2019
Noregon Systems - a vehicle data provider - provides software products and supporting hardware to companies who manage fleets of commercial vehicles. Their applications provide vehicle information to assist with diagnosis and repair to insure that cars and trucks in the fleet remain in good working order and that they are safe to drive. Learn more about Noregon on their website.
Our team worked with Noregon staff to modernize an aging system that required manual lookup and a lot of back-and-forth to view vehicle information. The goal of the discovery (described here) was to define an intuitive UI to allow searching of their massive database of vehicles and to provide one-click access to each vehicle's data.
As the lead experience designer, it was my responsibility to engage the client in conversations to understand their business objectives and to define a user journey that would support those objectives while giving end users access to a dashboard that displayed vehicle overviews as well as details and troubleshooting information. Product owners would use the output of our discovery to pitch product improvement ideas to their upper management team. Upon approval, their dev team implemented the updates.
Facilitated initial meeting to understand problems with existing systems and gaps in user flows
Interviewed product owners to determine ideal outcomes for the end user in a new system
Validated product owner assumptions through interviews with end users
Facilitated whiteboard sessions to prioritize opportunities and brainstorm solutions
Created clickable low-fidelity wireframes to test solutions, then iterated based on feedback
Collaborated with design team to create mid-fidelity views of key screens
Initial sketches and ideation
Arnold application wireframes alongside version 1 designs
Arnold application "zoom view" designs (wireframe version).
The TripVision Intake app is another Noregon product that manages the tracking and maintenance of fleet vehicles. Using data from the vehicle's little black box, Noregon monitors hundreds of vehicle characteristics which can indicate the health of a vehicle. This data is evaluated using AI (against acceptance criteria) in order to define the overall health of a vehicle and its individual components. These numbers are then used to predict the optimal maintenance schedule and the likelihood of parts failure.
The Intake app would be used by a client when the vehicle arrived at the garage to collect additional information–some of it qualitative–to further inform the AI engine. Below are the core screens for Intake as they would appear on a mobile device.
