Boost Restaurant Performance: 5 Automated Recommendations for Managers

Restaurant managers make hundreds of important decisions each week. From how much food to order to how many staff to schedule, these decisions directly affect profitability, guest experience, and employee satisfaction. But in an industry where margins are thin and variables like weather, traffic, and seasonality change daily, even experienced managers can’t rely on gut instinct alone.

That’s where AI and automations can make a big impact. Intelligent, data-driven suggestions embedded directly into restaurant software take the heavy lifting off your managers. These systems don’t just show you numbers or reports; they surface actionable recommendations to help you make smarter, faster, and more profitable decisions. As artificial intelligence continues to evolve, these automated recommendations are quickly becoming the new standard for restaurant management platforms. Here's what that looks like for restaurants today: 

One of the most common challenges restaurants face is ordering the right amount of food. That means enough to meet demand but not so much that it leads to waste. Traditional systems rely on static par levels or manual tracking, which often fail to account for real-time sales patterns or special events.

In Crunchtime, the AI Forecast drives the recommendation by accurately predicting your future sales, guest volume, and check counts.

Next, the system analyzes your current on-hand quantities and compares them to your static or dynamic par levels, which stem from consumption patterns and the upcoming forecast. Finally, the system looks at your upcoming delivery dates to provide your manager with an exact recommendation of what needs to be ordered to maintain optimized stock levels. Learn more about recommended orders here. 

In the kitchen, aligning food prep with demand is another area where even small improvements drive big gains. Prepping too much often leads to waste, while prepping too little can create delays and poor guest experiences. 

As part of Crunchtime's AI-powered prep recommendations, the system tells managers not only what to prep, but when to prep it, down to the 15-minute interval. Imagine starting your Monday morning with the system telling you exactly when to start thawing chicken, and how much is needed. 

This feature is fully customizable as the user can set up recipes for batch cooking in advance, or vegetable prep  for intermediate or sub-recipes. It can even tell you when to start removing items from the freezer for thawing times. 

For restaurants like Panini Kabob Grill, using Crunchtime’s prep recommendations have become a non-negotiable part of their operation.

“We have a policy in place where Crunchtime’s recommendations become an absolute established baseline, and we hold kitchen managers accountable if they do not prep according to Crunchtime’s suggested prep," says Scott Costello at Panini Kabob Grill. “We find more often than not, Crunchtime’s suggested prep is far more accurate than what we would have chosen manually.” — Scott Costello, Panini Kabob Grill

3. Recommendations on how many hours to schedule each employee

Labor costs are one of the biggest controllable expenses in any restaurant. Scheduling too many people cuts into profits, while scheduling too few hurts service and sales.

Crunchtime Labor & Scheduling uses AI forecasting to recommend how many hours to schedule for each role and shift. These predictive models factor in sales forecasts, consumption, historical traffic, holidays, and more. By giving managers clear, data-backed staffing recommendations, restaurants can maintain service quality while minimizing labor overspend.

No single forecasting model is perfect for every situation. Sales patterns at lunch might behave differently than dinner, weekends might trend differently from weekdays, and promotions might skew typical patterns.

That’s why advanced systems continuously monitor your forecasting accuracy — and then recommend when it’s time to switch algorithms.

For example:

• The system might detect that its current sales forecasting model consistently underestimates lunchtime volume.
• It compares alternative algorithms (like moving to the projected consumption model), which have historically performed 10% better.
• It then alerts the manager or automatically recommends switching to the better-performing model for that time segment.

This approach keeps your forecast as accurate as possible, even as business patterns evolve. Managers no longer need to guess which model to trust; the system recommends it for them.

Weather can drastically change restaurant performance, but not every operator has time to monitor forecasts and manually adjust staffing or prep plans. That’s where AI-powered recommendations make a difference.

Modern restaurant software now continuously tracks weather data alongside sales forecasts, analyzing how conditions such as temperature, precipitation, and severe weather have historically affected your specific location’s performance.

When the system detects that upcoming weather patterns are likely to influence demand, it doesn’t just silently update the forecast; it recommends that managers take action.

For example:

• If rain is expected on a day that’s normally busy, the system might alert the manager: “Forecasted rainfall may reduce dine-in traffic by 18%. Consider adjusting your sales forecast and reducing labor by two hours for tonight’s shift.”
• Conversely, a sunny weekend could trigger a proactive suggestion to add staff or prep more inventory for patio service.

This kind of proactive guidance empowers managers to make timely, data-backed decisions without having to constantly analyze weather reports or guess how they’ll affect business.

The Bottom Line: From Data to Decisions

The restaurant of the future won’t be managed by spreadsheets or static dashboards — it will be guided by AI and automated recommendations that help managers act on insights in real time.

From food ordering to prep, labor scheduling to weather-driven adjustments, these systems turn complex data into confident, high-impact decisions.

Restaurants that embrace these tools will reduce waste, control labor costs, and stay agile no matter what the forecast holds because when managers have the right insights at the right time, everyone wins. 

to learn more.