Leading Hamburger Chain Using Computer Vision to Improve Operations

Background

Client

Hamburger Chain

Project

Improve Operations and Speed of Service

Ascent South Lake Union

Amid increased demand and labor shortages, a large hamburger chain focuses on the use of AI and computer vision to improve operational efficiencies and customer service. By incorporating the use of visual intelligence in their test lab, this leading organization measures speed of service, food preparation and employee efficiencies to adjust for new product and service rollouts.

  • Structure: Quick Service Restaurants Hamburger Chain

  • Locations: Innovation lab used for rollouts to thousands of restaurants

  • End goal: Improve operational efficiencies and customer service to ensure efficient growth

  • Solution: Touchless, computer vision system for measuring queue times and speed-of-service, customer satisfaction, and employee efficiency using innovation lab simulation for rollout across thousands of restaurants

  • Data insights: How new operational processes impact the following key metrics:

  1. Speed of service

  2. Customer satisfaction

  3. Labor efficiency and movement

  4. Production times of product

Introduction:


With digital transformation in full swing and mobile orders doubling during the pandemic, this leading hamburger chain was experiencing significant increased demand for their restaurant offerings. As with most restaurants, they were facing the challenge of labor shortages and needed a way to streamline food production and improve the operational efficiency of their restaurants.


Already exploring artificial intelligence by way of robots in the kitchen as well as other automation and technology solutions, they looked to Nomad Go’s computer vision solution for detailed data and insights about their physical stores. They needed a scalable and easy-to-deploy solution that could be used in their innovation lab for collecting automated, accurate and real-time data from their test simulations. Once data was collected, the group needed to compare results across different tests and enable rapid ideation without deploying significant human resources. In addition, they needed to scale the innovation process beyond the lab, capturing a 360-degree from stores in the field so they could learn about hidden process efficiencies and areas for improvement.

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The Challenge

Before Nomad Go

Challenges/Goals:

Growing demand and ongoing pressures to operate within thin margins, this leading QSR needed to find an easy and affordable way to track performance at-scale and find new, more efficient ways to prepare food and serve their customers.


Specially they were looking to:

  • Shorten queue times

  • Streamline food preparation / employee processes / employee efficiency

  • Track store performance at scale without significant resources

  • Improve customer satisfaction and ultimately retention to protect revenues

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The Solution

After Nomad Go

Solution:

An automated, computer vision-based, visual intelligence system for collecting key data points was utilized to measure, analyze and improve for key customer service, employee and product preparation processes.


  • Improving Customer Experience – measure wait times and speed of service:

  1. Time in line waiting to place order

  2. Time from place order to pay for order

  3. Time from pay for order to pick up order at counter

  4. Total speed-of-service (combination of three from above)

  • Enhancing Employee Efficiencies – measure employee efficiency:

  1. Time for employees to prepare the menu item

  2. Time for employees to ‘reset’ after completing the order

  3. Employee utilization and movement throughout a shift

Accurate and reliable data was collected in real-time including a 360-degree view of food preparation and service times so that they could understand inefficiencies and areas for improvement.


The highly flexible Nomad Go system was deployed without any major retrofit to the lab environment and accommodated the need to capture data across shifting layouts, formats, and store designs. Beyond the Nomad Go smart devices that go into the space, no other IT infrastructure was needed to get the system up and running.

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An automated, computer vision-based, visual intelligence system for collecting key data points was utilized to measure, analyze and improve for key customer service, employee and product preparation processes.

Results

    Results
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With the help of visual intelligence, this leading QSR hamburger chain was able to accelerate the pace of innovation, reduce labor costs, and improve throughput of the new product and service processes being tested in the innovation lab.

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Conclusion

Nomad Go is the only end-to-end computer vision solution that provides real-time data so companies can understand and respond instantaneously to how people are using physical spaces.


Traditional systems are costly and time-intensive to deploy. The Nomad Go solution deploys quickly and cost-effectively, allowing companies to get real-time insights about physical spaces out of the box instantly. Learn more https://www.nomad-go.com/

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We are excited about the opportunity Nomad Go’s technology offers our properties, our clients, and our tenants. With over 200 owned assets and over 2,000 properties under management globally, we are looking forward to expanding the use of Nomad Go and seeing improved business and environmental impact across our portfolio.

 Adrian De Smul

Senior Director of Customer Experience
& Innovation at Greystar

Image by Stephen Dawson

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