Uber Freight - Complex System
Designing for Logistics:
From Industry Challenges to AI-Driven Solutions
Team
Noy Goldenbeg
Paz Mali
Mor Perry
Sharon Friedman
Duration
5 Weeks
Jan-Feb 2024
Disciplines
User Experience Design
User Interface Design
Responsibilites
UX Research
Data-Driven Analysis
Design Thinking
Wireframing
Prototyping
Shipper
CS team
Carrier
Inaccurate data
Shippers | Carriers | Customer Success
Prevention | Live Problem Solving | Proactive Monitoring
1 major problem
3 users
3 AI-driven solutions
OVERVIEW
Enhancing the freight experience through smarter UX— focusing on designing for a B2B complex system. streamlining load management, reducing errors from inaccurate shipment data, and improving workflows for shippers, carriers, and support teams.
The Problem
Inaccurate Shipping Data Costs Billions
Every year, businesses lose $600 billion in the freight industry due to inaccurate or incomplete shipping data. These errors ripple through the supply chain, causing delays, cancellations, and unnecessary costs.
Background
Understanding Uber Freight and the US Trucking Industry
Uber Freight is a global logistics company that connects shippers and carriers via a digital platform.
Our focus was on the U.S. trucking sector, where the complexity of the logistics landscape—comprising companies of various sizes and cargo types—presents unique challenges.
Through Uber Freight's platform, both shippers and carriers interact via web and mobile applications, facilitating transparent and efficient freight operations.
Research
How inaccurate shipping data translates into loss of penalties
One key finding was the NMFC Code—a numerical classification that determines freight costs based on cargo attributes. A mistake in this code can result in:
-
Unsuccessful pickups, leaving trucks empty
-
Partial shipments, increasing inefficiencies
-
Unnecessary fees and penalties
Shipper Persona
Bev
Owner of Bev's Beverages
Goals
Deliver shipments smoothly, ensure customer satisfaction, avoid unexpected fees.
Pain Points
Complex freight terminology, risk of incorrect data entry, costly penalties for mistakes.
Needs
Clear guidance during order entry, real-time validation of freight details
The Carrier - Persona
Carlos
Independent Truck Driver
Goals
Complete deliveries without unexpected surprises and getting home on time after completing daily deliveries.
Pain Points
Incorrect freight details leading to mismatched shipments, wasted fuel and time, financial losses from cancellations.
Needs
Accurate shipment details before pickup, ability to adjust loads dynamically, fewer scheduling disruptions.
Personas
Pain points, Goals & Needs
The Shipper
Bev
Owner of Bev's Beverages
Goals
Deliver shipments smoothly, ensure customer satisfaction, avoid unexpected fees.
Pain Points
Complex freight terminology, risk of incorrect data entry, costly penalties for mistakes.
Needs
Clear guidance during order entry, real-time validation of freight details
The Carrier
Carlos
Independent truck driver
Goals
Complete deliveries without unexpected surprises and getting home on time after completing daily deliveries.
Pain Points
Incorrect freight details leading to mismatched shipments, wasted fuel and time, financial losses from cancellations.
Needs
Accurate shipment details before pickup, ability to adjust loads dynamically, fewer scheduling disruptions.
CS Team
Elaine
Customer Success & Support
Goals
Streamline dispute resolution, improve efficiency, enhance user satisfaction.
Pain Points
High volume of disputes from incorrect freight classifications, slow resolution times, repetitive support cases.
Needs
Real-time data on common errors, AI-driven tools to assist users before issues arise, a simplified workflow for dispute resolution.
The Shipper
How might we help business owners prevent errors in their shipping data?
Today
The current
order entry form
The Solution
AI-Powered Order Helper
A chat designed to guide users through the form, minimizing mistakes and confusion.
UX Principles
How it works
Progressive Disclosure
Reduction of cognitive overload - The form is broken into expandable sections.
Ai step-by-step support
Context-Aware: The AI assistant detects which section Bev is in and simplifies complex logistics terms.
Real-Time Validation
As the form is completed, green checkmarks confirm correct inputs, ensuring accuracy before submission.
The Carrier
How might we help carriers prevent shipment cancellations due to inaccurate information?
The Solution
Introducing Load Split:
We developed Load Split, a feature that allows carriers to adjust their shipments dynamically instead of canceling them entirely.
Business Value
Predicting potential issues, the system enables:
Shippers
Split their loads into multiple shipments
Carriers
Maximize truck space and reduce empty miles
Uber Freight
Maintain seamless logistics with fewer cancellations & issues
Business Value
Predicting potential issues, the system enables:
Shippers
Split their loads into multiple shipments
Carriers
Maximize truck space and reduce empty miles
Uber Freight
Maintain seamless logistics with fewer cancellations & issues
Customer Support & Success Team
Problem: High volumes of disputes and slow resolutions due to incorrect freight details.
The Solution
AI-Powered Dashboard
Monitoring and resolving shipment issues in real time.
AI mistakes value
Key Features
Optimizing response & mistake prevention
Mistake Type Distribution
Real-time panel
Split load data
Disputes monitoring
Real-time panel
Split load data
Disputes monitoring
AI mistakes value
Mistake Type Distribution
Impact
A More Efficient Freight System
With our UX solutions, we improved the experience for all stakeholders:
Shippers
Prevent costly mistakes and ensure timely deliveries.
Carriers
Avoid shipment cancellations and optimize truckloads.
Uber Freight
Benefits from fewer disruptions, reduced delays, and improved operational efficiency.
