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Helping QSRs see operational excellence with computer vision

What's computer vision and why does a QSR operator care? Read on because it could save you cash and boost your customer and employee experience.

Photo: iStock

October 29, 2019

By Jesse Mouallek/Deepomatic North America Head of Operations
 
Providing services that are timely, accurate and consumer-focused is paramount to the success of quick-serve restaurants, particularly when reliability and quality can make or break a franchise. In an industry with low margins for error and no shortage of competition, restaurants can greatly benefit from an Artificial Intelligence (AI) upgrade. 

One subset of AI that could benefit QSRs greatly is computer vision — image recognition technology that allows computers to see and identify objects the same way humans do. We've seen AI-enabled image recognition and computer vision applications begin to augment today's workers elsewhere in business, acroos industries such as telecommunications and insurance. 

But, QSRs make up one sector that is ripe for implementation. Computer vision and image recognition can be instrumental in improving key quick-service business operations, including everything from employee training and food preparation, to customer satisfaction. This is especially true as it relates to the sector's growing delivery needs.  

Making a delivery difference 

Today, there are increasingly fewer QSRs that don't deliver, especially in urban areas. And just as the number of delivery options has grown, its ease of use for customers has been turbocharged by the advent of both in-house and third-party delivery apps.

While beneficial in most aspects, third-party involvement and communication issues with apps can add to the issues already inherent in delivery — namely, late or wrong, late or incomplete orders. These are the types of issues that computer vision and image recognition can go a long way toward eliminating. This type of tech is key in eliminating the factors which cause mistakes, while simultaneously helping brands provide a more positive customer experience. 
 
For example, computer vision models that recognize items on a menu, can head off ordering errors by confirming the order's contents before it's delivered. This benefit alone saves the time, frustration and possible brand/customer experience damage that occurs when customers must go through the process of obtaining a refund. 

The technology can also be used during the delivery process to measure wait times and delivery routes by informing managers and crew members on the best delivery options and times, which again improves overall customer experience and brand performance. 
 
The same applications can also be implemented in-store to improve wait-times for those ordering at the counter. This, in turn, allows managers to add or remove cashiers as needed in response.

When it comes to common customer pain-points, these types of applications go a long way toward boosting customer and employee satisfaction, as well as worker retention. 

 A vision of better training

A recent report from Toast, Inc. listed employee training as the third biggest challenge for restaurants, with 35% of restaurateurs ranking it within their top three operational issues. Training employees — particularly within the fast-paced environment of a quick-serve restaurant — can be a resource-heavy endeavor in terms of both money and time. 

Computer vision, however, can provide feedback and even augment workers. Though other industries are benefiting from these perks now, these areas could be of benefit to QSRs, as well. 

By using computer vision, remote managers and training staff can monitor and correct actions by new hires through real-time feedback. Franchisees, in turn, can save on resources like those needed to bring corporate trainers on-site, while still providing topnotch food safety and prep training. 

Here again, highly-trained, up-to-date staff not only improve customer satisfaction, but they are more likely to stay with the brand when they are better "kept in the loop" about what they are required to do on the job, even though no one is needed to physically watch over their shoulders.  

In short, computer vision and AI-enabled image recognition can help improve QSR business operations along with all the benefits that come with that. Likewise, these technologies offer the kind of flexibility that gives operators the freedom to customize their application based on their unique needs. In that respect, the options really are limitless.