Streamlining access to quality of service metrics for restaurant managers at Hungry Lion
6 min read
Timeline
Context
Tools
Role
Sector
Jul - Aug 2022
Internship Project
Team of 2 developers + 2 designers
Figma
Miro
UX Research
UX Design
Consulting
Data
Business
Restaurants
Restaurant managers find it time consuming and difficult to evaluate the Quality of Service. How might we streamline this process?
Context: Hungry Lion had come to us in hopes of improving their management system by providing their restaurant managers with real time information on their Quality of Service. Developers at Polymorph had started brainstorming solutions around creating an 'at a glance' overview of QoS and then allowing users to drill down into specific metrics.
Dashboard view of all branches
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Surveillance view of a branch using IoT sensors
Statistical Comparison of 2 branches
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Empathize
Define
Design
Survey
User Interviews
User Persona
Journey mapping
Wire-framing
Prototyping
We surveyed and interviewed 50 restaurant managers to narrow down the 3 key metrics that'd be most beneficial for them to evaluate the quality of service of a restaurant.
Key Metrics:
1. the number of orders
2. the time taken to complete an order
3. amount of people in various parts of the store through various IoT sensors
We identified the pain points with regards to viewing existing layouts produced by IoT sensors in the restaurant, we gathered the following insights from the managers:
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Pain points :
1. Too many colors and shapes that cannot easily be discerned by the user.
2. Relating the labels with their colors and the shapes of that color is a difficult and time consuming process.
3. Unclear what the numbers are supposed to mean
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Insights
1. High point: Being determined to improve the business profitability and finding out the main cause of concern.
2. Low point: Finding out the cause of concern being a particular branch and validating it with statistical evidence that can be acted upon.
3. Greatest gift: Easy to access overview of all branches
4. Greatest threat: Inconvenience in the form of hard to read data visualization formats when trying to understand statistical evidence
1. Navigating unfamiliar systems: Working on systems using IoT and data visualization was quite new to me. Gaining knowledge by not just reading about it but also talking to people who might be using it on the daily gave me great perspective to move forward on my journey.
2. Taking feasibility and technical constraints into account: On this project I had the opportunity to work with two developers at Polymorph as well. They helped me ground my design decisions within the boundaries of solutions that would be possible for them to work on in the given timeframe. This helped me set realistic product goals and expectations.
3. Building empathy: As I was working with a user population that I could not relate to, I had build immense empathy by carrying out intensive surveys and interviews with them. I learned a lot about their work style and their problems as a manager that helped me design accordingly.
