ARC Filters Refined
Region: Worldwide
Industry: Consulting
Overview
My task was to enhance the consistency, scalability, and usability of the reporting features. One of those was redesigning filters on a page that took up half the screen so the report was not visible.
I employed Product Thinking, Information Architecture, Interaction, Visual Design, Prototyping, and Testing methodologies to achieve our goals.
Process
To improve the filters for ARC, I carefully analyzed the current filter set to identify any inconsistencies and areas that could be improved. This involved a thorough examination of the existing filter set. Using Card Sorting exercises, I engaged users to group filters based on their mental models, extracting valuable insights to refine our proposals. This iterative process enabled me to create a streamlined and scalable filter structure that aligned closely with user expectations and optimized usability.
Afterward, I conducted user testing sessions with high-fidelity prototypes, presenting users with tasks representative of their typical interactions. Through observation and analysis, I measured user behavior and feedback, making sure that the redesigned filters met their needs effectively. The collaborative process resulted in a solution that not only solved the initial problems but also laid the groundwork for future improvements. This has made the ARC platform more clear, efficient, and user-friendly.
Results
Enhanced Focus
The redesigned filter set allows users to concentrate on tasks more effectively, with intuitive groupings that align with their mental models.
Improved Efficiency
Adding new filters is now more straightforward, Thanks to a consistent and scalable model that organizes information logically.
Enhanced Scalability
The ARC system has a refined filter model that can be used across all tabs. This provides consistency and helps in comparing different data sources.