OPTIMIZING TRANSPORTATION FOR A FOOD RETAIL NETWORK WITH AUTO-PLANNING

ABOUT OUR CUSTOMER

Our customer is a food retail and FMCG company operating a network of more than 100 retail locations across Ho Chi Minh City and Binh Duong.

The business manages approximately 1,000–2,000 B2B deliveries per month, supported by nearly 10 transport contractors and around 100 vehicles.

As all transportation activities are outsourced, effective planning, shipment visibility, and reliable operational data are critical to maintaining service quality across the distribution network.

OPERATING CONTEXT

Food retail distribution operates within highly time-sensitive delivery windows.

Dry goods are typically loaded between 7:00 PM and 10:00 PM and delivered before midnight. Fresh vegetables and other perishable goods are loaded between approximately 1:45 AM and 3:00 AM and must reach stores before 5:00 AM.

Before implementing a centralized transport management system, the logistics team relied heavily on Excel to receive order data, build trips, plan routes, assign vehicles, and communicate plans to transport contractors.

POD, reconciliation records, reporting, and billing also required multiple manual steps, creating additional workload during end-of-period settlement and carrier reconciliation.

KEY CHALLENGES

Heavy reliance on manual transport planning.
As shipment volumes and delivery points increased, manual route planning became increasingly time-consuming and made it difficult to optimize vehicle type, load utilization, and delivery time windows simultaneously.

Limited real-time transport visibility.
With 100% of the fleet outsourced, the business needed early visibility into late vehicle arrivals, delayed departures, and potential ETA exceptions.

Fragmented reconciliation and performance data.
POD, cost data, SLA information, and trip records were spread across multiple sources, increasing reconciliation effort and limiting visibility into carrier performance.

SMARTLOG'S APPROACH

Smartlog STM was implemented to connect the key stages of transport operations within a single platform.

Auto-planning processes transport demand, delivery points, vehicle types, and operational constraints to generate suitable trip plans. The system supports delivery-point grouping, vehicle selection, and load utilization calculations.

During execution, STM monitors key ETD and ETA milestones and issues alerts when delays or exceptions are detected, enabling the logistics team to intervene earlier.

Trip data is then reused across POD, billing, SLA monitoring, and reporting, helping the company establish a more consistent source of transportation data.

RESULTS

In an auto-planning scenario using actual operational data, the system processed 37.722 tonnes of goods across 30 delivery points and generated a plan comprising 18 transport trips.

Key results included:

• 20 seconds to generate the transport plan

• 30 delivery points processed simultaneously

• 87% average vehicle load utilization

• 98.43% highest vehicle load utilization

The results demonstrate the system's ability to process multiple operational variables quickly while giving the logistics team a practical basis for reviewing and adjusting transport plans before execution.

BUSINESS VALUE

STM helps the company move toward a more data-driven approach to transportation management.

Instead of relying mainly on Excel, manual communication, and individual planning experience, the logistics team gains the ability to automate transport planning, monitor delivery progress in real time, and manage trip data within a centralized platform.

For a business operating with a fully outsourced transport network, this data foundation also supports stronger control over carrier performance, SLA compliance, vehicle utilization, and route- or trip-level transportation costs.

This creates a scalable foundation for expanding the distribution network while maintaining operational control.