Case Studies
RL Auto Repair
A research-driven product concept designed to optimize lift station turnover and reduce service delays in small auto repair shops.
Project Type
UX Case Study
Roles
UX Researcher, Product Designer, Strategist
Tools
Figma, Illustrator, After Effects, Inshot
Timeline
~15 Weeks
To be continued…
Overview
This project is a product/UX design concept, collaborating directly with mechanics and shop staff to simulate scheduling logic through a concierge MVP. The goal was to reduce downtime for short jobs, improve task visibility, and streamline customer drop-offs.
Research & Strategy
Multiple days were spent observing and interviewing workers at a local family-owned auto shop.
Key methods included:
Contextual interviews with technicians, managers, and customers
Service blueprinting to map out current pain points
Time tracking and lift usage analysis
Identification of job types by duration, tools, and value
Key Insight
Short jobs, when clustered together without strategy, created unpredictable downtime and service gridlock.
Mechanics also lacked visibility into the upcoming queue or who was available to help.
Ideation & Prototyping
After defining core job categories and user types (mechanics, service advisor, manager)
Valerie developed:
Job scheduling logic based on duration, part arrival, and lift station availability
Smart queue system that prioritized small, fast tasks when lift time opened up
Concierge MVP: Manual, hands-on simulation with real shop staff with the Minimum Viable Product
The Solution
The proposed system included:
A digital lift map showing current and upcoming jobs
Smart job queueing that bubbled up low-time, high-frequency tasks
An optional voice-based command system (e.g., “What’s next on Lift 3?”)
Customer drop-off tracking and after-hours key return system
Visual Scheduling for service writers to pre-plan busy days
A design system with branding, color, and UI elements approved by the shop, ensuring alignment with their existing identity and maintaining familiarity for staff and customers
Key Insight
Short jobs, when clustered together without strategy, created unpredictable downtime and service gridlock.
Mechanics also lacked visibility into the upcoming queue or who was available to help.
Results & Reflection
Mechanics reported better visibility into workload and availability
Manager spent less time manually reshuffling jobs
Customer wait times decreased for quick walk-in jobs
What was Learned
This project taught Valerie how to balance systems thinking with real-world feasibility.
Working alongside actual shop workers brought invaluable feedback and grounded her design decisions in practicality, not solely aesthetic and assumption.
Testing with a Concierge MVP made it easier to validate flow and logic before jumping into high-fidelity visuals.
