How To Boss A Menu Like Gordon Ramsay

How to boss a menu like Gordon Ramsay

If you have ever watched an episode of Kitchen Nightmares, you’ll find one theme which occurs again and again (aside from feigned melodrama, real nervous breakdowns and extensive, elaborate and very British-flavoured tirades of swearing, of course): Keep it Simple!

If you give most chefs free control over the menu, not only will they cram it full with expensive, perishable (but hopefully delicious) dishes, but they will inevitably cram it with too many of them.  Because they love to cook them all.

We’ll leave the conversation about input costs, margins, wastage and profitability for another day (and we’ll help you out with some free tools to support this) – today we want to focus on menu simplicity, why it’s a good thing and how to use your data to achieve it.

Customer Perception

Now different restaurant/café/bar types will have wildly varying numbers of choices on their menus: from a high-end degustation – where there may be no choices at all – to a Chinese restaurant where there may be near to a hundred items.

But there is a common misconception that more choice necessarily equals happier customers, whereas there is some pretty compelling evidence that this is not actually the case, and that more menu choices make for less content consumers.  In a 2013 paper, researchers from Bournemouth in the UK determined that the optimal menu size for a fast-food restaurant is a mere six items per category, and for fine dining restaurants seven starters and ten main courses.

They also determined that below a certain number of choices, customers became disconcerted, but the runaway success of companies like In’N’Out Burger in the USA (which sold out half an hour before it opened when it popped up in Sydney this year!), which only has three burgers on the menu shows that keeping it super-simple can work if you do it right.

Operational Simplicity

And keeping it simple is easier to manage too.  If you have a simple menu you can have simple processes, simple flows through the kitchen and it is simple to train (potentially simple) new staff members to get them right.  If they can perfect the smaller set of items on the menu much more quickly, you will ensure better consistency, higher quality and happier customers, who (hopefully) keep coming back for more, spending more money and bringing their friends.

There’s a reason that a company like Nathan’s Famous has gone from one small stall on Coney Island in NYC, to a global brand (recently arrived in Australia!) selling over half a Billion hot dogs a year – and a large part of that is down to keeping it simple.


Clearly a smaller, simpler menu should also have a lower number of different ingredients, and the ingredients which you do use will be consumed at a higher rate.  This increased ‘velocity’ will mean that your consumption should get more predictable, so you should be able to order more effectively to reduce wastage.  Less wastage = lower cost = higher profit margin.

When Joe Wee bought an existing bar and turned it into The Noble Hops in Redfern, Sydney, he got rid of all food, cocktails and anything perishable at all.  He now concentrates on one simple thing, amazing craft beer, which enables him to stay focused on sourcing and serving the best product to his customers.  The fact that he won Best New Craft Beer Venue at Sydney Craft Beer Week 2016 is testament to his hard work, and his clear, simple vision.  And the fact that he’s also cut his wastage down to an absolute minimum is great for his bottom line.

Building Your Brand

And once you’re known for doing one thing (or a couple of things) really well, it’s much easier to focus your brand, your marketing and PR activity around this.  Think of the difference between the empty takeaway on the corner purporting to sell Kebabs, Chicken, Pizza, Curry, Fish & Chips, Steak, Pasta and Haggis, and you can see why there are often queues out the door at places like Carney & Earl’s in Coff’s Harbour, where they are singularly focused on their burger menu, which they do unbelievably well.

Burgers which are ‘hand formed, and then individually sealed and cooked in a water bath to a consistent medium rare, before being finished on the grill’, complemented by ‘perfectly melted cheese and artisan wood smoked bacon’?  Simple: Yes Please!

Keeping it Simple

So, in conclusion: keep it simple and you should be able make your customers happier, increase your revenues, improve your profit margins and also make your marketing clearer, simpler and more effective. And all you have to do is trim your menu down to size.

Sounds pretty simple, huh?  Well if you’re a Kounta and Floodlight client, then it really is… just read on below for guidelines on how to use one of our Floodlight Focus reports to do just this:

‘Identify Low Selling Category Items’ Report Objective:

This report is designed to support analysis of best and worst selling products within categories, in order to adapt your product line to the actual customer demands and maintain simplicity.  Different people will use different thresholds, but a good rule of thumb we find our clients use is: if it’s consistently less that 5% of the category (and there is no other specific dietary reason to keep it), then drop it from the menu.  Simples.

Extracting Data from Floodlight:

  1. Log into to your Floodlight Analytics dashboard
  2. Navigate to ‘Floodlight Focus’ in the left sidebar
  3. Select the ‘Accelerate Growth’ tab from the top tabs
  4. Scroll down to the ‘Plan Launch Stock Effectively’ report in the ‘Roll Out New Sites Efficiently’ section
  5. Select the desired Start Date and End Date (e.g. 8 weeks ago and today)
  6. Click the ‘Download CSV’ button
  7. Save the file historic_product_sales_qty_by_week to an appropriate location (e.g. local or cloud drive)

Report Overview:

All products with at least one sale in the selected time period will be presented in this report, along with the number of units sold within each week.

How to Use This Report:

  1. Format the data for easier readability
  2. Add a filter so you can quickly find the data you are looking for

Analysis within Category

  1. Filter down to the categories you are interested in analysing
    • Note that the column sum of categoryNamePercentage should be equal or very close to 100% (due to rounding errors)
      1. To quickly  find this sum, highlight the column and check the bottom right of your screen
  2. Sort the category into descending order to rank the products from best to worst sellers
  3. Review products within each category to identify any with a low value (e.g. <5%) in the ‘categoryNamePercentage’ column – these will be your lowest sellers within the category
  4. Consider whether you should still be selling these products if there are others within the category which are more popular
  5. Review products within each category to identify any with a high value in the ‘categoryNamePercentage’ column – these will be your best sellers within the category
  6. Consider why these are the best sellers and help this inform your view of what your customers actually want, and what you are doing really well.  Is it worth focusing more energy and effort on these products?

Additional Points to Note

  1. If using Excel for analysis, remember to save as an Excel file (e.g. xlsx) instead of csv or you will lose formatting and formulae upon saving


Report Specifications (for reference):

Row Structure

  • One row per product sold in the time period

Description Column Structure

  • categoryID: ID of the first alphabetical category assigned to the product
  • categoryName: Name of the first alphabetical category assigned to the product
  • productID: ID of the product
  • productName: Name of the product

Crosstab Structure

  • Crosstab Columns: Each column represents a single week of sales, and is labelled according to the date of the Monday of each week
  • Crosstab Units: Each datapoint represents the number of units sold in the week

Summary Structure

  • Total: Total number of units sold in the period
  • Accounting Average: Total number of units divided by the total number of distinct weeks in the report
  • Trading Average: Total number of units divided by the total number of distinct weeks with a non-zero unit count
  • All Datapoints: Number of distinct weeks in report
  • Non-Zero Datapoints: Number of weeks for which there were sales greater than zero
  • Zero Datapoints: Number of weeks for which there were no unit sales
  • categoryNameOverallTotal: Total unit sales for the category relating to this product
  • categoryNamePercentage: Percentage contribution of this product to the overall category sales, in terms of units sold over the full period
  • percentageOfAll: Percentage contribution of this product to total unit sales over the full period