The Descartes Systems Group (DSG) Status update summary

AI-driven transformation in last mile delivery

• AI and machine learning are revolutionizing delivery by learning from real-world execution data, enabling continuous improvement in route planning and service time predictions.

• Traditional static routing models are being replaced by dynamic, data-driven approaches that account for variables like order size, product mix, site conditions, and driver behavior.

• Integrating planning, execution, and customer communication into a single platform enhances real-time visibility and enables proactive, data-driven decision-making.

• Machine learning enables up to 30% greater route density and improved asset utilization without adding trucks or drivers, while also reducing missed delivery windows and overtime.

• Real-time feedback loops, such as Descartes' René, close the gap between planning and execution, driving operational precision and customer satisfaction.

Evolving operational challenges and customer expectations

• Rising costs, labor shortages, and escalating customer expectations are intensifying pressure on fleet operations.

• Customers now demand precise ETAs, real-time visibility, and seamless delivery experiences, making last mile delivery mission critical for both service quality and cost structure.

• A persistent 10%-20% gap between planned and actual routes is often due to reliance on static assumptions rather than real-world data.

• Missed time windows and poor communication are increasingly unacceptable, highlighting the need for adaptive, AI-driven planning.

Benefits of connected, data-driven delivery environments

• Fully integrated systems eliminate silos between routing, dispatch, and customer communication, ensuring seamless data flow and faster response to exceptions.

• Real-time visibility allows fleets to dynamically adjust routes, update ETAs, and communicate changes to both drivers and customers, minimizing disruptions.

• Proactive notifications and dynamic ETAs reduce friction, improve job site coordination, and enable faster service recovery.

• Closing the loop with proof of delivery and feedback capture fuels continuous improvement and deeper customer insights.