The NineHertz collaborated with a last-mile logistics company that operates in the western United States. The company operates a delivery fleet of 48 vehicles, consisting of medium-duty trucks and commercial vans. The entire fleet completes 150 to 180 delivery stops every day across urban and semi-urban service territories.
The company mainly serves e-commerce fulfillment partners, B2B wholesale suppliers, and grocery chains. Fuel cost has been one of the highest operating costs for the company, which consumes more than 31% of the total monthly expenditure. However, the incremental inefficiency across 150+ daily stops further drags on the margin when the fuel prices remain elevated.
The biggest challenge for the client was manual route planning, which caused inefficient stop sequences. Dispatchers spend more than 2 hours every morning selecting routes that often consist of unbalanced stoppages, unnecessary backtracking, and high traffic. Increasing fuel prices were another challenge that often accounted for more than a third of the total operational costs.
No visibility into the driver behavior was another challenge, as the fuel consumption was only tracked through the monthly fuel card reconciliation. There was no tracking on idle time, prolonged engine-on period during stops, aggressive acceleration, etc. Moreover, there was no ability to identify and choose a separate route in case of unexpected road closure or traffic.
The NineHertz built a customized route optimization platform that eliminates the need for manual route planning and fosters an automated data-driven routing engine.
We built a route optimization system that suggests routes by analyzing factors like stop locations, vehicle load capacity, delivery windows, and driver shift duration, along with live traffic data.
The new solution is capable of capturing idle time, stop locations, acceleration and braking patterns, engine-on duration, and much more to record driver behavior and its impact on fuel consumption.
Whenever the driver reports a road closure, failed delivery attempt, or significant traffic, the platform automatically calculates the remaining delivery sequence to suggest a new route and processes it in under 90 seconds.
Our team deployed a dashboard that offers real-time insights to the operational manager about projected completion time, active routes, estimated fuel consumption, and much more.
The new route optimization system delivers measurable improvement across operational efficiency, fuel expenditure, and overhead planning within 3 months of deployment.
After the implementation of the new solution, monthly fuel spend dropped by 22%, saving more than $12,000 per month, reducing overall operational costs.
Algorithmic stop sequence eliminated the need for imbalance load distribution and backtracking. Thus, each truck covers fewer miles per day, which reduces the daily fleet mileage.
Navigation planning that used to take 2 hours every morning is now completed in 4 minutes with the help of an automated route suggestion engine without compromising the distance, traffic conditions, and weather reports.
The new system provides information about driver behavior in real time, and the supervisor can connect instantly to the driver. Thus, the idle time was reduced by 31%, leading to significant fuel and cost savings.
