Digital Thread Engineering (DTi), an internal SaaS product for industrial operations, is a database of CAD drawings, part schematics, CIDs and other manufacturing data that connects stages of the product lifecycle such as production, operations, testing, and maintenance with all departments in GE. As lead designer on the search experience, I was tasked with identifying and designing improvements to the experience.
Our team, including a senior PM, technical PM, and engineers, identified inefficiencies in DTi search through stakeholder interviews and user research. The root issue was the lack of granular search control, forcing users into broad, slow searches with irrelevant results and frequent timeouts. Users adopted workarounds like running multiple tabs or memorizing part numbers to save time.
To address these issues, I proposed two enhancements. Data Type Search, enabling searches by specific data types for more targeted, faster results and autocomplete suggestions, adding real-time keyword and content suggestions to guide users toward relevant results and refine searches efficiently.
Before development, I conducted a usability study with 5 engineers to quantify the new design’s impact on overall user satisfaction for general and specific search tasks.
The study consisted of two search tasks, one general, one specific, and a follow up questionnaire using a likert scale to understand initial perceptions, and satisfaction. Engineers were asked to speak out loud during each search. My goal was to capture initial evidence for the design direction.
Using a 'Wizard of Oz' approach to displaying real time search suggestions and autocomplete, feedback was overwhelmingly positive:
These findings validated the designs and allowed our team to feel confident in the impact on user productivity and sentiment.
After presenting my designs and findings to our team, the PMs decided to add the improvements to their product roadmap and commit to building a pilot search experience using the proposed enhancements.