CASE STUDY ONE
Increasing Maintenance Completion Through Accountability and Automation
Role: Product Designer, UX Researcher
Tools: Figma Make, LLMs, Codex, Lottie, Hex Analytics
Tools: Figma Make, LLMs, Codex, Lottie, Hex Analytics
The Problem
Fleetio's Maintenance Shop Network connected customers with thousands of service providers, but actual maintenance work was still falling through the cracks. When a vehicle became due for service, users received an alert and access to a directory of repair shops. While the platform successfully identified maintenance needs, it did little to help users take action.
As a result, overdue work accumulated, vehicles remained in service longer than intended, and repair opportunities were lost. This gap created challenges for both customers and the business. Customers struggled to keep vehicles compliant, safe, and operational, while Fleetio missed opportunities to drive engagement with its Maintenance Shop Network and increase completed service transactions.
but it surfaced information without providing enough guidance to drive decision-making.
Lean Research Results
Through a series of quick and simple user interviews, as well as asynchronous workflow analysis in heap, we discovered the issue wasn't awareness—it was execution. Fleet managers faced three points of friction:
- No clear owner for getting maintenance done
- Manual and limited coordination between managers, drivers, and shops
- Too much effort required to choose a repair provider
The Approach
Rather than expanding the shop network, I focused on reducing the effort required to move from maintenance identified to maintenance scheduled.
I designed a workflow that enabled fleet managers to: assign reposponsibility for maintenance, notify drivers via SMS or email, receive shop recommendations based on vehicle location and service needs, and finally, intiate service directly from the alert itself. The goal was to transform maintenance alerts from passive notifications into actionable workflows.
Net-new four-step workflow for assigning maintenance.
Validation
Using lean RITE testing, I iterated on:
- Assignment workflows
- Notification strategies
- Shop recommendation logic
- Call-to-action clarity
Research consistently showed that users were more likely to complete maintenance when responsibility was explicitly assigned and communicated.
The Impact
The strongest outcome came from introducing accountability.
Maintenance that was assigned through the workflow moved significantly faster than maintenance that remained unassigned, often reaching completion within days rather than weeks. The project demonstrated that improving operational outcomes wasn't primarily a discovery problem, it was a coordination problem.
By reducing decision-making overhead and creating clear ownership, we increased the likelihood that maintenance work was completed and created a stronger pathway into Fleetio's shop network.
We monitored the experience through a longitudinal survey and found usability scores stabilized at 4.3 / 5.0 for ease of use, exceeding both our expectations and the industry benchmark of 4.0 / 5.0.
Looking Forward
The next step will involve exploring how algorithmic recommendations can further reduce workflow friction by automatically recommending providers, assigning maintenance based on team responsibilities, and proactively initiating service workflows before delays occur.
The next step will involve exploring how algorithmic recommendations can further reduce workflow friction by automatically recommending providers, assigning maintenance based on team responsibilities, and proactively initiating service workflows before delays occur.
CASE STUDY ONE