Reimaging Fleet Performance
My role: UX & Visual Design
FinFleet is a proof-of-concept application that re-imagines how fleet managers monitor the health of heavy equipment machines. The solution emphasizes metric visualizations, alert notifications and intuitive machine analysis at a glance.
On-site Finning Visit
Finning is the largest Caterpillar dealer in the world. They sell, rent and service heavy equipment machinery to customers in many industries such as mining, construction and power systems.
A Data-driven opportunity
The heavy equipment industry is currently experiencing an unprecedented surge in data-driven technologies that helps operators monitor and improve the efficiency of their machines.
Although competent in aggregating information, the current platforms do not relay the information in the most intuitive and effective format. This was an opportunity to create a solution that aims to improve a fleet manager's experience of machine monitoring and telematic data analysis.
Understanding the user
After conducting extensive discovery sessions and in-depth interviews with fleet managers and other stakeholders, we were able to extract insightful pain-points that helped in framing the problem we were solving for.
High Cognitive Load
Information is presented in extensive XLS format, often without any indication of heirachy and visual signifiers.
Lack of Human Factors:
System-based reporting outputted complicated error codes that were not easily understandable.
Not viewable on mobile:
Even without any native applications, Web-based tools were not responsive or mobile-ready.
Fleet managers need an intuitive and customizable way to monitor machine health on the go without needing to sift through large amounts of data.
With the problem clearly outlined, we identified a list of design requirements that the solution must help address:
Find necessary information at a glance.
Get notified of critical alerts on the go.
Easily visualize faults and other health/performance indicators.
Share diagnostic information with other fleet managers.
After gauging other telematic solutions, we decided to widen our scope of inspiration to more than just heavy industry. We drew inspiration from NHL, earthquake statistics, baseball analytics and even Pokedex - all of which have inspired us to think differently about visualization. This was a refreshing contrast to the data-heavy dashboards that our target users are normally accustomed to.
The insights from research led us to explore concepts that made functional use of progressive disclosure. We pursued different ideas by rapid prototyping and unrestricted ideation sessions. Allowing the space for unconfined exploration resulted in useful ideas that were worthy of further validation.
After the initial ideation phase, we tested our prototypes and extracted important insights that informed further revisions. We continued to design, test and iterate according to user feedback on information heirachy, color choice, layout and readability .
Simplifying UI Flow
As an example of user testing feedback, the overview page on the right underwent several rounds of changes based on the feedback gathered from usability testing. Several competing design decisions were put to the test. Feedback concerning readability, color signifiers and layout were used to further refine the design.
High Torque Oil Temp 3D visualization.
Making Faults more intuitive.
One major feature that came from user-testing was that users wanted a visual representation of the Fault codes. Transforming Fault code numbers and codenames into understandable information coupled with suppplementary visual representation.
Mapping out our Flows
The proof of concept aimed to demonstrate a fleet manager’s journey from choosing a fleet, navigating to general machine overview and finally to narrowing down on an individual machine metric. Of all the metrics that combine to create machine performance, we explored diagnostic faults for our demonstration purposes.
Overview and details
With a few clicks, fleet managers are able to toggle between general overview and individual machine metrics. FinFleet ensures a seamless transition from different modes of analysis.
Users can group machines into customizable fleet variations tailored specifically to their needs. Machines can exist in multiple categories, and as a result can be analyzed whichever way is required.
Easily monitor diagnostic faults
Fleet managers can clearly visualize machine-specific diagnostic faults. Our three level warning system makes it easy to identify urgent errors that demand immediate attention.
Retrospectives save lives
Conducting team retrospectives as often as possible were crucial to ensuring internal cohesion and project alignemnt. Our use of retros proved to be an excellent opportunity to inspect, adapt and iterate on our team dynamics.
Test early, test often
At low-fidelity stages, testing early and getting verbal/behavioral feedback is crucial for effective iterations. Extracting these types of insights as early as possible helps save a lot of time as the workflow progresses.
Trusted > Beta tools
Although it is hard to not be enthusiastic about new design tools. In teams, its wiser to use stable ones that have bigger active communities and tested integrations.
Project Manager / Developer
U/X Design / Scrum Master
UI Designer / Product Owner