Uber freight
Case study - Team work - 8 weeks - 2025
In this project, we focused on addressing loading delays, a critical challenge
in freight logistics that leads to increased costs and inefficiencies.
Through research, we identified gaps in the system and designed three key solutions:
a structured input step for shippers to improve planning, a real-time tracking feature for drivers to enhance visibility,
and a performance dashboard to monitor
and optimize loading efficiency.
What is uber freight ?
A digital freight brokerage platform that connects shippers and carriers, transforming the traditional trucking industry with technology-driven solutions. By leveraging automation, real-time data, and AI-driven optimizations, Uber Freight streamlines logistics operations, reduces inefficiencies, and enhances transparency across the supply chain. As a key player in the U.S. freight market, the company enables businesses to move goods efficiently at scale
while providing truck drivers with better access to loads and improved route planning.
the problem
Delays in the truck loading phase at large warehouse shippers.
We identified that the loading process serves as a significant bottleneck, where delays of one or two hours at the beginning of the process can accumulate and disrupt the entire day's logistics operations.
the users and their challenges
01
Shippers
Shippers struggled to coordinate efficient loading schedules, causing delays and increased costs.
02
Truck Drivers
Drivers face long waiting times at loading docks due to poor scheduling, impacting their income and daily routes.
03
Customer Success
& Support Teams
Inefficient coordination between shippers and drivers led to delays, financial losses, and lower customer satisfaction.
How might we
Improve the coordination and efficiency of loading processes to reduce delays in Uber Freight?
research & analysis
As part of our research, we used multiple methods to understand the causes of delivery delays. We analyzed discussions on social media, interviewed a truck driver from the U.S., reviewed industry articles, and listened to logistics podcasts.
We discovered that while external factors such as weather conditions, contribute to delays, the primary bottleneck lies in the loading process. Delays of one or two hours at this stage can accumulate, disrupting the entire shipping schedule.
insights
01
Lack of Coordination
& Scheduling
Unscheduled loading times create congestion, confusion, and inefficiencies for both drivers and warehouses.
02
Inefficient Resource Management
Poor allocation of workforce and limited availability of operational teams during loading lead to delays and inefficiencies in the process.
03
Poor Communication Between Drivers & Warehouses
A lack of real-time updates leads to misalignment, causing drivers to arrive without clear instructions, resulting in extended wait times and accumulated delays.
how it works today
Uber Freight’s TMS (Transportation Management System) allows shippers to book freight, schedule pickup and delivery,
and receive pricing from available drivers. However, the system primarily focuses on the endpoints, neglecting the loading stage.
our solution
As part of our solution, we integrated an advanced AI tool that calculates the estimated loading time based on the data entered by the shipper in previous steps. After providing shipment details, workforce, and resource requirements, the algorithm analyzes the information and generates an accurate loading time estimate. This allows shippers to better organize their schedules, prevent delays, and optimize the overall efficiency of the freight process.
01
for the shippers
We developed a solution that integrates smart scheduling directly into Uber Freight’s TMS. Shippers can now set defined loading time slots, provide real-time updates to drivers and warehouses, and allocate resources accordingly.
After entering all necessary loading details, shippers receive
a calendar invite on their phone with full shipment information. On the loading day, 30 minutes before the scheduled time,
they receive a reminder with all pre-entered loading requirements to ensure a fast and efficient process.
o2
for the drivers
To enhance the driver experience and reduce uncertainty and delays,
we developed a solution that provides precise and accessible information at every stage. Drivers receive the exact location within the warehouse where they need to arrive, eliminating the need to navigate large facilities on their own. Additionally, we designed the driver’s interface to display only the most relevant information at each step, preventing information overload. Drivers receive notifications at the start and end of the loading process, allowing them to anticipate potential delays. Lastly, we introduced a real-time reporting feature, enabling drivers to flag any issues causing delays, improving the overall efficiency of the process.
Customer Success & Support Teams dashboard
AI-powered search
Allows users to search for specific data, such as warehouses with the highest delays.
Customer service info cards Provide a snapshot of open issues, response times, and delay resolution rates.
Real-time shipment tracking table
The core of the dashboard, allowing users
to monitor shipment status, view delays,
and directly contact shippers or drivers
for real-time updates.
The purpose of the dashboard is to provide users with data-driven insights into loading times and shipment delays, enabling them to identify issues, optimize processes,
and improve workflow efficiency.
It consolidates critical real-time information, highlights key delay factors, and supports fast, informed decision-making through advanced tools such as AI-powered search, global filters, and real-time shipment tracking.
Delay cause breakdown
An interactive component
that categorizes key delay
factors, including navigation
issues, system failures,
and warehouse readiness.
Loading time comparison
A graph displaying the gap between scheduled loading times and actual performance.