Case study

Optimizing Restaurant Operations with a Reservation Management System

This project involved designing a reservation and table management system for restaurant operators, focusing on reducing no-shows, improving floor efficiency, and streamlining the guest experience.

As a UX Designer, I worked closely with restaurant managers and hosts to understand operational challenges and design a system that adapts to the fast-paced hospitality environment.

My Rol

UX Research UI Design Interaction Design Interaction Design

The Challenge

Restaurant teams were managing reservations through fragmented tools—paper books, spreadsheets, and basic phone systems. This created:

High no-show rates with no automated follow-up
Poor table utilization during peak hours
Communication gaps between front-of-house and kitchen staff
Communication gaps between front-of-house and kitchen staff

The core tension

How might we reduce no-shows and improve table efficiency without adding complexity for the host team?

Framing the Opportunity

We identified key opportunities through research:

Automate guest confirmations to reduce no-shows
Visualize floor plans in real-time for better table management
Simplify the reservation flow for faster booking

We identified key opportunities through research:

Our guiding principle

Speed and simplicity for the host, transparency for the manager.

Approach

We focused on understanding real workflows and system behavior:

System & Workflow Mapping

We began by mapping the main functionalities of the software to better understand the core interactions. This helped us identify friction points and prioritize improvements.

We combined field research with rapid prototyping:

Restaurant staff (hosts, managers)
Observed how they manage reservations and tables
Identified pain points during peak hours

We combined field research with rapid prototyping:

Restaurant staff (hosts, managers)
Observed how they manage reservations and tables

We combined field research with rapid prototyping:

Observed how they manage reservations and tables
Identified pain points during peak hours

Users

We identified two primary user profiles:

🧑‍🍳

Restaurant Hosts

Manage walk-ins and reservations simultaneously
Need fast, one-glance visibility of table status
Often work under time pressure

Restaurant Hosts

Manage walk-ins and reservations simultaneously
Need fast, one-glance visibility of table status
Often work under time pressure

👨‍💼

Restaurant Managers

Track occupancy and revenue patterns
Need reporting and analytics
Make decisions about staffing and capacity

Restaurant Hosts

Manage walk-ins and reservations simultaneously
Need fast, one-glance visibility of table status
Often work under time pressure

👨‍💼

Restaurant Managers

Track occupancy and revenue patterns
Need reporting and analytics

Restaurant Hosts

Manage walk-ins and reservations simultaneously
Need fast, one-glance visibility of table status
Often work under time pressure

Key Problems Identified

No-show management → No automated reminders or follow-ups
Floor visibility → No real-time view of table status
Booking friction → Too many steps to create a reservation
Data gaps → No insights on patterns or trends
Data gaps → No insights on patterns or trends

The Challenge

High no-show rates with no automated follow-up
Poor table utilization during peak hours
Communication gaps between front-of-house and kitchen staff
Communication gaps between front-of-house and kitchen staff
Communication gaps between front-of-house and kitchen staff

The Solution

We designed a unified reservation system with real-time floor management and automated guest communications.

Core Features

Smart Floor Plan

Instant visibility of availability
Reduces hosting errors

Confirmation, reminder, and waitlist notifications via SMS and email.

Automated Guest Communication

Reduces no-shows by up to 30%
Improves guest experience

Why it matters:

Quick Reservation Flow

Fewer steps to book
Works for phone, walk-in, and online bookings

Why it matters:

Analytics Dashboard

Data-driven staffing decisions
Identifies patterns for optimization
Identifies patterns for optimization

👉 Faster decision-making and reduced errors

Automated Guest Communication

Reduces no-shows by up to 30%
Improves guest experience

Why it matters:

Quick Reservation Flow

Fewer steps to book
Works for phone, walk-in, and online bookings

Why it matters:

Analytics Dashboard

Data-driven staffing decisions
Identifies patterns for optimization

Why it matters:

Outcomes

Established a clear, unified vision for AI-powered digital advice

Established a clear, unified vision for AI-powered digital advice

Aligned stakeholders around a cohesive experience strategy

Aligned stakeholders around a cohesive experience strategy

Defined a realistic MVP and phased roadmap

Aligned stakeholders around a cohesive experience strategy

Produced high-fidelity prototypes to communicate complex ideas

Aligned stakeholders around a cohesive experience strategy

Created reusable patterns for AI-assisted decision-making

Aligned stakeholders around a cohesive experience strategy

Key Takeaways

Guidance is most effective when it respects user autonomy

What I’d Improve Next

Personalize guidance based on behavior over time.
Validate with real users in live trading environments.
Further reduce cognitive load in high-stress moments.

Closing Thought

Designing for financial decision-making isn’t just about usability—it’s about responsibility.

The goal isn’t to make decisions for users, but to help them make better ones.