1.15.2026
Restaurant operators have spent the last decade investing in technology designed to deliver visibility: point-of-sale systems, dashboards, labor tools, online ordering platforms, loyalty programs, and delivery integrations. Yet despite this proliferation of systems, many operators still lack clarity about what is happening in their business right now—let alone what is likely to happen tomorrow.
That contradiction is one of the central takeaways from The Restaurant Optimization Playbook, a new research-driven eBook independently produced by Starfleet Research and presented by Square. Based on market research involving 350+ restaurant owners and operators, the study shows that in a landscape defined by volatile demand, rising labor costs, supplier price instability and increasingly complex guest expectations, restaurant optimization has moved from a tactical priority to a core operating strategy.
Across formats, from quick-service and fast casual to fine dining, bars, taprooms and cafés, restaurants are confronting the same fundamental problem: too many critical decisions are still being made using incomplete, delayed, or disconnected information. In 2026, speed matters, but speed of insight matters more.
Forecasting confidence is fragile—and that’s now a profitability risk
Perhaps the most striking finding from the research is how few operators feel confident forecasting key operational variables such as sales, traffic, and labor needs.
Only 18% of restaurant operators describe themselves as very confident in their ability to forecast sales, labor requirements, or guest traffic on a daily or weekly basis. Nearly half (48%) say they are only somewhat confident, often citing unpredictable disruptions such as weather events, promotions, holidays, and staffing issues. Another 32% admit they are not very confident or not confident at all.
This forecasting gap affects restaurants at every stage. Pre-opening operators struggle to model demand accurately before real-world data begins flowing. Long-established restaurants often rely on historical patterns that no longer reflect current conditions. In both cases, forecasting weakness drives a more reactive style of management, which can be costly in an environment where labor, inventory, and pricing decisions must be adjusted quickly to protect margins.
At the same time, operators are clear about what they want. When asked about predictive insights that incorporate external factors like weather, local events, and neighborhood traffic patterns, 74% of respondents rate those insights as extremely or very valuable. This is a strong signal that operators do not simply want “more reporting.” They want decision support that helps them anticipate what’s coming next.
The shift from dashboards to answers is accelerating
The research, which is currently available for complimentary download, also reveals how pervasive day-to-day uncertainty has become, even for operators with modern systems.
Nearly two-thirds of operators (65%) say they wish they had faster answers to core operational questions on a daily or several-times-per-week basis. Questions like:
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Why were sales down today?
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Which items are hurting margins?
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Why did labor spike on an otherwise normal shift?
Only 15% of operators say those questions arise rarely, reinforcing how reactive restaurant management still is despite widespread technology adoption. Many operators still rely on retrospective reports that summarize performance after the shift, day, or week has already passed. By the time issues appear in a report, the opportunity to correct them may already be gone.
This visibility gap is particularly notable given that 79% of operators say real-time data is essential to day-to-day operations. Yet only 64% say their current systems support meaningful measurement of key performance metrics. More than one in four (27%) report that they cannot reliably track even basic KPIs such as average order time, prep duration, or upsell conversion rates.
In other words, restaurants know real-time insight matters, but many still don’t have it in a form they can actually use.
Handheld POS has become the frontline optimization engine
One of the most impactful findings from the research is how rapidly handheld POS has evolved from a tactical tool into a strategic layer for data capture and performance optimization.
According to the study (click here to access), 72% of restaurant operators use handheld POS devices for line-busting or tableside ordering, while an additional 47% use handhelds for curbside or drive-thru workflows. Importantly, adoption extends well beyond traditional QSR environments. Fast casual brands use handhelds to manage customization without slowing throughput. Cafés use them to absorb morning rush volume without adding counter staff. Bars, brewpubs, and taprooms rely on handhelds to open and close tabs quickly during peak demand. Even fine dining operators are increasingly adopting handheld workflows for tableside ordering, wine service, and discreet payment processing.
Kitchen integration is another critical performance driver. Among operators using handhelds, 79% say the devices are integrated with kitchen display systems (KDS), allowing orders to flow instantly to the line. The payoff is measurable:
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82% report a positive impact on service speed
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63% report increased average check size driven by upsell prompts and modifiers
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70% report improved guest satisfaction due to faster service and fewer errors
Beyond speed, handhelds are increasingly valued for the intelligence they generate. Nearly half (47%) say their handheld systems support real-time promotions, loyalty integration, order-ahead workflows, and guest feedback collection. Meanwhile, 61% say their handheld systems track KPIs such as ticket size, prep time, and upsell conversion rates.
Given the forecasting uncertainty reflected in the research, this type of real-time insight becomes a necessary safety net—allowing teams to recognize demand shifts by channel, daypart, or service mode during the shift, not after.
Self-service ordering is now a revenue intelligence channel
Another major theme emerging from the research is the growing strategic role of self-service kiosks and guest-directed ordering.
Once viewed primarily as a labor-saving mechanism, self-service ordering is increasingly being positioned as a way to improve speed, order accuracy, and check size while generating cleaner behavioral data. More than half of operators report using self-service kiosks in at least one location, with adoption strongest among QSR and fast casual but growing steadily across cafés, bars, and high-traffic full-service environments.
Among kiosk-enabled restaurants, performance impact is significant:
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76% report reduced wait times
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67% report increased check size through upsell prompts and guest autonomy
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69% cite improved order accuracy with guests entering selections directly
Just as importantly, kiosks generate structured, consistent data: modifier selection behavior, abandonment points, completion times, and item-level demand patterns. This matters because the research suggests many operators know what sells but lack confidence in what truly drives profitability. Self-service ordering provides a clearer window into guest behavior, helping restaurants identify “popular” items that quietly erode margins.
Operators want proactive alerts and AI assistance—with guardrails
In a complex operating environment, even real-time dashboards may not be enough. Managers can’t realistically monitor dozens of KPIs during peak periods. That reality is driving growing interest in exception-based management.
When asked about proactive alerts that flag when metrics drift outside normal ranges (labor percentage, ingredient costs, ticket size, prep time), 78% of operators rate these alerts as extremely or very useful.
This is tightly linked to another emerging trend: AI-powered operational assistance. Nearly two-thirds (64%) say an AI assistant capable of answering questions about sales, staffing, or customer trends would be very or extremely helpful, with another 22% rating it moderately helpful. Importantly, the research shows operators are not looking to hand over control. They want faster explanations, clearer signals, and recommendations they can evaluate and approve.
Download the eBook: The Restaurant Optimization Playbook
In 2026, restaurant performance will be shaped less by how much data an operator collects—and more by how quickly they can convert data into action. Handheld workflows, self-service ordering, real-time analytics, proactive alerts and margin intelligence are no longer isolated capabilities. When integrated, they form the backbone of a more resilient, more adaptive and more profitable restaurant operation.
To explore the full research findings and a practical framework for restaurant optimization, download the eBook: The Restaurant Optimization Playbook: How to achieve peak performance and profitability in 2026 — and beyond.
