Menu engineering is often presented as a clear path to higher profitability: adjust pricing, promote high-margin items, refine the menu mix, et voilà. But it is much more than that.
Explore how F&B and operations leaders can apply it more intelligently: not as a formula for maximizing individual item performance, but as a tool for strengthening the menu as a whole.
Before we briefly cover the mechanics, the pitfalls of menu engineering, and how to avoid them, one point upfront: This profitability framework still matters.
However, menu decisions now carry more commercial weight than many operators would assume. That said, a menu is more than a pricing tool or a sales mechanism.
EHL Professor Dr. Marc Stierand, who has worked in restaurants on menu engineering for many decades, notes:
Also, the role of this framework has become even more important in environments where spending behavior is evolving:
Recent industry analysis, such as McKinsey’s consumer research, suggests that in many markets, dining behavior is increasingly influenced by value considerations. Rather than abandoning brands altogether, a growing number of guests adjust their spending by taking advantage of promotions, ordering fewer items, or opting for lower‑priced choices.
These shifts do not affect every segment equally, but they reinforce a broader operational dynamic: menu decisions now influence profitability more directly because guests are making more considered choices.
At the same time, pickup demand is rising while delivery spending softens, signaling changes in both guest behavior and channel economics. In that environment, menu engineering becomes even more important but also riskier, because blindly applying it can lead to costly mistakes.
Before we touch upon those mistakes and pitfalls, let’s briefly cover the basics.
Menu engineering is a prominent technique used by restaurant operators to assess menu item popularity and profitability, enabling critical decisions such as pricing, sales strategies, and menu design.
In simpler terms, it connects the guest's choice to what drives the restaurant's profitability, and when used correctly, it should not only improve item economics but also strengthen the menu as a commercial system.
In practice, this means asking not only “Which dishes make the most money?” but also “Which dishes do guests actually order, and how often?”
Answering these questions requires the systematic application of two analytical core concepts: contribution margin and sales mix (menu mix) analysis.
Contribution margin (CM) shows how much each menu item contributes to the business each time it is sold. In simpler words, it is the revenue from a dish after covering its direct, variable costs, primarily food, and in some cases, closely related expenses.
It is typically calculated as:
In menu‑engineering, food cost is usually defined as the standard cost of ingredients and dish‑level garnishes/supplemental items used to produce one portion. This item-level CM is then used to:
However, food cost alone rarely reflects a dish’s true economic impact. Elements such as labor, waste, preparation time, and operational complexity can significantly affect its overall contribution. As an industry expert and EHL Professor, Dr. Cindy Heo notes:
She also highlights that profitability alone does not determine a menu item’s importance. A dish may contribute modestly to the bottom line while still driving demand or shaping guest choice.
This is where sales mix analysis becomes essential.
Instead of looking for revenue or profit, the sales mix, also known as the menu mix, focuses on how often an item is sold.
It is calculated by comparing the number of portions of a single item sold to the total number of items sold on the menu over a specific time period.
For example, if 120 out of 1,000 dishes sold are a specific item, its sales mix is 12%. This highlights which dishes resonate most with guests.
Taken together, these metrics provide clarity into your menu's performance and help:
However, in practice, operators rarely work with these metrics in isolation. Instead, they combine them into a framework designed to guide decisions.
We will touch upon this below.
Those data-driven insights bring structure to what is often managed by intuition. They make menu performance measurable and highlight tensions that are otherwise easy to overlook, such as dishes that sell well but generate little profit, or items that deliver strong margins but fail to attract demand.
To simplify these insights, menu engineering is often represented in a framework, a menu matrix, that groups items by profitability and popularity, commonly labeled as:
Stars (high popularity / high profitability),
This makes patterns easier to interpret and suggests where attention is most needed.
However, looking at a menu only through a data lens is where the risk begins.
The menu matrix and the data both concentrate on what can be accurately measured. They don't describe how the menu functions as a system or how customers perceive value.
EHL research published in the International Journal of Gastronomy and Food Science shows that guests rate meals not only functionally. Atmosphere, appropriateness, familiarity, privacy, and emotional fit for the occasion play a crucial role in the guests' experience.
As a result, using menu engineering purely as a decision rule rather than a diagnostic tool can lead to predictable mistakes:
A simple pasta dish can be financially weak but still essential to the menu, anchoring a category, structuring price perception, or guiding choice. Removing it may improve margins, but it would make the menu less intuitive and even eliminate the approachable option that helps price-sensitive guests commit to ordering.
Ask: Am I removing a low-margin item, or removing part of how the menu makes sense to the guest?
Or in other words, not seeing the menu as a whole.
Increasing the price of a popular steak on your menu, or promoting or repositioning it, can lead to reduced performance because guests might be pushed toward a less profitable substitute.
Ask: Does this change create real incremental profit, or just move sales from one item to another?
When reducing value to price and order frequency, menu engineering fails to reflect how guests interpret value beyond the numbers. Ordering decisions are influenced by expectations, perceived fairness, and comparisons with menu alternatives. A technically correct change can still reduce willingness to order if it feels inconsistent with the rest of the offer.
Ask: Does this decision increase sales efficiency at the cost of perceived value or willingness to order?
What works well in a dine‑in setting does not automatically translate to delivery or digital channels. A dish that performs strongly in the restaurant may struggle in delivery due to poor travel quality or a drop in perceived value once fees are added.
Ask: Does this menu optimization still work the same way across other channels, and am I optimizing for one while underperforming in another?
Menu engineering is most effective when it improves the menu's overall performance, not just the metrics of individual items. This broader operational perspective is reinforced in the EHL 2025 Global Foodservice Outlook, which highlights that profitability increasingly depends on integrating menu decisions with operations, execution, sourcing, and channel strategy rather than on food-cost optimization alone.
In practice, that requires operators to move beyond item-level optimization and evaluate how each decision affects guest behavior, operational flow, and overall profitability.
Before changing prices, removing dishes, or promoting specific items, ask:
Most importantly, evaluate menu items not only by profitability and popularity, but also by the role they play within the menu.
Some dishes attract guests, some structure price perception, and others create familiarity or balance within the offer. Removing them too aggressively can improve isolated metrics while weakening the menu’s overall performance.
Used this way, menu engineering becomes a tool for aligning profitability, guest expectations, and operational performance within a single menu strategy, rather than a pricing exercise!