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February 16, 2021

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

  • Ability to access delivery calendar as order management

  • Schedule, re-schedule, or cancel delivery appointment

  • Ability to integrate with dynamic routing to optimize execution plan

AI, ML, Mobility, Cloud

Dynamic Routing

  • Real-time adjustment of delivery plan to reflect current appointment schedule and execution scenario

  • Optimal allocation of resources such as driver, trailer, and tractors

  • Plan update based on real-time logistics assets tracking

AI, ML, Cloud, IoT


Cross-dock Operations

  • Dynamically assign outbound vehicles / docks to inbound

  • Visually assist XDock lead to direct shipment to correct vehicle

  • Monitor XDock efficiencies and report analytics

AI, ML, Cobots, IoT (RFID)


Driver Application

  • Provide accurate routing / traffic instructions to driver

  • Guide driver in installation and cleaning checklist

  • Track driver and assets location and any cancellations

Mobility, Cloud, IoT


Digital Quality Assurance

  • Professional installation and delivery checklist for driver

  • Instant customer feedback via mobile device

  • Real-time analysis and tracking of CSI and related metrics

Mobility, AI, ML Cloud


Customer Service & Communications

  • 360-degree customer data management and front office enablement

  • Proactive communication about order details and tracking

  • Customer focused order management portal (self-service)

Mobility, Cloud


Tactical Planning (What-if)

  • Create tactical baseline of network and comparing against potential operational scenarios

  • Ability to plan resources such as driver, trucks and equipment

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.

Ajit Talgaonkar leads the logistics and transportation practice for supply chain management in Manufacturing at TCS. He is a subject matter expert on logistics strategy and technology, having over 20 years of experience in the industry. He has previously worked at leading 3PL and technology organizations in transportation, warehousing, and operations.


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