What data do I need to do menu engineering properly in my restaurant?

What data do I need to do menu engineering properly in my restaurant?

To answer “What data do I need to do menu engineering properly in my restaurant?”, you need accurate sales data and precise cost data for every menu item. At minimum, you must know how much each item sells and how much it costs you to produce. Without both, menu engineering becomes guesswork instead of a structured management tool.

In most restaurants, menu engineering is based on two main factors: profitability and popularity. Everything else supports these two measurements.

1. Sales Data (Item Popularity)

Sales data tells you which items guests actually order. This is typically pulled from your POS system over a defined period, such as 30, 60, or 90 days.

• Number of units sold per item
• Total revenue generated per item
• Sales mix percentage (item sales divided by total item sales in that category)
• Seasonal or daypart trends (lunch vs. dinner, weekday vs. weekend)

For example, if a burger sells 450 times in a month and a steak sells 90 times, the burger is clearly more popular. That popularity matters, even if the steak has a higher price.

2. Food Cost Data (Item Profitability)

Profitability depends on accurate recipe costing. In practice, this means knowing the exact cost of every ingredient and the standard portion size used in service.

• Detailed recipe with quantities
• Cost per ingredient (based on supplier invoices)
• Total plate cost
• Food cost percentage
• Contribution margin (selling price minus plate cost)

Contribution margin is widely used in menu engineering because it shows how much each dish contributes toward covering labor and overhead. An item that sells for $20 but costs $15 to produce is less valuable than a $14 dish that costs $5, even if the selling price is lower.

3. Category-Level Benchmarks

Menu engineering is usually done within categories (starters, mains, desserts, drinks). You will need:

• Average contribution margin per category
• Average popularity percentage per category

These averages help you classify items into commonly used groups such as high-profit/high-popularity, high-profit/low-popularity, low-profit/high-popularity, and low-profit/low-popularity. This classification supports decisions about promotion, price adjustments, or removal.

4. Operational Data (Often Overlooked)

Beyond numbers, experienced operators also review operational factors:

• Preparation time and kitchen complexity
• Waste levels and spoilage risk
• Equipment dependency
• Staff skill requirements

An item may be profitable on paper but slow down the kitchen during peak hours. In a busy café or bar, complexity can reduce overall efficiency, which indirectly affects profitability.

How It’s Typically Done in Practice

In most restaurants, menu engineering follows a structured process:

• Step 1: Export item-level sales data from the POS for a defined period.
• Step 2: Calculate accurate recipe costs using current supplier prices.
• Step 3: Compute contribution margin for each item.
• Step 4: Compare each item against category averages.
• Step 5: Classify items and decide whether to promote, reprice, reformulate, or remove them.

For example, a restaurant may discover that its most popular pasta dish has a low margin. Instead of removing it, they might slightly adjust the portion size, renegotiate ingredient costs, or increase the price modestly. On the other hand, a high-margin dish that rarely sells may need better placement or description rather than elimination.

How Digital Menu Systems Can Support This

Digital menu and management platforms can help centralize item data, pricing, and availability across one or multiple locations. For example, systems like Menuviel allow operators to manage items from a single dashboard and adjust prices or highlight selected dishes consistently across menus.

While the analysis itself depends on your sales and cost data, having a centralized system makes it easier to implement changes quickly once decisions are made.

In short, proper menu engineering requires reliable sales volume data, accurate recipe costing, contribution margin calculations, and category benchmarks. When these numbers are correct, your menu decisions become structured, measurable, and financially grounded.