Data Tables
Standardizing CRUD workflows across a system of records—replacing 32 fragmented implementations with a table system used across 80% of product surfaces
Dayforce is fundamentally a system of records
Nearly 80% of Dayforce surfaces depended on data tables to create, view, and manage records. But each of the 32 product teams implemented its own interaction patterns, behaviors, and editing models—creating a fragmented experience for users navigating across the product. Managers needed to quickly compare and update multiple employee records without drilling into each detail view. Employees needed predictable ways to review and confirm their own data. Administrators needed safe bulk actions across hundreds of records without risking errors. Instead, they encountered inconsistent interaction models that required relearning table behavior in every module.
The fragmentation ran deep. Recruiting teams expected inline editing. Payroll teams needed bulk selection and heavy mass-editing. Reporting teams relied on analytics views and inline filtering. No single pattern served everyone—so everyone built their own.
A context-driven, modular table system
Instead of forcing 32 teams to adopt a single pattern, I built a flexible template system that teams could configure for their specific use cases while maintaining platform consistency.
Rather than prescribing a single "right way," I identified reusable building blocks that teams could combine. The goal: maximum flexibility within a consistent interaction model.
