cost savings. Second, we found that their rules needed revision. Many of their shipping destinations were within a 2-3 day ground shipping zone from their facility, meaning they were overpaying by choosing air services when ground shipping would have been just as timely and much cheaper.
This analysis helped them adjust their decision-making processes, leading to significant cost savings without compromising delivery times.
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