Engineering a menu combines art and science.
The science aspect of the menu tends to challenge most operators. Learn the best way to gather the most effective data to streamline the science of designing an optimized menu.
Restaurant operators often propose that “menu engineering” is firmly in the realm of menu design, layout, and customer psychology. Others propose that menu engineering is not as much about the menu layout or design, but more about prices and profits. Both proposals are accurate because menu engineering truly blends both art and science. Luckily, everyone agrees that the most successfully engineered menus greatly benefit sales and profits.
Always start with the right data. This will allow you to create an ideal menu right from the start.
Use these three guidelines to make sure that your data set includes important aspects for each menu item:
1. Detail the transaction level:
- Tracking Menu Items: For every restaurant, for every menu item, make sure to track each time a menu item was sold, and how much money each item garnered.
- Date range: Use the longest time frame possible. This will allow you to best compare data against previous periods.
2. Cost of Ingredients:
- Calculate and report all costs with the same method across all of your operations.
- Remember that ingredient costs for a menu item will determine its profitability.
3. Segment the Menu:
- Compare similar items by segmenting them into categories such as entrees, appetizers and desserts. You may also wish to subcategorize them into eating time periods such as breakfast, lunch, or dinner.
- As with food ingredient costing, segmenting the categories of the menu must be consistent across the entire data set in order for the analysis results to be usable.
Core aspects of the “science-side” of menu engineering include:
- assessing customer needs
- percentage of sales
- costs of ingredients
- profit margins
They also must allow you to easily identifying more or less profitable menu items. Where do you look for the data to make these calculations?
An effective business intelligence and analytics tool will perform all of the heavy lifting by accessing a comprehensive data warehouse pre-populated with all of the data (and a lot more) mentioned above. Of course, this data is collected and analyzed by your enterprise back office solution.
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