Logistic Case Study
Dynamic routing and pricing can be a challenge for even the largest of trucking firms. That was the case with one large client of ours: they were doing some things programmatically internally, but it wasn’t efficient, dynamic, or all-encompassing. And with human interaction with the routing, there’s invariably only so many data points that can be addressed in the decision-making process… and humans are biased. They wanted a robust, dynamic, and real time scheduling algorithm that factored in a number of historical data points.
They also wanted to avoid the long delays caused by spending hours or even days to find the record and rules that the scheduler was using and then fix that algorithm. They wanted a programmatic way to speed data processing, improve decision-making quality, and decrease the historical evaluation time.