| CPC G06Q 10/08 (2013.01) [G06Q 10/063116 (2013.01); G06Q 10/06315 (2013.01); G06Q 10/067 (2013.01)] | 16 Claims |
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10. A non-transitory machine readable medium storing instructions executable by a processing device, wherein execution of the instructions causes the processing device to implement a method for determining a transportation workload, the method comprising:
accessing, by a dwell time module of a computing device, the dwell time module comprising a dwell time circuit, over one or more geographically distributed communication networks, data collected in real-time from a plurality of mobile computing devices associated with a plurality of delivery vehicles, the plurality of mobile computing devices communicably coupled to the computing device over one or more geographically distributed communication networks, wherein each of the plurality of mobile computing devices comprises one or more sensors configured to sense and collect real-time data relating to at least one of a speed, a distance traveled, and a time taken to travel the distance for the respective associated delivery vehicle, and wherein each of the plurality of delivery vehicles is operated by one of a plurality of drivers;
tracking, by the dwell time module, non-driving time for the plurality of drivers engaged in delivering inventory to a store via a plurality of routes based on the real-time data from the one or more sensors associated with each of the plurality of mobile computing devices;
accessing, by a forecast module of the computing device, the forecast module comprising a forecast circuit, over the one or more geographically distributed communication networks, from a first database storing data from a central office serving a plurality of distribution centers, historic non-driving time data and the tracked non-driving time, wherein a distribution center serves a plurality of stores, and forecasting an amount of transportation miles needed to deliver inventory from a distribution center to a store based on a sales forecast for the store for a defined time period, the tracked non-driving time, and the historic non-driving time data;
calculating, by the forecast module, an amount of time needed to deliver the inventory by dynamically converting the forecasted transportation miles to a time value and adding the time value to the non-driving time;
accessing, by a staffing module of the computing device, the staffing module comprising a staffing circuit, over the one or more geographically distributed communication networks, the first database storing data from the central office and a second database storing data from the plurality of distribution centers, and communicating with the forecast module to retrieve the amount of time needed to deliver the inventory calculated by the forecast module;
generating, by the staffing module, an optimal transportation workload for the distribution center based on the amount of time needed to deliver the inventory calculated by the forecast module, data from the first database storing data from a central office, and data from the second database storing data from the distribution center, wherein the optimal transportation workload defines driver schedules by assigning at least some of the plurality of drivers and delivery vehicles to deliver the inventory from the distribution center to the plurality of stores;
generating, by the staffing module, and causing to display on a visual display device of the computing device, a user interface displaying the optimal transportation workload; and
dynamically updating, by the staffing module, the optimal transportation workload and the user interface displaying the optimal transportation workload when a store is realigned to be served by a different distribution center.
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