Zomato
SHIPPED 2025
How might we help restaurant teams work faster without cognitive overload
Responsibility
Lead product designer
and core UX architecture
Team
3 Designers, 2 Product Managers,
12+ Engineers
Time
Jan - April, 2025
The Problem
Zomato’s legacy OMS was outgrown by modern kitchens
Over a million orders flow through Zomato’s legacy Order Management System every day, across cloud kitchens, high-volume QSRs, and multi-outlet brands. When the system kept up, service felt
Impact
From order tracker to reliable control surface
Designed for faster order acceptance, better instruction adherence, and higher cross‑outlet adoption once rolled out
1.2 sec
Improvement in Avg. order
acceptance time
12%
Increase in instruction adherence on orders
15%
Reduction in refund-related issues tied to live orders
23%
Increase in cross-outlet adoption after rollout
Solution Overview
Key problem
The OMS treated everything as a flat stream of orders, assuming a single “kitchen user” moving them through stages. In reality, multiple user types operators on the line, kitchen staff, outlet managers, and multi‑outlet owners were all leaning on the same system with very different needs and time horizons.
👨🏽💼
Operator
Couldn’t see what needed attention next, every order looked the same, with no clear priority or urgency cues
👩🏾🍳
Kitchen staff
Missed critical details like allergies, modifications, and special instructions that were buried or surfaced too late
👨🏽💼
Outlet managers
Had no way to see what was slipping, issues were scattered across individual tickets, not aggregated into a clear picture
🧙🏽♂️
MULTI‑OUTLET OWNER
Constantly jumped between outlets with no single view of performance or risk, relying on calls and manual checks
Core insight
Across all of these user types, workflows felt fragmented, decisions were slow, and the OMS wasn’t aligned with how real kitchens actually move during service
Core workflows underperformed, especially order acceptance, visibility of critical details, and reaction time at peak load
High rejections and slow acceptance revealed missing cues, vague priorities, and an overwhelming interface
All orders appeared identical, making it impossible to spot delays or time-sensitive tickets
Fragmented workflows forced teams into offline coordination
Defining the problem
HMW help restaurant teams work faster without cognitive overload
Design goals
We took a strategic decision to position OMS as the “control tower” for restaurant operations, ensuring it scales for enterprise-grade kitchens while remaining effortless for small outlets
Flexible
Scales from single outlet to multi‑outlet chains
Design Highlights
Reposition OMS from "order tracker" to "control tower" scaling for enterprise-grade kitchens while remaining effortless for small outlets
Reflections
What I learned
Kitchens are not a single user; multiple user types rely on the same OMS with very different needs and pressures. That framing made every design decision clearer, but the hardest part wasn’t the interface—it was getting into real kitchens during peak hours, earning trust fast, and seeing where things actually break
Next steps
With the pilot validating clearer hierarchy, reduced switching, and better adherence to instructions, the next phase focuses on scaling the system
With the pilot validating reduced cognitive load, faster order decisions, and improved adherence to instructions, the next phase focuses on scaling the system across outlet types and operational complexity. The roadmap deepens role-specific views for operators, managers, and owners, and adds smarter, upstream alerts so risks surface before they impact guests or refunds. The long-term goal is an OMS that becomes the operational control layer for Zomato kitchens, keeping service predictable and resilient even under sustained peak load
