How AI Can Streamline Foodservice Equipment Repairs
Article contributed by Sidney Lara, Service Principal, Aquant
The relationship between restaurants and service organizations is a tale as old as time. The ice cream machine breaks, the restaurant manager calls the service company, they send a service technician to fix the machine, the technician fixes the problem, and customers get to enjoy their soft serve again. Easy enough right? If only it were that easy.
Due to labor shortages and skills gaps, the downtime on kitchen equipment — like the aforementioned ice cream machine — is getting longer and longer. Restaurant owners and food service managers are putting immense effort into hiring and training an unprecedented level of workers to fill open positions, causing repair and maintenance to take a back seat. At the same time, the aging workforce in the service industry is making it harder to find qualified technicians, leading to longer response times when a service call comes in from a restaurant.
Restaurants are short staffed, and it’s putting other industry challenges in the back seat
The labor shortage continues to be a significant challenge facing many business owners. A July 2022 survey from the National Federation of Independent Business found that about half of small-business owners said they still can’t fill open jobs, a near-record high in the survey’s roughly five-decade history.
Restaurant owners, as we know, are among this group — frantically looking for new workers, while massively increasing time and effort to train their new workforce. The industry is still down 750,000 jobs — roughly 6.1% of its workforce — from pre-pandemic levels as of May 2022, according to the National Restaurant Association. As a result, repair and maintenance of kitchen equipment has become an afterthought.
However, putting repair and maintenance (R&M) planning on the back burner will, in turn, raise the overall operating and capital expenses of a restaurant by 15%, according to ResQ’s State of Disrepair report.
But rather than restaurants simply prioritizing traditional R&M, it’s time for the service and repair teams to embrace new technologies that will enable the entire workforce to complete jobs more effectively–no matter how experienced their technicians are–so that restaurants avoid downtime altogether and stay fully operational. Restaurant owners can then reallocate time and money to more efficient uses, like ensuring they can hire staff as needed.
Service organizations are implementing AI technologies to streamline operations
At the same time, finding qualified service technicians is a major pain point. This problem affects many service companies who operate in the food service industry, including United Service Technologies (UST) who service supermarket hot-side equipment. As an additional challenge, UST customers are demanding actionable data at an increasing rate. Faced with these two issues, UST turned to AI to solve their problems.
UST was unable to find the time to sift through thousands of invoices by hand to identify useful insights. But now, with powerful emerging technologies, like AI-powered service intelligence, their teams can organize and analyze invoices, calls, and reports in minutes, providing actionable insights in a fraction of the time. Use of this emerging technology helped UST generate actionable service insights on the over 25 years worth of data they collected.
UST now takes advantage of the massive amount of data they have and use it to transform their once reactionary business into one that is far more predictive. They are able to be prescriptive and tell customers what the entire life cycle of a machine will look like, all without exhausting their IT efforts.
UST also uses service intelligence as an educational tool for new technicians to troubleshoot repairs and learn the trade while they’re out in the field. Based on historical and real-time data, the system asks technicians a series of questions, then narrows down the most likely scenario, including the root cause of the expected failure, parts needed, and any additional or tangential issues. Techs arrive empowered to make the right decisions about alerts. Instead of taking an experimental approach and swapping out unnecessary parts, or walking away with a ‘no-fault-found’ diagnosis, both novice technicians and service pros are more likely to complete the maintenance job right the first time. Technology like this not only eliminates the skills gap between veteran and novice technicians, but also cuts out expensive and overly time-consuming training.
Another company moving the needle with AI innovation is Smart Care, America’s premier commercial kitchen service organization.
The leaders at Smart Care knew they needed to streamline operations once the organization became flooded with data. A single work order that technicians fill out every day contains thousands of data capture points. They needed to figure out how to leverage technology to build a platform that allowed Smart Care to help both customers and technicians alike by aggregating data and organizing it in a manner useful to both parties.
Smart Care wanted to take advantage of field service analytics and gain service insights that could help them move from an old, reactive service organization to a prescriptive one. Smart Care did not want to be stuck in an archaic business model, so in order to stay competitive, the company set out to find a solution through technology.
They turned to service intelligence. The AI-powered tool was not only able to read a work order as a living document, but also analyze the field notes each technician captured onsite. With this ability, Smart Care took their most complicated pieces of equipment and worked with the manufacturer to obtain building materials and FAQ documents, along with their own work order data, to build a diagnosis tool technicians use in the field on specific pieces of equipment.
As a result, Smart Care saw a dramatic reduction in things like recall ratios and ordering the wrong parts which, in turn, saves the company thousands of dollars and generates positive customer experiences.
The average restaurant repair and maintenance costs across the U.S. are $28 billion per year. Regardless of the current state of R&M in your restaurant, it’s best to be proactive, rather than reactive. Smart Care and UST were both ahead of the curve with their organizational innovations. Finding the right service partner that has implemented cutting-edge AI-powered technologies could save the restaurant industry billions of dollars by avoiding downtime and ensuring each piece of kitchen equipment is always functioning as it should.
With over a decade of experience in operations and service, Sidney Lara brings incredible skill and insight to Aquant, a software company focusing on transforming unstructured company data into a business asset for improving customer satisfaction and workforce skills. He has a passion for solving problems in the field service industry, making his start as a field service technician and now using operations to solve problems in field service industries at a massive scale. Prior to joining the Aquant team, Sidney served in several service-oriented roles at companies such as Nielsen and Rational USA.