dashboard for fleet management service

role

UX/UI design

year

2025

tools

Figma

Goals & Context

Summary: A fast-paced design sprint aimed to create a demo of a fleet SaaS dashboard, within 5 days, covering research, usability testing, flows, interface, iterations, and case study . This project was initiated to explore the design challenges within fleet management services, in the mobility industry.
Given my interest in mastering complex data visualization and user-centric solutions, i aimed to quickly familiarize myself with the industry's needs.

Hypotheses

At an operational level, in e.g. public transportation, fleet managers a required to efficiently manage bus fleets, ensure compliance and enhance passengers safety. Dealing with various issues (safety, compliance, efficiency) might lead them to information overload.

Fleet managers might be overloaded with information of different sorts and therefore need an interface that provide information "at a glance", to help to operate with ease.

Research & Insights

Through generative research, I gained early insights that informed a persona, clarifying both the fleet manager’s responsibilities and the decision-making challenges they face daily, as outlined below.

Fleet Manager Role:
Fleet managers typically hold mid-level operational positions, focusing on the hands-on management of daily fleet activities. They prioritize efficiency, safety, and cost control rather than strategic decision-making. Key responsibilities include:

  • Monitoring fleet performance (availability, fuel efficiency, maintenance needs)
  • Ensuring vehicle safety and compliance
  • Coordinating with drivers and maintenance teams
  • Responding to operational alerts (vehicle breakdowns, driver issues)
  • Reporting to top management

Decision-Making Space:
The “decision-making space” refers to the cognitive environment in which fleet managers interpret information and make operational choices. Fleet managers face multiple challenges daily—safety, compliance, and efficiency—which can lead to information overload. They must rapidly process inputs such as:

  • Inputs: vehicle telemetry, driver reports, passenger feedback, maintenance alerts.
  • Processing: filtering, prioritizing, and interpreting signals (what's noise vs. critical).
  • Outputs: actions (reroute, schedule maintenance, assign a new driver, alert stakeholders).


AI-assisted persona to guide user-centered design and empathy

Problem Framing

A fleet manager may feel anxious about missing critical information that could impact user safety—a “blind spot” where unknown issues might go unnoticed or have unforeseen consequences. The core challenge is providing access to the most critical data within a high-volume information environment, helping managers filter signals, distinguish noise from urgent alerts, and anticipate issues before they escalate.

Ideation & Prototyping

I first mapped the user flow to outline key tasks and visualize how screens and information would be structured, helping to guide the information architecture. Based on this, I created wireframes, mid-fidelity mockups, and a clickable prototype to test with users as early as possible.



user flow for helping to guide the information architecture
early wireframes, and mid quality mockups for clickable prototype

Usability Testing & Insights

I conducted remote usability tests with clickable prototypes to evaluate user understanding of information, navigation flow and contact features. Key insights included:

  • Tested comprehension of dashboard metrics (costs, crash rates)
  • Assessed navigation preferences (cards vs side menu)
  • Evaluated interaction with fleet map and live danger alerts
  • Identified missing features: multiple contact methods and clearer alert visuals
summary table of user feedback & pain points


Iteration & Validation

A second usability test confirmed improved metric comprehension and map interaction but revealed continued navigation ambiguities and contact access issues, guiding further refinements.

Outcome

Delivered three key desktop views (dashboard, real-time map, and maintenance). These are presented as mid-fidelity mockups to communicate structure, layout and visual intent — optimized for clarity over pixel-perfection due to the tight 5-day sprint format.

above: 1st mid-quality mockups; below: the 2nd iteration
2nd mid-quality mockups's iterations for live map and maintenance views

Summary & Next Steps

Through usability testing and rapid iterations, I refined the dashboard to improve clarity, navigation, and in-context communication—enabling fleet managers to quickly contact the assigned maintenance team when issues arise. This iterative process revealed opportunities to streamline contact and alert workflows, establish a clearer information hierarchy to prevent overload, and implement actionable improvements for critical UI components.

Moving forward, the focus will be on iteratively refining existing screens, adding new high-priority features, and continuously testing with users to ensure the dashboard remains intuitive, efficient, and aligned with fleet managers’ needs.