Global Search
Details
The Global Search redesign modernized enterprise-wide information discovery by consolidating fragmented legacy backends into a single, unified architecture. Spanning complex B2B SaaS workflows, the project eliminated navigation friction and empowered both learners and administrators to find critical reports and data with speed and precision.
Client
Cornerstone OnDemand
Scope of Ownership
Redesign, End-to-end user experience, Interaction architecture, Design system componentization
Cross-Functional Partners
Unified search interface patterns, responsive faceted filter systems, modular component cards via the "Flare" design system, and beta-ready interactive prototypes.
Year
2026
The problem
Fragmented legacy infrastructure and clunky interactions trapped critical enterprise data behind high-friction search silos, draining user productivity.
Built on an outdated, disconnected backend, the search experience forced users into a punishing multi-day Lead Time (LT) of context-switching, hunting across disparate silos, and abandoned queries. With an active Process Time (PT) of ~14 minutes per lookup (as users bounced between multiple tabs trying to locate specific reports) and a dismal 62% First-Pass Quality (%C/A) accuracy rate, enterprise accounts suffered from severe cognitive fatigue and operational drag.
The process
We combined multi-product alignment, empirical testing, and Value Stream Mapping to systematically modernize the discovery journey.
Secured multi-product and engineering buy-in to transition from fragmented backends to a single unified architecture.
Used Value Stream Mapping (VSM) to isolate hand-off lags and navigation bottlenecks in the as-is workflow.
Partnered with the "flare" design system to componentize flexible card items, achieving a 35% reduction in design-to-code handoff friction.
Conducted A/B testing and moderated usability sessions with diverse audiences (learners vs. administrators), validating our designs to reach a 92% task-success rate prior to release.
The solution
A unified search architecture powered by intuitive left-sidebar filters, role-aware AI overviews, and scalable design system components.
Merged fragmented backend silos into a single engine that slashes search friction and brings information retrieval to real-time inline resolution. By implementing high-performing left-sidebar filters and role-tailored AI overviews, we compressed active Process Time (PT) down to 45 seconds while protecting users from cognitive overload. Additionally, modular "flare" components streamlined execution for upcoming features like the Adaptive Learning Agent.
Impact & outcomes
Time-to-Insight Transformation:
Compressed total search resolution cycles from days of hunting to real-time inline results, and slashed active Process Time (PT) from ~14 minutes to 45 seconds.
Accuracy & Quality Lift (%C/A):
Boosted first-pass search success and data accuracy from 62% to 95%+.
Efficiency Gains:
Cut average user navigation and search time by 40% across core enterprise workflows.
Launch Milestone:
Successfully deployed into live customer beta with high satisfaction metrics, locking in a General Availability (GA) release date for March 27.
Selected Projects
Adaptive Learn Agent
End-to-end UX/UI architecture, Conversational UI design, System interaction models
2026
