In the commercial food service industry, an increasingly complex portfolio of kitchen equipment increases operational risk. Any piece can fail, torpedoing revenue and customer experience as the kitchen grinds to a halt. Our industry is already facing the 'Amazon effect' expectations. Equipment owners expect service and parts logistics at a level that had not been imagined a few years ago, along with the use of innovative technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) to deliver it.
This is the challenge faced by America's leading provider of commercial kitchen equipment repair and maintenance services. Smart Care serves restaurants, hotels, cafeterias, and other food service operations in more than 40,000 establishments across 42 states. Customers rely on our 600-plus technicians to fix and maintain refrigerators, walk-in coolers, commercial dishwashing equipment and cooking equipment from conveyor pizza ovens, griddles, steamers, gas ranges and more. These are capital assets worth hundreds of thousands of dollars apiece, and if they are not operating, revenue can grind to a halt, expensive food in freezers is destroyed and the experience of our customers' customer is damaged.
There is this whole expectation of service delivery, and timing of service delivery, and great communication and constant communication flow. But also, things like information on the equipment you're working on, and work order management systems, all point to consumerism driving the expectation of our end users much higher. Layer on top of that this whole idea of menu complexities — our CEO jokes around about this, and I agree with him, that when I was younger, I went to Taco Bell overnight. But I never went there for breakfast … Now they serve breakfast because they've expanded their menu. As their menus proliferate, the complexity of the equipment goes up and the redundancy goes down, because they only have so much square footage.
Optimizing the customer experience
AI has been a key success factor in meeting this demand as we have been able to automate our way around many of the challenges. An AI-driven schedule optimization engine makes real-time adjustments to dispatch-to-work assignments to get the ideal technician with the right parts on site even as emergent requests roll in. We also rely on AI to help technicians with part identification and equipment diagnostics.
Our service offers have expanded beyond traditional reactive break-fix repair. Smart Care also sells annual maintenance contracts that require proactive planning and management to ensure resources are available when needed and that plans are priced to be both competitive and viable.
A recent innovation that drives even more complexity is our new MYTECH® service which lets customers pre-pay for hours to use as they see fit, and when a SmartCare tech visits, they get a 'honey-do list'.
Essentially what the customer has done is given us a work order… saying here's the list of things I need you to look at as you're walking in. And the technician then, for the next three, four, five or eight hours that the customer has pre-purchased, will work on all of those items that the customer has asked for.
The importance of getting paid
This is convenient for customers but makes one element of field service management that much harder — getting paid for the work you complete and the parts you consume. The field service software solution has driven improvements here, however.
The value we've seen so far is in the mobility solution — the actual handheld the technicians use. With our previous solution we had seen what we called value leakage — essentially where time was not being either recorded or billed for accurately. But because we've configured the system in the mobility tool, such that there's an accurate record reconciliation of the job time on site, and the build time to the customer and the paid time to the technician, we have seen a pretty significant step up in the last two months… recovering that value on the labor side, part side, the chain of custody in terms of when a part moves through our warehousing system to the technician and ultimately to the work order. It's much tighter, and there's fewer areas for that part to get lost in the process.
Looking forward - value from customer data
Asset information and maintenance history that's residing in our software are a source of future potential as we figure out how to mine it and leverage it to improve services. This data can help SmartCare become a strategic advisor to the customer, offering insights on what assets or even makes or models of equipment are more problematic, and when assets are nearing end of life and should be replaced. However, we are still figuring out how to feed equipment insights back to newer technicians so the deep understanding developed by experienced techs over decades, and structured maintenance histories on customer equipment, can improve service levels and support a consultative approach.
In time, more kitchen equipment will include IoT sensors that can drive intelligent maintenance. It's not here yet, but the big data revolution will soon land in the kitchen. Equipment design will increasingly incorporate smart functionality to self-monitor and report proactively on a variety of custom data points from performance to parts, warranty expirations and advance notice of needed service and repair. Factory-trained technicians will be able to use the data to not only effectively repair the equipment to operating standard but also to offer insight on the causes of the failure and how it can be prevented in the future.
See Gyner Ozgul talk on this topic alongside peers from Auto Windscreens, Cubic Transportation Systems and Spencer Technologies, in this recorded panel event.