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    Blog Hero

    Hot orders, cool heads: how intelligent operations keep QSR crews on the floor

    9 MIN | Nov 3, 2026 | Unisys Corporation

    Short on time? Read the key takeaways

    • Digital ordering, kiosks, and drive-thru systems now carry quick-service restaurant (QSR) revenue, so the support model behind them should get the same level of attention as the menu.
    • Intelligent store operations use telemetry and AI across devices, applications, and infrastructure to detect and resolve issues before crews or guests notice.
    • Pattern data across thousands of locations lets support teams prioritize fixes by revenue impact and pause a faulty software update before it reaches the wider network.
    • Start with a baseline: map your top recurring ticket drivers, check how device health is monitored, and measure peak-hour uptime alongside ticket counts.

    Restaurant crews are experts at serving guests, and the support behind their technology should stay out of their way. Here’s how intelligent store operations make this possible.

    Telemetry and AI across devices, applications, and infrastructure detect an issue, open a case, and start the fix, often before anyone on the floor notices.

    That matters because digital tools now carry the order — kiosks, mobile apps, and drive-thru screens. A recent DBS research note found that major QSR chains treat digital ordering, AI-powered personalization, and data-driven menu management as core operating architecture. In the note's view, technology is how chains turn traffic into repeat, profitable transactions. When the kiosk is the front counter, keeping it running becomes a revenue priority as much as an IT one.

    What are intelligent store operations?

    Intelligent store operations involve a proactive support model for multi-location restaurants. They combine device and application telemetry, AI-driven diagnostics, workflow orchestration, cloud infrastructure, and field services into one loop that detects, understands, and resolves technology issues before they disrupt service.

    The loop has three stages:

    1. Detect: Telemetry from kiosks, POS terminals, drive-thru systems, ordering apps, and cloud infrastructure flags an anomaly and opens a case, without anyone calling it in.
    2. Understand: AI-driven analysis correlates device, application, and infrastructure data to identify the likely root cause, assess business impact, and recommend the appropriate response.
    3. Resolve: A remote script, guided self-service for the shift manager, or a technician carrying the right parts handles the fix, depending on what the problem needs.

    The model works because it treats restaurant technology as one system. A kiosk is only as reliable as the ordering app it runs, the network behind it, and the support around it.

    With Unisys intelligent store operations, one global quick-service restaurant client achieved $5.5 million in savings, 20% faster resolution, 12% less effort per ticket, and 17% more tier-one resolutions. (Source: Unisys global quick-service restaurant client data, 2025).

    Keep crews focused on guests

    Most QSR support still begins when a crew member spots a problem and finds a spare minute to report it. During a rush, that minute rarely comes, so the ticket arrives after the orders are gone.

    Relying on a call is an outdated way to report a case, and it puts the job on the busiest people in the building. Crew members and shift managers are experts in running a restaurant. Every minute spent describing a frozen kiosk to a help desk is time away from the guests in front of them.

    Guests feel the difference. According to the National Restaurant Association’s 2026 State of the Industry report, nearly two-thirds of operators said technology improves the hospitality their restaurants offer, while only 41% of consumers agreed. Closing that gap starts with taking issue reporting off the crew's plate.

    Proactive monitoring does just that. Shift managers see device health across the restaurant in real time. When something needs attention, they already know what it is, what's being done, and whether they need to step in at all.

    Five ways to protect speed of service during the rush

    Each practice below reduces the time between a technology problem and full service, especially when a lost minute will cost the most.

    Prioritize by revenue impact. Many support teams treat a frozen kiosk the same as a forgotten password: same queue, same wait. Machine learning, trained on QSR device types and ticket patterns across thousands of restaurants, spots which issues spike at peak and ranks them by potential lost sales. The fix that protects the most orders goes first.

    Contain problems before they spread. When telemetry detects abnormal behavior in the first wave of a software update, a root cause analyzer traces the issue, the rollout pauses, and the findings go to engineering.

    Make every field visit count. When a remote fix won't do, AI-coordinated dispatch matches the right technician to the job by skills, proximity, and parts availability. The technician arrives with the fault history and a list of every remote fix already attempted, and augmented reality (AR) guides the repair. That preparation helps Unisys' 7,000+ field technicians reach a 95% first-visit fix rate, and each visit feeds the knowledge base for next time.

    Give shift managers a faster path. Some issues still need a person's eyes. For those, a manager can scan a QR code, report an issue, and schedule a callback after the breakfast rush. By the time the agent calls back, troubleshooting is already underway, and AR guidance walks them through the fix.

    Fix recurring issues at the source. Some incidents keep returning because the software or hardware behind them has aged. Modernizing ordering, loyalty, and kiosk applications helps remove failure points and get new features to guests faster. Ongoing applications and cloud management help monitor performance, correlate telemetry, and resolve emerging issues before they impact multiple locations. A device lifecycle management service keeps POS terminals and kiosks current, so aging hardware fails less often at peak, with predictable per-device costs in place of large capital outlays.

    Where to begin

    Proactive support depends on good telemetry, and coverage varies across older devices and mixed fleets. Four questions make a good baseline:

    • What are your top recurring ticket drivers, and which repeat month after month?
    • Is device health monitored in real time, or do problems surface after a shift ends?
    • Are aging applications causing the same issues at multiple locations?
    • Do you measure peak-hour uptime and crew experience alongside ticket counts?

    The answers point to your first intelligent store operations pilot, ideally on the devices and applications that carry the most revenue.

    Less downtime, more revenue

    Digital now runs the restaurant, and the support behind it can move just as quickly. When technology looks after itself, crews stay with guests, managers stay with their teams, and every location runs to the same standard.

    Explore intelligent store operations for quick-service restaurants and find out how it would work at your locations. A Unisys QSR advisor will show you where proactive detection could have caught your last three major incidents before your crew or guests felt them.

     

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