AI Route Planning Sharpens Efficiency & On-time Deliveries

June 5th, 2020    2 Min Read   

Route optimization is a critical component in logistics transportation planning as it paves the way for timely deliveries and helps in lowering shipping costs. There are several factors affecting routing optimization, and all of them must be considered when planning strategies. Finding the best route to take involves analyzing hundreds of data points rapidly and being able to leverage it to your advantage.

Planning for the most optimal routes is even harder when companies are dealing with a high volume of packages and heavy traffic congestion. Fortunately, artificial intelligence and machine learning help in route optimization by using complex algorithms that take into account historical and real-time data to identify optimal routes.

Below are the key benefits of using machine learning and AI for optimized route planning.

Reduce Time Lost to Traffic

The report “Cost of Congestion to the Trucking Industry” released in 2016 revealed that traffic congestion costs the trucking industry as much as $74.5 billion or equivalent to 1.2 billion hours of lost productivity yearly. Traffic congestion costs are close to $6,500 per truck per year.

That was four years ago. Fast forward to 2020, and eCommerce growth has been exponential, with many companies offering the same day or next day shipping options. Plus, returns of orders almost account for 30% of road time. All these are forcing more delivery vehicles on the road, creating more road congestion.

Route planning solutions is one of the best ways of avoiding lost fuel and time due to worsening traffic conditions. Optimizing routes ensures that drivers are passing through roads with the least idle time.

Faster Delivery Times

Competing with big brands and industry leaders like Amazon entails offering faster delivery options. Optimizing routes is crucial in ensuring the timely and efficient delivery of packages to customers. Route optimization helps ensure that company fleets are spending less time on the roads to meet customer demands for same-day order fulfillment by taking road conditions, traffic, and the destination all into account simultaneously.

Helps in Discovering New Potential Routes

Route optimization also means making use of all available resources or infrastructure. Unfortunately, many drivers are only taking routes that they are familiar with, which is natural. But road conditions change over time. For faster travel times, drivers must be guided to alternative routes they can take to avoid heavy traffic congestion and poor road conditions.

Saves Time

The less time a vehicle stays on the road is equal to the reduction of fuel cost and paid hours. Being off the road an hour early can save the company several hundreds of dollars a week, which over months and years, adds to significant added expenses.

eCommerce is growing exponentially, and any business looking to compete against the billionaire brands online must ensure that drivers use optimal routes. Otherwise, enterprises will lose money because of idle time, higher fuel consumption, and more driver hours. Fortunately, AI and machine learning are now being bundled into logistics software at affordable price points, so you can get help in optimal route planning to ensure fast, on-time, and cost-effective deliveries.

DispatchTrack is a leading provider of SaaS solutions that enable end-to-end optimization of operations and customer experiences in last-mile delivery. The company's platform includes modular tools for self-scheduling, route optimization, customer communication, real-time tracking and ETA, proof of delivery, and delivery network intelligence and analytics. With customers across North America, Europe, South America, and Asia, DispatchTrack is used by thousands of businesses of all sizes and many multi-billion-dollar enterprises across a wide range of industries, including furniture, appliances, building supplies, food, and beverage. More than 60 million scheduled delivery experiences are powered by DispatchTrack each year. For more information, visit

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