In today's day and age, restaurants and hotel managers are taking a lot of efforts in making their business profitable. For that purpose, various managerial approaches and methods are used by them. One such approach is menu engineering which is all about designing the menu and placing items as per their profitability and popularity. In this report, an illustration of the menu engineering is provided and EPOS data is analysed and the menu items are classified using Kasavana and Smiths method based on the profit margin and volume. Furthermore, a thorough discussion of the application and usefulness of menu engineering is provided. Various literature works are also reviewed in order to enlist the advantages and disadvantages of the menu engineering and providing recommendations for various categories of the food items on the menu.
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The very basic aspect of this report is to read about menu engineering and the most widely used method of menu engineering, i.e., Kasavana and Smiths method. This method is based on a matrix that assists in incorporating both profit margin and volume of the items on the menu. This facilitates in defining the key difference between the costs of products and selling price of the item on the menu. The method has classified different food items in the menu into four different categories based on the contribution margin and popularity (volume) (DiPietro, 2017). The categories are star, workhorses, dogs, and puzzle.
The data has been collected from the EPOS (Electronic Point of Sales) which is a computerized system used in recoding sales in restaurants and hotels (Khan& Rundle-Thiele, 2019). The managers can be able to get enough sales records of the restaurant of each item on the menu. Furthermore,it can also be seen that one can also retrieve data regarding time and place of the transaction. The data collected regarding each food items that include information related to a number of items sold, the cost of making the food, and sales price of the food item has been gathered from the EPOS.
Talking about the benefits and pitfalls of the menu engineering, literature and journal articles provided on the moodle are referred and reviewed thoroughly. They also provide some useful information about each category of food items as mentioned in the Kasavana and Smiths method.For providingrecommendations, same articles along with some other research work available online published in some peer-reviewed journals. These are quite helpful in getting insight into the topic and providing certain recommendations. The results are shown as clarification matrix and excel spreadsheet attached in the appendix.
From the data taken from EPOS and its analysis, it is quite clear that not all food items belong to the same category as given in the Kasavana and Smiths method. For the classification purpose, it is necessary to calculate the average popularity percentage and average gross profit earned by selling one unit of all items in the list. In this case, the average gross profit is $5.63 while the average popularity percentage is 9.99%. Hence, any item with a profit margin less than $5.63 would be considered as the food with low profitability while those items having popularity percentage lower than the average popularity percentage would be considered as a less popular food item in the menu of the restaurant. Based on the combination of profitability and popularity, all the listed food items on the menu have been classified into four categories.
Referring to the spreadsheet attached in appendix 1, it can be seen that Tournedos Rossini the popularity percentage is 11% while the profit margin of the item is $7. Both of these values are higher than the average values of popularity percentage (9.99%) and average profit margin ($5.63). Hence, this item belongs to the star category of menu items as per the theory of Khan& Rundle-Thiele (2019). Similarly, just by comparing the popularity percentage and profit margin of every item on the menu, the manager of restaurants can be able to carry out menu engineering. The classification of food items on the menu is done below:-
As mentioned by Khan& Rundle-Thiele (2019), menu engineering is about studying the popularity & profitability of food items mentioned in the menu of a hotel or restaurant. In addition to this, another aspect of this field of study is to determine how these two factors (popularity & profitability) impact the placement of the food items in the restaurant's menu. According to Attwood et al (2020), the primary motive of menu engineering is quite simple, i.e., increasing profitability of the restaurant per guest. The categorization of the food items is done into four categories based on the aforementioned two factors. However, the topic is a bit complicated as one should have deep knowledge and understanding of prices of menu items, cost of making food, and contribution margins (Attwood et al, 2020). With a detailed view of the menu items' popularity and profitability, the restaurant manager or owner can determine which food item gives higher profit and which food item is performing poorly in terms of sales (DiPietro, 2017).
As per the argument made by Reinders et al (2017), menu engineering efforts can increase the profits of any restaurant up to 10-15% within a week. Hotels and restaurants should carry out a menu engineering analysis at least once a year to squeeze additional profits out of the same menu. Reinders et al (2017) mentioned that all hotels and restaurant managers must understand that staff persons have a better idea about the popularity of the items as they are in direct touch with customers. Hence, they must be involved in the process of menu design. They must be provided with enough knowledge and training to judge the star or dog items or other categories of the menu items (Attwood et al, 2020).
Talking about the benefits and limitations of the menu engineering, different experts have given their opinion on this subject. For instance, Khan& Rundle-Thiele (2019) believe that menu engineering assists in making the sensible decisions about keeping or removing an item from menu or help in the positioning of dishes on the menu that might increase its sales. The manager of the hotel or restaurant can look into three areas simultaneously and can make wiser decisions. These include several dishes sold by the restaurant in a particular period, the gross profit margin associated with each dish and cost of making the food, and net profit associated with each dish (Machielet al., 2017). Just by carrying out a well-detailed analysis, the manager can be able to make an impact on the business bottom line. Furthermore, Khan& Rundle-Thiele (2019) outlined that menu engineering provides better operational control of the aspects of the food and beverage related operations.
However, there are certain limitations of menu engineering as highlighted by various researchers. For instance, Attwood et al, (2020) outlined that menu engineering is quite complex and hard to understand. Even a small mistake in the calculation can ruin the menu. Also, it has been noticed that it can result in a larger menu that can lower down the contribution margin. It can also confuse customers while choosing the right food option for them. Reinders et al (2017) mentioned that menu engineering increases the usage of preset assets. As menu engineering creates a pre-model of the services. It has been noticed that customer expectations get increased regarding customer service quality and they expect more from the hotels and restaurants every time they visit them.
Referring to the menu engineering matrix discussed in section 3 of this report, it can be seen that certain items have been classified into a dog, start, plowhorses, and puzzles. Each category has a different definition and characteristics in terms of costing and popularity. These are discussed in this section.
Talking about star items, in the given case, Tournedos, blue cheese rump steak, Cod Mornay, scampi & chips are considered a star. This means these food items have a high popularity and high profitability (Attwood et al, 2020). This can be seen in figure 1 or Appendix 1 that the contribution margin of each food item mentioned above has the profit margin more than the average contribution percentage which is $5.63. Moreover, the popularity percentage for each item is also more than the average popularity percentage of the restaurant items (Machielet al., 2017).
Figure 1: Clarification Matrix
Talking about the dog items, these include items like vegetarian pasta and sirloin steak. The chart shows that these items have a low-profit margin and low popularity. This means they have high making cost and not very much appreciated by customers (Lai et al., 2019). These items are consuming space on the menu for those items that can add more value to the restaurant (DiPietro, 2017).
Coming on the plowhorses items, these items include those items which have high popularity but low profitability (Ben Hadj Salem?Mhamdia& Bejar Ghadhab, 2012). In this case, these are cottage pie, lasagna, and beef bourguignon. This means that restaurant managers must think about making such items cheaper to earn maximum profit out of them (DiPietro, 2017).
At last, comes the puzzle items, these items are those that have high profitability but are quite less popular among customers (Lai et al., 2019). This might be due to many factors and these are required to be determined by the hotel managers. In appendix 1, it can be seen that there is only one item in the list which is categorized as a puzzle item which is Pork steak with Wild Mushrooms.
As recommended by Machielet al (2017), the restaurant owners or managers must involve the team and staff members in thinking about improving the dog items and change the approach of selling them. These can be added in a combo meal or can be offered as a complimentary meal to increase the popularity among patrons. Even after this much efforts, if the sales do not increase, then restaurant must think about removing them from the menu items and add some new replacements that could add more value to the restaurant (Machielet al., 2017). However, rebranding and reinventing are two other options as well that can be used for this category of food items in the list.
Even due to lower popularity, it is commonly observed that puzzle items are kept in the menu by managers due to their high-profit margin. Therefore, the manager must think about making them popular through word of mouth method, training their servers to describe dishes to customers and persuade them to order them. Also, running promotion can have a certain impact on consumers' mind. DiPietro (2017) recommend that restaurant can also think about lowering prices that might increase the popularity percentage of the item.
The plowhorses items require a bit of rework in creating the profitability of the items through changing the recipe. Lai et al., (2019) believe that by adjusting the ingredients in the food, the cost can be optimized. In addition to this, the manager can keep the focus on the appearance of the food items being served to them and their portion size. These techniques can make a plowhorse item a start category item.
According to Lai et al (2019), even the star items need regular improvement. The manager of the hotels or restaurants can think about increasing their prices or packaging them along with other puzzle items to add more value to the profit margin.Machielet al., (2017) suggested that star items are required to be made highly visible on the menu and restaurant should keep promoting them consistently to add more revenue.
From this analysis report, a discussion on the menu engineering is done wherein the menu of a restaurant has been reviewed and items have been classified given in the Kasavana and Smiths approach. A discussion on the menu engineering, its usefulness, and benefits & limitation was done. The arguments placed in the report were based on the literature review done using the journal articles. In the report, mathematical analysis of the data gathered from the EPOS and brief description of the hotel's menu engineering was provided. In addition to this, the clarification matrix was created and elaborated in one of the section in the report. Also, the recommendations regarding each of the categories of the menu engineering were provided at the end of the report.
Attwood, S., Chesworth, S. J., & Parkin, B. L. (2020). Menu engineering to encourage sustainable food choices when dining out: an online trial of priced-based decoys. Appetite, 149, 104601-104601. https://doi.org/10.1016/j.appet.2020.104601
Ben Hadj Salem?Mhamdia, A., & Bejar Ghadhab, B. (2012). Value management and activity-based costing model in the Tunisian restaurant. International Journal of Contemporary Hospitality Management, 24(2), 269-288. https://doi.org/10.1108/09596111211206178
DiPietro, R. (2017). Restaurant and foodservice research. International Journal of Contemporary Hospitality Management, 29(4), 1203-1234. https://doi.org/10.1108/IJCHM-01-2016-0046
Khan, J., & Rundle-Thiele, S. (2019). Factors explaining shared clothes consumption in china: individual benefit or planet concern? International Journal of Nonprofit and Voluntary Sector Marketing, 24(4). https://doi.org/10.1002/nvsm.1652
Lai, H. B. J., Karim, S., Krauss, S. E., & Ishak, F. A. C. (2019). Can restaurant revenue management work with menu analysis? Journal of Revenue and Pricing Management, 18(3), 204-212. https://doi.org/10.1057/s41272-019-00194-6
Machiel, J. R., Marlijn, H., S, C. D., Anna, J. M., & Joris, H. (2017). Menu-engineering in restaurants - adapting portion sizes on plates to enhance vegetable consumption: a real-life experiment. International Journal of Behavioral Nutrition and Physical Activity, 14(1), 41-41. https://doi.org/10.1186/s12966-017-0496-9
Raab, C., Mayer, K., & Shoemaker, S. (2010). Menu engineering using activity-based costing: an exploratory study using a profit factor comparison approach. Journal of Hospitality & Tourism Research, 34(2), 204-224.
Reinders, M. J., Huitink, M., Dijkstra, S. C., Maaskant, A. J., & Heijnen, J. (2017). Menu-engineering in restaurants - adapting portion sizes on plates to enhance vegetable consumption: a real-life experiment. The International Journal of Behavioral Nutrition and Physical Activity, 14(1), 41-41. https://doi.org/10.1186/s12966-017-0496-9
Seyitoglu, F. (2017). Components of the menu planning process: the case of five-star hotels in Antalya. British Food Journal, 119(7), 1562-1577. https://doi.org/10.1108/BFJ-11-2016-0560
Yang, C.-Y., & Chang, T.-Y. (2011). Binomial real option pricing for restaurant menu analysis*. Cornell Hospitality Quarterly, 52(3), 273-282.
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