Labor optimization is a frequently misunderstood term.
For years, the conversation has mostly centered on cutting. Cut hours. Cut shifts. Cut the percentage. Get labor under control.
And sometimes, that work matters. If labor is too high, operators have to address it.
But cutting is not the same thing as optimizing.
The Real Problem
A labor target is not a labor plan.
When a manager is told to “hit 17%” there are a lot of ways to get there. The fastest way is often to reduce hours, trim shifts, or ask fewer people to do more work.
On paper, the number improves.
Inside the restaurant, something else may be happening.
Service slows down. Guests wait longer. Tables turn more slowly. Team members become frustrated. Strong performers begin carrying more of the load while the operation becomes increasingly dependent on simply getting through the shift.
The restaurant may achieve the labor target while creating entirely new problems.
That’s why labor optimization can be risky when it’s approached as a cost-cutting exercise instead of a planning exercise.
What’s Changing
Labor optimization is not the activity. It’s the outcome. The real work is labor planning.
It starts with understanding what the business is trying to accomplish. What sales are expected? When will those sales occur? What staffing levels will be required throughout the day? What operational challenges are likely to emerge? How much flexibility is needed for weather, seasonality, special events, or unexpected demand?
Those answers rarely come from a labor percentage.
They come from understanding the operation.
Most restaurants already have much of this information available. POS systems contain valuable data about sales patterns, ordering behavior, guest traffic, checkout timing, and operational peaks. Combined with historical performance and local business knowledge, that data can help operators understand not only how many people are needed, but when they’re needed.
The challenge is turning that information into a realistic plan.
And that’s difficult work.
It can be difficult for a new manager to learn the business. It can be difficult for an experienced operator managing a complex operation. The more volatile the business, the more important planning becomes.
Fail to plan, plan to fail as the old adage goes.
What Actually Works
The strongest restaurant brands are beginning to approach labor differently.
Instead of using technology primarily to measure labor performance after the fact, they’re using technology to improve planning before the schedule is ever published.
That distinction matters.
Recently, a multi-unit restaurant group was working through a particularly difficult labor planning challenge. The business shares employees between locations, experiences significant weather-driven volatility, operates with strong seasonality, and has undergone major operational changes over the past year.
The objective wasn’t simply to reduce labor.
The objective was to improve hospitality, reduce logistical complexity, prepare for growth, support peak demand, and maintain profitability at the same time.
Using Axial’s connection to Claude, the team spent time evaluating different scenarios and building a labor strategy based on actual operational data. Claude wasn’t creating schedules in isolation. It was helping management analyze historical performance, understand constraints, and evaluate tradeoffs.
The result wasn’t a schedule. The result was a better plan.
The following week, sales increased roughly 70% above recent levels.
The labor plan didn’t create the demand. But it allowed the operation to capitalize on it.
The team handled the volume successfully, maintained strong service standards, generated multiple five-star reviews, achieved high sell-through and did so while operating with a lower labor cost structure than before.
That’s what labor optimization should look like.
Not spending the least, but getting the plan right.
What To Do Now
Restaurant brands should be careful not to confuse labor targets with labor strategy.
Percentages matter. Budgets matter. Accountability matters.
But labor optimization happens when those goals are connected to a thoughtful plan for serving guests, supporting employees, and operating profitably.
The most effective operators are building feedback loops between planning and execution.
What was forecasted? What actually happened? Where did staffing succeed? Where did it fall short? How did guests respond? How should the next plan improve?
Increasingly, AI is helping answer those questions.
Not by replacing operators, but by helping operators learn from prior execution and make better decisions going forward.
Because labor optimization isn’t about cutting labor. It’s about getting labor right.
And the brands that consistently get labor right are usually the brands that planned for success long before the shift began.
