McDonald’s Restaurant Profile Management
Modernizing a large-scale configuration system to improve operational efficiency at McDonald’s
Design impact
My role
I led a designer intern to successfully complete this project, focusing on defining use cases, updating IA, and designing UI&UX for the restaurant profile module.
Highlights
I led a designer intern to successfully complete this project, focusing on defining use cases, updating IA, and designing UI&UX for the restaurant profile module.
background
What is RFM?
Restaurant File Management (RFM) is a management tool used by restaurant owners, corporate executives, and consultants alike to ensure a high level of standardization across stores for decisions such as: menu items, ingredients, store hours, and item pricing.
As a 10-year-old system, it is characterized by confusing internal jargon, segmented user journeys, and outdated visual design, which made common configuration tasks harder to learn and slower to complete.
Problem
Growing design debt
To unearth the biggest pain points in the tool’s usability, we conducted over 15+ interview sessions with store owners and internal consultants to understand the management tasks and uncover the most disruptive pain points while using the platform.
Admin
Internal Consultants
Works at the corporate to set up and maintain how store data is structured across restaurants. Defines and manages configurations such as menu items, pricing, and operational rules.
Owner/Operator
Store Owners
Uses the system to update store settings based on what’s happening in day-to-day operations. Adjusts store hours, tax settings, receipts, and promotions as needed. Makes changes in response to events like holidays, staffing, or local business conditions.
Findings
Insights
Admin
Fragmentation
Information needed for a single operational task is split across multiple systems and tabs, even simple updates require cross-system hunting before any action can happen.
Admin
Inefficiency
Multi-store editing is a primary workflow, but the system treats it like a series of single-store tasks, creating repetitive work and poor scalability.
Owner/Operator
Complexity
Frequent tasks, edge cases, and advanced settings are surfaced with similar weight, making routine actions harder to identify and complete.
Owner/Operator
High Learning Curve
Onboarding friction is driven by low discoverability. Users must rely on prior knowledge or training because the system does not clearly guide them through tasks.
How might we ease the burden of configuring and adjusting technology rulesets in restaurants?
My role
Brainstorming
Updating confusing information architecture
One of the biggest challenges was to redesign the system without breaking existing workflows. I led two rounds of scenario mapping activity as part of 15+ user interviews with both operators/owners and admins to answer these key questions, which helped me rethink and restructure the IA.
What are the scenarios that drive admins and restaurant owners/operators to the management tool?
What tasks are owners/operators performing the most?
What are the most complex and time consuming tasks?
Brainstorming
New information architecture
I identified several issues with the current information architecture that directly impact the user experience:
Use of internal jargon
High-frequency tasks are hard to find
Related content is fragmented across multiple tabs
To address these challenges, I restructured and reclassified the information architecture.
Iterations
Design challenges
Once I fleshed out enough content to turn IA into wireframes, I was ready to validate them with users. I led the first two rounds of validation, I received positive reactions about larger scale improvements, like the updated IA and bulk updates.
Challenge 1: How might we make bulk edits more efficient and less repetitive?
Managing store hours across 7 days and 3 service channels can be repetitive. I explored batch editing and copy/paste solutions. Compared with batch editing, copy/paste better supported quick repeat actions while giving users more granular control.
Challenge 2: How might we reduce visual density without removing depth?
Operational details are dense and complex. I first grouped related information, then explored patterns like dropdowns and collapsible cards. Collaborating with PMs, we decided collapsible cards to reduce visual density while keeping depth and clarity.
Final Solution
Select restaurants
To reduce repetitive work, multi-select enables users to update multiple restaurants in a single action without editing them individually.
Final Solution
Update restaurant information
After selecting restaurants, users can quickly update hours, address, and operational details across all selections, making the process simple and more efficient.
Outcome
Takeaways
During my time on this project, I learned to separate visual design from user-centered design. You can come up with a clean-cut design solution which looks visually appealing in Figma, but just because it’s striking doesn’t mean it provides the best experience possible for users.
More than once I would come up with a flashy UI design that wasn’t realistic to implement. In these scenarios, it was important to take a step back, think about what the user needs, and discard your own biases about how something should look. The result is a system in need of return to its core use cases while respecting flexibility its users can still enjoy.