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Too much dependency on manual operation. This have let to a fairly challenging situation to allow maximization of the truck capacity.
The challenges of losing capacity due to the regulatory change that requires customer to remove modification to their vehicle that allow over dimension and over loading capability. The removal of this over dimension and over loading will reduce the total capacity of Customer by 40%. Thus there is a need for a solution to help maximize capacity usage and reduce or delay the need to acquire vehicle to replace the reduced capacity.
Using a fix assigned truck approach for customer do not help. Customer better maximize the available truck and its capacity.
Unmaximized revenue per trip, as Customer get paid per motor bike delivered or collected, the ability to maximize truck utilization and capacity will help Customer increase revenue.
Lack of proper integration for the GPS also leads to inefficient use of GPS information.
Low utilization of trucks, by improving routes management and truck tracking to know the position of trucks.
Leveraging the concept of “first come first serve” in assigning trucks to delivery order rather than best fit capacity thus lead to further capacity maximization issues.
Reduce errors in operations and reduce latency of operations to improve productivity and speed up operations.
There is a significant rate of failed delivery due to address is not found and missed delivery time-window.
Increasing revenue per trip. Load Maximization. By considering multiple product size and its arrangement, it will improve the utilization rate / truck. Therefore, more unit = more revenue.
Distribution to drivers are not balanced and optimal. Management found cases where 1 drivers can take up 40 delivery orders while other driver only have 1 delivery order.
Reducing cost / trip. Route management and optimization. By considering SAP Express cost-structure to drivers, drivers will get assigned to maximize their trip within delivery duration.
Given limited area assigned to drivers, there is a potential unbalanced delivery orders per area that result in idle drivers.
Driver Availability. Automate in delivery order assignment to available drivers will increase trip rate / driver and reduce idle resources.
Delivery sequence. Arrangement of products based on route will improve delivery time by lower unloading time.
Truck Delivery Progress. Operations can be more effective and more predictable by knowing how many products are delivered and driver’s progress rate to complete trip.
Looking for local route optimization that can adapt to Indonesian map and perishable product restriction.
Load maximization by considering product restriction to reduce risk of product damage.
Low load maximization due to manual process of routing.
Delivery route is optimized based on location, time and number of orders to serve maximum revenue possible.
Low truck utilization rate per day is low due to varieties of store working hours and restriction in maximum time of delivery.
Loading and unloading time is optimized based on driver experience and behavior.