1.Context & Product Scope

Sally is an autonomous food robot operating 24/7 across high-traffic environments (universities, hospitals, grocery stores), where operator efficiency directly impacts uptime, revenue, and customer trust.

2.Problem Framing

• Robot downtime emerged as the primary system constraint, with restocking identified as the highest-leverage intervention point.

• The existing restocking experience was step-heavy, cognitively demanding, and poorly instrumented, forcing operators to rely on memory rather than system guidance.

3.User & Domain Insights

• Operator workflows spanned physical hardware + digital interfaces, creating friction at handoffs.

• Key failure modes included:

  • Mental tracking of ingredients, quantities, and expiry constraints

  • Inefficient navigation between tablet UI and physical canisters

  • Lack of actionable visibility due to hardware sensing limitations

4.Design Strategy

• Shifted restocking from a memory-driven task to a system-guided workflow.

• Prioritized:

  • Step-by-step, glanceable UI

  • Reduced cognitive load and decision fatigue

  • Accessibility-first interaction models for diverse operator needs

  • Audio-visual feedback to bridge physical–digital gaps

5.System Constraints & Tradeoffs

• Designed within hardware limitations (binary canister detection only).

• Optimized for scalability and operational simplicity over visually complex but fragile interaction models.

6.Execution & Platform Thinking

• Extended DoorDash’s Prism Design System for large robotic displays, ensuring:

  • Consistency with existing operator mental models

  • Faster adoption without retraining

  • A scalable foundation for future robot workflows

7.Outcome & Signal

• Prototype testing with operators showed strong usability gains and clear reduction in perceived effort.

• The redesign positioned restocking as a repeatable, low-friction system behavior, directly supporting reduced downtime and higher service availability.

8.Key Takeaway

• The work demonstrates how systems thinking + domain depth + design execution can unlock outsized impact in human-robot operational products.