Off
The “last mile” problem in logistics refers to the last leg in the delivery of a product from supplier to customer. It is often the least efficient link in the supply chain. For local third-party logistics company, Courex Pte Ltd, which supports retailers in their logistics operations, it saw opportunities to use technology to improve its operations in this final crucial stage to overcome challenges in delivering goods in dense urban cities.
Through TechInnovation 2014, Courex came across a technology offering “Real-time Traffic Prediction & Route Guidance” by Nanyang Technological University (NTU). With IPI’s facilitation, Courex commissioned NTU to build a smart algorithm to optimise its route planning. The mathematically computed programme efficiently clusters articles for delivery and proposes the best route to deliver each article in the cluster.
"Our smart algorithm can be scaled up to handle large numbers of traffic routes, which in turn means that the company can handle an exponential increase in deliveries. It is also self-learning and capable of providing alternative routes to drivers to avoid traffic congestion, enabling companies to achieve the most efficient delivery routes, saving both time and fuel costs,” said Assistant Professor Justin Dauwels, NTU’s School of Electrical and Electronic Engineering.
Courex has already benefited from improvements in productivity. For example, scheduling work that used to require two man-hours can now be autonomously completed within minutes with the new system.
“We are convinced by the returns of investment in technology and TechInnovation offered an excellent platform for us to discover and explore potential technologies to achieve greater operational excellence. Beyond operational cost savings, efficient route planning has also enabled us to cut down on our carbon footprint. This innovation provides an added service enhancement to many reputed retailers who place their trust in Courex as the direct touch point with their customers,” said Joe Choa, Managing Director, Courex.
Sub Title
Courex Pte Ltd, a third-party logistics provider, leveraged a smart real-time traffic prediction and route planning algorithm to overcome last mile delivery inefficiencies in dense urban cities, boosting productivity and reducing operational costs.
Impact Title
Driving Productivity and Sustainability in Urban Logistics
Sub Title
Driving Productivity and Sustainability in Urban Logistics
Sub Heading
Smart route planning transforms last mile logistics for Courex.
At a glance
TechInnovation
IPI Service
Smart Real-Time Traffic Prediction & Route Planning
Key Technology
Add Impact
With the implementation of the smart route planning algorithm, Courex experienced a dramatic improvement in operational productivity. Scheduling work that previously required two man-hours can now be completed autonomously within minutes, freeing up manpower for higher-value tasks and enabling the company to handle a greater volume of deliveries efficiently.
Productivity Enhancement
The self-learning system not only optimises delivery routes to save time but also reduces fuel consumption, contributing to lower operational costs and a smaller carbon footprint. Efficient route planning has enabled Courex to enhance its environmental sustainability while delivering added value to its retail clients.
Sustainability and Cost Savings
Sub Title
Courex partnered with NTU through IPI’s TechInnovation platform to implement a smart, self-learning route planning algorithm, leading to significant productivity improvements and reduced environmental impact.
The challenge
Navigating the complexities of last mile delivery in dense urban environments posed significant challenges for Courex. Traffic congestion, unpredictable delays, and the need for timely, reliable deliveries made traditional manual scheduling both inefficient and costly.
Urban Delivery Inefficiencies
Manual route planning required substantial manpower and time, limiting Courex’s ability to scale operations and respond rapidly to increasing demand from retailers. These inefficiencies threatened both productivity and customer satisfaction.
Resource-Intensive Scheduling
The challenges title
The Challenge
The challenges description
The 'last mile' in logistics—the final leg of delivering a product from supplier to customer—has long been recognised as the least efficient and most challenging segment of the supply chain. For Courex Pte Ltd, a third-party logistics provider supporting retailers, this stage was particularly problematic in densely populated urban areas. The complexities of city traffic, unpredictable congestion, and the need for timely deliveries created significant operational hurdles.
Traditional route planning methods often resulted in suboptimal delivery schedules, increased fuel consumption, and higher operational costs. Manual scheduling was time-consuming, requiring substantial manpower to coordinate and optimise multiple delivery routes. These inefficiencies not only affected productivity but also impacted customer satisfaction and the company’s ability to scale its operations to meet growing demand from retailers. Courex recognised that overcoming these last mile challenges was critical to maintaining its competitive edge and delivering superior service to its clients.
The Solution Title
The Solution
The Solution Description
IPI Singapore facilitated a collaboration between Courex and Nanyang Technological University (NTU) through TechInnovation 2014, enabling Courex to commission NTU to develop a smart algorithm for real-time traffic prediction and route guidance. By leveraging IPI's network and technology matching platform, Courex was able to identify and adopt an advanced, mathematically computed programme that efficiently clusters delivery articles and proposes optimal routes for each cluster.
The solution is scalable, capable of handling large numbers of traffic routes, and features self-learning capabilities that provide alternative routes to drivers to avoid congestion. This innovation not only streamlines route planning but also automates scheduling tasks that previously required significant manual effort. The result is a system that enables Courex to manage an exponential increase in deliveries, achieve the most efficient delivery routes, and realise substantial time and fuel savings.
Testimonial Section
Testimonial title
Technology Provider Perspective
Testimonial description
"Our smart algorithm can be scaled up to handle large numbers of traffic routes, which in turn means that the company can handle an exponential increase in deliveries. It is also self-learning and capable of providing alternative routes to drivers to avoid traffic congestion, enabling companies to achieve the most efficient delivery routes, saving both time and fuel costs."
Testimonial Name
Justin Dauwels
Testimonial Designation
Assistant Professor, NTU’s School of Electrical and Electronic Engineering
Testimonial title
Client Perspective
Testimonial description
"We are convinced by the returns of investment in technology and TechInnovation offered an excellent platform for us to discover and explore potential technologies to achieve greater operational excellence. Beyond operational cost savings, efficient route planning has also enabled us to cut down on our carbon footprint. This innovation provides an added service enhancement to many reputed retailers who place their trust in Courex as the direct touch point with their customers."
Testimonial Name
Joe Choa
Testimonial Designation
Managing Director, Courex
Business impact Heading
Business Impact
Business impact title
Productivity gains and sustainability through smart logistics innovation
Impact scores
Counter Text
Productivity Improvement
Counter Text
Scheduling Time Saved
Overview
Courex Pte Ltd is a local third-party logistics company that supports retailers in their logistics operations. The company sought to address inefficiencies in the crucial last mile of product delivery, particularly in dense urban environments, by exploring innovative technology solutions.
Slug
overcoming-last-mile-logistics-challenges-with-smart-real-time-traffic-prediction-and-route-planning
