At Motive, I approached fleet management as a data interpretation problem, focusing on how complex operational data could be translated into clear, actionable insights. I worked closely with product and engineering to map out key workflows and identify where users experienced cognitive overload or delays in decision-making. From there, I designed data-driven interfaces and dashboards that prioritized clarity, enabling fleet managers to quickly assess vehicle performance, driver behavior, and operational health.

My focus was on refining information hierarchy, simplifying navigation, and creating scalable UI patterns within the existing design system. By structuring data more intentionally and reducing visual noise, the redesigned dashboards improved usability and speed of insight. As a result, we saw a ~20% reduction in time to access critical information and a noticeable improvement in task efficiency across daily fleet monitoring workflows.