Enhancing electric fleet management
Platform for monitoring and planning fleet delivering service
Main objective
Movia is an electro-mobility platform created to improve the efficiency of electric vehicles fleets. It manages and monitors fleets delivering information, to indicate users when to charge the vehicles reducing energy costs, and maximising the useful life of batteries.
Design process
We divided the design into different stages. Starting with understanding the existing solution, the different user personas and their main pain point and behaviors while using the platform.
In the first stage, we focused on understanding the existing solution and different user personas. We generated the current site map and conducted a series of interview and usability testing sessions. We identified user pain points, behaviors, and key user journey maps. In the design stage, we analyzed the data, and recognize essential tasks and features to be added and enhanced to meet the user needs. The study concluded with another round of usability testing on the new solution.
Understanding the problem
In the first stage, we focused on understanding the existing solution and different user personas. We generated the site map of the platform and conducted a series of interviews and usability test sessions. We identified user pain points, behaviors, and fundamental user journeys. In the design stage, we analyzed the data, and recognize essential tasks and features to be added and enhanced to meet the user needs. The study concluded by iterating on the design following the major finding on another round of usability test session using the new solution.
Movia platform was based on the existing Antufleet platform the client had already developed. I was asked to improve the existent platform, generate new views and add new functionalities according to the users needs and essential workflows.
The first stage considered the understanding of the already existing platform in order to improve it. We developed three interview sessions of user testing in wish we found out the main problems of the existing solution, that mainly consisted in structure misunderstood and missing features, as the incorporation of data visualization of the fleet performance, settings for the fleet organization and administrative tasks.
The first result from the usability test consisted in an affinity map with the main features to develop, sorted by topic.
The second stage consisted in the analysis of all the information collected, both from the main problems of the users with the existing platform and the new features to be developed according to the main needs.
We also developed two user personas that considered the administrator, project manager and head of innovation of the electric vehicles fleet. Finally we identified the main opportunities from the user journey map to improve the experience according the emotional result caused by the already existing solution.
The design stage was the creation of the design system, the restructuring of the platform and designing new modules and views for the added features.
The solution developed consisted in 4 main sections:
Home: We redefined the main objective of this section by introducing a real-time map displaying all fleet vehicles and charging stations, along with detailed views of drivers and fleet status.
Statistics: This section provides the status of each vehicle, key performance indicators (KPIs), battery levels, and a panel for alert notifications and settings.
Optimization: This section focuses on fleet planning and battery usage to enhance the efficiency of vehicle journeys.
Administration: This was the only section that was not modified, as our research did not identify any significant elements needing improvement or major user pain points.
The final step involved testing the renewed platform, and newly integrated sections, with particular focus on the statistics and optimization modules. This involved user testing with two fleet managers, a product manager, and an innovation manager from sustainable transportation companies, to assess how the new solution enhances efficiency and aligns with user needs. We developed an empathy map to capture fundamental key takeaways. These results are essential for next stages and delivering recommended steps for continuing design iteration.
