The Importance of Analytics in Menu Engineering and Development

I often come across F&B business owners who develop their menus through gut feel and observation. While those aren't negative qualities in itself, Let me say that there is actually a way to be more analytical and consistent in developing and engineering menus to achieve better profit margins, reduce cost, and achieve scalability.

Why should Menus be Engineered?

Lack of Menu Engineering can lead to a whole gamut of problems surrounding a F&B business. From a financial standpoint, poorly or non-engineered menus often come with inconsistent costs month on month, incur higher than acceptable rates of wastage, and there is often a 10-15% rate of redundancy in the menu(items that are stocked but do not sell). From a strategic standpoint, because of the inconsistencies experienced financially, this makes it extremely difficult to scale the business, expand, and achieve operational consistency across all points of sale.

Sources of Analytics in Menu Engineering

When we talk about analytics in Menu Engineering, we aren't talking about solicited data gathered from big data consultancies on the latest consumer trend. You can gather the data you need right within your own operations. The fundamental pieces of data you will require, include, number of portions sold per dish, costing and recipe cards per dish, profit margin per dish, and total number of portions sold across all dishes.

Analysing the Data

The objectives of analysing the data can be split into two main objectives. Firstly, you will want to identify the growth-share of each of your menu items. Secondly, you want to separate the vital few from the insignificant many (80-20 rule or Pareto Theory). Identifying the growth-share of each of your menu items will give you an indication on dish-specific actions you need to take (increase price, cut cost, increase marketing etc.), while separating the vital few from the insignificant many will prove to you that indeed, in most cases, 20% of your menu items account for 80% of your revenue. This is where you will find the redundancy, and when you can remove them.

In another article, I'll share a little more about ensuring your data is clean, so that your subsequent analysis is conclusive.

Cheers

David Foo