Selection Framework

UX / Design Systems / Cross-Product

As the lead facilitator, I initiated and guided an idea-generation workshop to align UX and Platform teams on needs, use cases, and availability related to the prompt component ecosystem. The goal was to uncover areas where we could consolidate functionality, deprecate redundant code, and increase adoption of Canvas-maintained tokens—ultimately streamlining our design and development approach.

Prompted by insights from the Suggestive ML Prompt initiative, we identified significant variation in how the prompt component was implemented across Workday's product suite. Multiple versions existed in separate repositories, with overlapping yet inconsistent functionality. Many teams defaulted to the most complex, “multi-select” version—resulting in overuse, confusion, and bloated experiences. I audited these component options, clarified their differences, and worked cross-functionally to develop a plan for rationalization. This included surfacing which variants could be consolidated, absorbed into the Canvas Design System, or fully deprecated. The outcome: a more intuitive and scalable framework for App Developers to select the right component for their use case, reducing design debt and improving product clarity.