Truck Repair On-the-Road Application
Figma | Design in Coded React Interface
Project Background
Bridging Design and Functionality in Truck Repair
As the lead Product Designer, I oversaw the end-to-end development of “FOX Road Mechanic,” an innovative truck repair platform for an Atlanta-based startup. Over 12 weeks, I took a holistic approach, working from concept ideation to actual product execution, ensuring that design, usability, and functionality were seamlessly integrated. Guided by user needs and technical feasibility, the product was optimized for desktop, tablet, and mobile platforms. This involved the aesthetic and usability aspects, technology integration, and the product’s alignment with business goals.
Team
Product Designer: Michael Long
Program Manager: Julietta Poi
Developers: Lucas Melo, Diego Armando
Setting the Scene
Semi-truck breakdowns lead to significant downtime. Recognizing this, my client saw an opportunity to improve the repair process through an application. They brought me on board to meld design with functionality, ensuring a visually appealing and functional end product.
Context
Unnecessary mechanical problems with semi-trucks annually lead to significant downtime and financial losses estimated at over 1.1 billion annually.
Over the course of the repair process, each phase becomes progressively more expensive. When a truck breaks down, owner-operators may need more knowledge of the mechanical issues with their vehicle, the trailer, or the load. In remote regions, it can be very time-consuming to diagnose a problem and then find the correct mechanical expertise to address the problem.
My client decided this presented an opportunity and wanted to dive deeper into the truck repair process. They hired me as the product designer of the team. First, I wanted to understand the entire process from start to finish with all of the user roles involved.
Process
Discover, Define, Design, and Deliver
I followed the LUMA UX HCD process by first conducting user research. White Paper Research was utilized to gain a broader direction. After synthesizing inspiring insights from Stakeholder Mapping, Ethnographic Study, Experience Diagramming, I formed a group of Subject Matter Experts consisting of people in the industry, including truckers. I defined the problem and jumped right into the ideation phase.
UX Exercises
Journey Mapping: UX Experience Diagramming visually represents a driver’s interactions, highlighting potential areas for design and efficiency. This was vital, especially for drivers like Murphy, who helped us understand the challenges faced on the road. Given truckers’ unique needs, this process ensures the app offers clear information with minimal distractions.
Ethnographic Study: I looked at both user needs and how mechanics, drivers, and fleet managers interacted with similar technologies, ensuring our product was ahead of the curve.
Competitive Analysis: Beyond just evaluating existing trucker applications in the market, such as Samsura Driver and Teletrac Navman, I identified their strengths and weaknesses and derived insights that will inform the design and functionality of my app. I looked at transportation apps in the following categories: Communication and Dispatch, Load Boards and Freight Matching, Electronic Logging Devices (ELD), Fuel Management and Optimization, Maintenance and Repair Logs, and Tire Management.
I dove deep into the technical aspects of competitors, ensuring our product was both better designed and more technically advanced.
Samsura Driver exhibits a lack of responsiveness, provides merely referral information, and has unsatisfactory alert systems, contrasting with Teletrac Navman which offers real-time alerts and delivers a mix of varied features including the provision of engine fault codes. Nonetheless, the current options don’t appear to cater to all user needs, indicating a gap in the market for a more intuitive, inclusive, and advanced solution, a gap that FOX Road Mechanic aims to fill by creating an application which consolidates multiple features and enhances user interaction, bringing in real-time solutions, AI-driven responses, and a seamless interface to expedite and simplify on-the-road truck repairs.
Research findings
Physical Adaptability: A truck repair often involves multiple devices – from laptops for form filling and research to phones for capturing images from tight spaces like under the cab.
Cultural Adaptability: With 6.3 million trucks coming into the USA from Mexico, an app with localization, especially Spanish, has a significant competitive edge.
Reducing repair escalation reduces costs: Class 8 truck repairs often need to be understood, leading fleet managers and drivers to hastily call mechanics or visit repair shops, resulting in unnecessary expenses. Identifying and addressing simple repairs will reduce costs and save time.
A repair may require a search across multiple sources: From truck repair manuals to forums like TruckersReport, a single repair could require consultation from various sources. Consolidating these would speed up repairs.
Design Goals
How might I empower truckers to swiftly identify and address mechanical issues, ensuring minimized downtime and efficient repairs?
From my research, we’ve discerned a gap between the available solutions and truckers’ real-time needs. Truckers require an integrated platform that assists in accurately diagnosing mechanical challenges, connects them to skilled mechanics, and provides a seamless repair experience tailored to their unique situation. When a simple repair such as a censor, hose, or fuse is malfunctioning it can often be identified and repaired by the driver, significantly reducing costs.
Design Challenges
Communication Breakdowns: A challenge in the truck repair ecosystem is the communication gap between drivers, mechanics, and fleet managers. Transparent and timely communication is paramount to diagnosing and tackling mechanical issues efficiently. Misunderstandings or delays in relaying crucial information can lead to incorrect problem assessments, unnecessary escalations, and prolonged downtimes.
Clarity in Problem-solving Instructions: Ensuring drivers receive clear and actionable guidance when facing mechanical problems is vital. Ambiguity in repair instructions or unclear troubleshooting steps can exacerbate the issue at hand. It’s crucial that the provided solutions are both precise and easily comprehensible to the driver, reducing the likelihood of further complications.
Minimizing Escalation Issues: Every step in the repair process that escalates from the driver to on-site mechanics or to a repair facility incurs more downtime and costs. Concentrating on mechanisms that can preemptively minimize or even eliminate unnecessary escalations can save significant time and resources. This focus requires both clear communication tools and a system that effectively guides the driver through the initial stages of addressing the problem.
Technological Integration: A primary challenge is integrating design goals with robust technical requirements and integrated AI technologies.
Design Decisions
The connection AND communication between the owner-operator and the RIGHT mechanic is paramount for cost savings.
A system for finding and communicating with a qualified mechanic is key to success. Suggested mechanics need to understand the problem and communicate with the driver every step of the way.
An AI Chatbot backed up by human support can help direct the escalation process efficiently.
Leveraging an AI Chatbot in a truck repair application streamlines initial diagnostics and query processing, swiftly identifying common issues. When complex or ambiguous problems arise, the chatbot seamlessly escalates the query to human support, ensuring specialized expertise is engaged. This integrated approach guarantees rapid response times and personalized solutions, optimizing the truck repair experience.
Global Search with Auto-Complete Functionality
Recognizing the diverse challenges and the vast information landscape within the truck repair domain, I prioritized the implementation of a global search feature. This powerful search tool allows users to quickly access specific information or solutions within the platform. To enhance the user experience, I integrated an auto-complete functionality. As users begin to type, the system suggests relevant terms or phrases based on their input, ensuring they can swiftly locate pertinent information. The auto-complete suggestions are designed with error tolerance for common typos and industry-specific jargon, ensuring a seamless search experience. This decision empowers users by surfacing the most important data and minimizes searching time, aiding in quicker problem resolution.
Showcase
End-to-End Quality Assurance
My collaboration with the engineering team was about more than just design fidelity. I ensured that the product was technically sound, scalable, and robust.
Reflections
Interdisciplinary Approach
This project reinforced the idea that a product designer isn’t just about aesthetics. Melding new technologies like AI with design requirements is a far deeper cooperation that can only be achieved with an integrated approach. The consistent workgroups with all stakeholders were very effective.
User-Centric Design is Crucial
Immersing myself in the Interstate trucker ecosystem reinforced the importance of deeply understanding user needs and preferences. Engaging with mechanics, drivers, and fleet managers provided invaluable insights that guided my design decisions.
Simplicity Amplifies Efficiency
Introducing features like the global search with auto-complete simplifies complex tasks. What might seem like a straightforward tool can profoundly elevate the user experience by providing quick and relevant information.