Company
iCHEF
Time
3 months (From research to launch)
Team
2 Designers, 1 PM, 9 Engineers (FE, BE, iOS, QE)
Role
Sr. Product Designer (Led end-to-end UX, user research, product definition, and cross-functional execution)
I led the end-to-end UX for scheduled orders, aligning 4 roles and rebuilding time logic to ensure clarity and accuracy. This enabled restaurants to accept online scheduled-orders and reduce staff burden—resulting in 53% adoption within the first month.
My Impacts
Enabled 12,000+ Restaurants
53% Adoption in One Month
71% Boost in Daily Activation
2+ Weeks Saved in R&D
The Problem
No Scheduled Pickup: Top User Need, High Risk of Order Loss
iCHEF served 12,000+ restaurants across Asia, but its online ordering system only supported ASAP orders. We prioritized 100+ monthly merchant requests for scheduled pickup, as ASAP-only orders caused manual workarounds, errors, and incorrect performance metrics.
Business Goal
Increased Order Volume to Drive GMV and Subscription Upgrades
We prioritized scheduled pickup—the most requested core feature—based on a strategic hypothesis: increasing order volume would drive more merchants to upgrade their POS subscription plans and GMV. The feature targeted a critical gap in the ordering system and aligned with both user demand and infrastructure readiness, unlocking measurable growth in activations and GMV within the first month.
Main Challenge
Handled Cross-Role Flows and Time Logic Integration at Scale
We needed to support 4 distinct user types (operator, customer, staff, kitchen) with different tools, workflows, and habits. To ensure seamless adoption, we designed role-specific experiences and aligned them across the full order journey.
We also introduced a new time logic system to support scheduled pickups, requiring careful validation across timestamps, kitchen slips, and meal prep timing—ensuring new logic didn’t break business-critical operations.
Design Process
Design Plan
Shaped Problem Scope and Aligned Team Through Strategic Mapping
After receiving the project brief, I created a Design Plan and Service Plan based on the PRD, mapping out key considerations across business goals, user flows, and technical constraints. This helped define a clear problem scope, enabled team alignment early, and reduced miscommunication.
In parallel, I developed a strategic research plan focused on system limitations, restaurant workflows, and online ordering operations. This provided the domain knowledge and context we needed to make informed design decisions that addressed the needs of both staff and customers.
Initial Research Stage
Framed the Right Problem Through System-Level Discovery
After receiving the PRD, I created a design plan that outlined key assumptions, questions, and next steps. Building on that, we conducted research from three angles—restaurant staff, customers, and system behavior—to understand user mental models, motivations, and workflows. These insights shaped our design strategy and helped prioritize critical elements like timing logic and role-specific interactions.
Understanding Restaurant
Mixed-Methods Research to Uncover Real Operational Needs
Research Approaches
To ensure the feature addressed real store needs, I led the junior product designer to conduct mixed-method research to capture operational behaviors, motivations, and pain points from the ground up.
Key Insights
We uncovered key behavioral patterns and decision-making logic that shaped our product principles. Through mixed-method research across 84 feedbacks, 8 interviews, and behavioral data, we identified the top motivations (revenue, workload, food quality), operational blind spots (e.g., order editing, late-night behavior), and usage variations by store type. These findings directly informed persona creation, flexible feature logic, and setup guidance strategies.
Understanding Customer
Grounding UX Decisions in Competitive Benchmarking to Drive Familiarity and Reduce Friction
Why Benchmarking?
To reduce design misalignment and accelerate decision-making, I conducted targeted benchmarking across industry leaders and similar platforms. This surfaced best-in-class UX patterns for pickup flow, time display, and error prevention—allowing me to anchor our design in proven standards and minimize user confusion.
Selection Criteria
Top 2 delivery and pickup platforms in Taiwan.
Similar to iCHEF, but focused on online ordering.
Adopted proven UX patterns to reduce user friction and ensure clarity around order timing. Competitive benchmarking revealed best-in-class practices for time formatting, store availability, and order flow—enabling a familiar, intuitive experience that minimizes confusion and operational errors.
Understanding System
Auditing System Dependencies to Prevent Conflicts and Scale Pre-Order Logic
To ensure the new feature wouldn’t introduce edge case failures or logic conflicts, I conducted a system-level audit focused on time-related settings across ordering workflows.
By mapping impacted flows—such as auto-cancellation, order cutoffs, and scheduling logic—I surfaced a key conflict between existing ASAP logic and the proposed pre-order behavior. This alignment effort minimized downstream engineering rework and clarified cross-feature dependencies early.
Mapped system dependencies to eliminate logic conflicts and support scalable scheduling.
Strategy Stage
Mapped Business Goals to Real-World Constraints Stage
I defined the product strategy by translating goals into actionable design plans, rooted in real-world constraints across restaurants, online users, and backend systems.
This stage enabled early alignment with engineers and PMs, shaping a shared understanding of feasibility, scope, and user-centered priorities.
UX Goal
Focus on Outcomes That Drive Business Value
To align cross-functional teams, I translated high-level business goals into actionable strategies—prioritizing features with the highest impact on GMV while reducing design and dev overhead.
Transformed top-down goals into product decisions that improved outcomes without bloating scope.
MVP Specs
Evaluate Feasibility Early to Prevent Scope Creep
I created a prioritization framework to help the team evaluate user needs and technical feasibility early on—ensuring we solved the right problems without overcommitting resources.
We then broke specs into modular tasks. I partnered with our junior designer to assess task complexity, align on handoff scope, and assign entry-level flows that supported both his development and delivery goals.
Transformed top-down goals into product decisions that improved outcomes without bloating scope.
Early Team Sync Up
Use Flow Mapping to Uncover Risks & Accelerate Delivery
I created detailed user flows to discover the use cases, simulate edge cases, expose system risks, and align with engineering early. This de-risked implementation and enabled quicker cross-functional decisions.
Mapped use cases to reduce surprises and align MVP feasibility across teams.
Design Solution
Designed One Unified Experience Across Online and In-Store Operations
This solution bridged online behavior with in-store operations, redesigning not just the interface but also the timing logic to reduce friction and errors. One unified experience served three roles—owners, staff, and customers—solving for time, clarity, and trust across the order journey.
I led the design of the core flows, including role-based entry points and pickup-time logic. What follows highlights the decisions I drove and the systems I built to support a seamless cross-channel experience.
Design Solution - Cloud 01
71% Growth in Daily Activation by Realigning Navigation with User Mental Models
The Situation
In the initial release, the feature was followed by IA, buried under “Order Settings,” creating a major discoverability gap. Early pilot testing showed that 3 out of 4 users navigated to the wrong location—causing confusion, blocking adoption, and risking long-term scalability.
Strategic Approach
Pilot test revealed a mismatch between IA logic and user mental models.I proposed a low-cost, high-impact fix—relocating the feature to the main menu with a clearer label. This reduced confusion and drove a 71% spike in daily activations without engineering overhead.
Strategic restructure based on user flow, not just surface-level UI.
My Learning
I initially over-indexed on IA structure without validating user expectations, which led to late-stage confusion and engineering rework. This experience reinforced a core insight: navigation clarity isn’t just UX polish—it’s critical to business growth. Going forward, I prioritize early validation through usability testing and partner proactively with PM and Engineering to surface friction points before committing to structure.
Design Solution - Cloud 02
Faster Pickup Time Setup with Import Logic Based on User Insights
The Situation
The original UI for pickup time setup was outdated and overly manual—users had to create each time slot from scratch, leading to confusion and delays. A full redesign would have required significant engineering effort with limited impact, so I shifted focus to a more targeted question: How might we help restaurant owners complete setup efficiently using the existing legacy system?
Strategic Approach
To reduce friction without deep engineering effort, I identified a shared pattern in store behavior: most stores already aligned pickup hours with business hours. Based on this, I designed a one-click “Import Business Hours” solution and partnered with Education and Engineering to ensure smooth rollout across diverse stores.
My Learning
In this setup, I embedded hidden logic that restricted pickup time slots to store business hours, aiming to mirror real-world operations. However, this added design and engineering complexity, especially around error handling. Looking back, I realized strict, hidden constraints can backfire. In the future, I’d evaluate such rules more carefully against team cost.
Design Solution - Cloud 03
Avoid Missed Orders by Smart Scheduling
The Situation
Some stores only accept pre-orders one day in advance and close on weekends, causing gaps when customers place orders on Saturdays—no valid pickup dates are returned. If the system strictly followed calendar days, stores risked missing weekend orders and losing revenue.
Strategic Approach
To mitigate order loss without adding user friction, I introduced intelligent fallback logic that automatically suggests the next valid pickup day. This decision was driven by operational reality across stores and validated through real-world sales scenarios to ensure both usability and revenue protection.
My Learning
This project reinforced the value of designing logic based on operational truth—not just system rules. By mapping store behavior early and aligning with sales reps, I avoided misalignment later in development. It taught me the value of building system resilience around business edge cases without overcomplicating the UI.
Design Solution - POS 01
A Compact Interface for Quick Scanning and Fast Decisions
The Situation
Orders require quick, confident decisions—often within seconds—on pickup time, printing, or acceptance. However, the existing UI lacked visual hierarchy and flexibility to support real-time store operations across diverse workflows.
Strategic Approach
To support fast scanning under pressure, I prioritized reducing cognitive load without breaking habits. Drawing from usage data and store interviews, I refined the existing layout to highlight decision-critical info like time and price, while preserving button positions. This enabled smoother adoption across store types and improved operational clarity with minimal training overhead.
My Learning
Early in the process, I focused too heavily on redesigning and adding new features—without fully considering store-level behavior. Real-world testing revealed that minimizing layout changes while reinforcing familiar flows significantly improved confidence and efficiency. This experience reframed my design priorities: clarity and context over complexity. It also helped align cross-functional decisions around what truly mattered to operations, not just product aesthetics.
Design Solution - POS 02
The “Accept (Print Later)” Button: Flexible for Diverse Store Operations
The Situation
User research showed a gap between system behavior and store workflows. Some merchants skipped the “Accept (Print Later)” button because it didn’t align with their print-review habits. This insight prompted a logic redesign to preserve operational efficiency while increasing flexibility.
Strategic Approach
To address friction without changing store behavior, I redesigned the logic and labeling to better reflect real-world usage. By keeping the default logic consistent but introducing an optional “Print Later” path, I supported multiple workflows without adding risk or engineering overhead.
My Learning
This case showed how a small UX detail—like a label—can impact behavior. Instead of forcing adoption through design, I aligned system defaults with existing workflows. This reinforced a key principle: flexibility and operational alignment often drive adoption more than feature additions.
Design Solution - Online Store 01
Time Format and Mechanism Redesign to Enhance User Understanding
The Situation
Inconsistent time formats and pickup logic across the UI caused user confusion and internal misalignment. Critically, the ASAP pickup time was calculated based on when the store accepted the order—leading to cases where scheduled orders appeared earlier than ASAP orders if the store accepted ASAP orders slowly. This confused and frustrated customers.
Strategic Approach
To fix the trust gap, I redesigned the logic to reflect real-time order behavior, shifting the calculation to the user’s order time. I also adopted text-based formats and created storyboards to align stakeholders and ensure teams clearly understood how pickup logic worked across edge cases—minimizing ambiguity without disrupting store flow.
My Learning
Redesigning a foundational system logic—like timing mechanisms—can introduce friction if not backed by evidence. I learned that leading this kind of change requires more than just UX rationale; it takes strategic storytelling, supporting data, and operational context to align cross-functional teams and mitigate risk to align cross-functional teams and ship confidently with user trust intact.
Pilot Test Stage
Pilot Test is the key to the new feature, it aims to identify and minimize any major issues that could disrupt restaurant operations.
Pilot Test
Identify key issues before Launch with 4 Pioneering Restaurants
We collaborated with 4 restaurants that had requested the feature—each with distinct operational models—to help uncover real-world issues. Their feedback, including concerns about navigation and wording, guided us in refining the experience through further iteration.
Cross-Function Collaboration
Streamlined Cross-Functional Alignment to Speed Up Delivery
Illustrated timeline to align order touch-points across PM, engineering, and QA teams.
❶ Concise Design Documentation
Simplified docs to improve team alignment and speed up development.
❷ Unified Time Format
Reduced inconsistency by standardizing time formats across 5 teams.
❸ Streamlined UX Writing Process
Identified translation gaps, implemented workflows with FE & QA, saving 1 week.
Leadership & Mentorship
