I mentioned yesterday that I might blog about this subject. It’s a topic of very great relevance to restaurant operators, and it may have some value to operators in non-food sectors that offer a range of goods.
The most frequently used criteria for menu analysis are the financial performance and sales volume of each menu item. Selecting the right metric for each of these has been the subject of debate. With regards financial performance some experts advocated using gross profit percentage (GP%) i.e. selling price less dish cost as a percentage of selling price. The problem with GP% (like most percentages) is that it is fine for comparing one thing with another, but it does not actually measure financial performance. This is because you can have a high GP% on a low priced item that contributes less in cash terms than a lower GP% on a more expensive item. This was made even worse when some experts advocated using GP combined with sales volume, thereby measuring popularity twice. So I have always advocated (since 1987 onwards) keeping it simple. The financial measure should be cash contribution of each menu item (i.e. its selling price less its cost), and popularity should be the number of items sold in the given time frame.
All the dishes are then placed according to these criteria into a matrix to illustrate their respective performance. Each of the quadrants of the matrix can be assigned a name to represent figuratively the nature of items in each quadrant e.g. high popularity and high contribution items might be “stars”. Unfortunately different authors have assigned their own taxonomy, so there is no commonly agreed nomenclature. Effective management action is based on interpreting the reason for each item’s position and selecting one of the three or four suitable solutions. Most authors agree on what these solutions should be. The objective is to modify the menu’s composition in order to build on the positive items and reduce the negative ones.
For dishes with High Popularity and High Contribution (where “high” is above the average) the alternatives are do nothing; modify price slightly – up or down; promote through personal selling or menu positioning i.e. where on the menu the item appears.
For those with High Popularity and Low Contribution the menu developer should consider doing nothing; increasing price; or reducing the dish cost by either modifying the recipe, using cheaper commodities, and/or reducing portion size.
Action for dishes with Low Popularity and High Contribution will be designed to sell more of that item. The alternatives are do nothing; reduce price; rename dish; reposition dish on menu; promote through personal selling; and maybe remove from the menu.
Finally there are dishes with Low Popularity and Low Contribution. The alternatives to consider are do nothing; replace item with an alternative item; redesign dish; or remove dish from the menu.
An action that is often ignored is the ‘Do nothing’ option. It should be remembered that the menu analysis methodology designates “high” and “low” on the basis of taking the average. Hence there will always be those dishes with low popularity and poor financial performance. If every time the analysis was carried out, these dishes were removed without being replaced, the menu would end up with just one item on it. It is much more sensible to focus on one dish (or maybe two) in each quadrant and take action with regards these, rather than tackle every dish on the menu.
Another aspect to remember is that cash margins are likely to be different according to whether a dish is a starter, main course, or dessert. Hence it makes no sense to compare all the dishes on a menu, as the main course items will always outperform the other dishes. Menu analysis should be done by grouping similar dishes together and comparing their performance.
Finally, the operator needs to be aware of how homogeneous demand is. If the range of items sold at lunchtime is very different to those sold in the evening, then it is worth taking the sales for these two periods and analysing them separately. Likewise if midweek and weekend sales patterns vary.
Jones and Robinson 