The increasing volume of e-commerce channel transactions and changing customer expectations are putting immense pressure on transportation planning in order to improve last-mile delivery of industrial and consumer goods, such as white goods and installation services. However, traditional big box planning and execution technologies with focus on inbound operations lack the functionality to support the last leg of delivery.
In a typical final mile delivery, operational planning starts at the hub with customer orders being initiated via an electronics channel and consolidated further based on the customer’s requested delivery date. To minimize the cost of transportation, orders are consolidated by pooling shipments into a single or multiple line-hauls, from point of production to the final distribution center in a supply chain. In addition, shipments are usually cross-docked from larger full truck loads to smaller delivery trucks such as straight trucks in various configurations. Once cross-docked into smaller trucks, shipments are delivered or installed the same day to the final customer address (see Figure 1). Customers are constantly pressing business-to-business (B2B) and business-to-consumer (B2C) logistics companies to make the final mile delivery more responsive and visible through enhanced shipment tracking using industrial internet of things (IIoT) and mobile order management.
Figure 1: Traditional final mile delivery planning
This clearly warrants an end-to-end transportation management solution that helps address unique requirements of Industry 4.0 such as order management, appointment scheduling, dynamic routing, cross-dock operations, driver application, transportation planning, dynamic routing, customer communication, driver mobile application, and track and trace capability. This is crucial for enabling efficient and customer-centric final mile operations.
Key Considerations | Evaluation Parameters | Logistics 4.0 Enablers |
Appointment Scheduling / Re-scheduling |
| AI, ML, Mobility, Cloud |
Dynamic Routing |
| AI, ML, Cloud, IoT
|
Cross-dock Operations |
| AI, ML, Cobots, IoT (RFID)
|
Driver Application |
| Mobility, Cloud, IoT
|
Digital Quality Assurance |
| Mobility, AI, ML Cloud
|
Customer Service & Communications |
| Mobility, Cloud
|
Tactical Planning (What-if) |
| AI, ML, Cloud |
Figure 2: End-to-end transportation management solution
Dynamic routing model for logistics 4.0: The key to enhancing customer experience
One of the key factors influencing customer experience and satisfaction is the customer’s ability to schedule and reschedule specific delivery appointments. The reason: appointment schedules directly impact transportation plans and execution efforts. However, a traditional uni-directional approach of planning and execution hampers the customer’s ability to pick specific time slots based on availability for delivery or installation of products (white goods). Additionally, when a customer re-schedules an already scheduled order, the conventional process of transforming a static appointment schedule into the transportation plan results in inefficacy and delay, thereby impacting customer satisfaction and metrics such as on time in full (OTIF) (see Figure 3).
Figure 3: Dynamic routing and delivery promise
Dynamic routing and scheduling are core to the last mile process and need to be driven by an optimization engine which will keep the plan under constraint and simultaneously schedule the order. This helps allocate the right resources to fulfill specific appointments while reducing transportation costs and improving customer fulfillment experience. At the same time, it also avoids potential delays and delivery failures by notifying the customer and enabling self-service user experience.
Ensuring successful fitment of technology
Selecting technology, such as commercial-off-the-shelf (COTS) software, needs careful evaluation based on critical success factors for last mile delivery. This will help bake the solution into the conventional product evaluation framework and enable successful fitment of technology for logistics 4.0 transformation. The end result: enhanced consumer behavior, improved operational efficiency and productivity, increased customer satisfaction through flexibility, better product velocity, and inventory turnover.