A Case Study on Application of the Menu Engineering Technique in Government Offices Contract Foodservice

The purpose of this study was to analyze and evaluate the menu served in government offices foodservice by using Kasavana & Smith's Menu-Engineering. Sales and food costs were collected from the daily sales reports for a year from Jan 2 to Dec 31 in 2007. Calculation for menu analysis and customer's data were done by computer using the MS 2003 Excel spreadsheet program and SPSS 12.0 package program. Menu mix% (MM%) and unit contribution margin were used as variables by Kasavana & Smith. Four possible classifications by Menu-Engineering technique were turned out as 'STAR', 'PLOWHORSE', 'PUZZLE', 'DOG'. The main menus served during a year were 128 dishes and about 141 peoples visited this restaurant daily. The mean age of the men was 44.1 +/- 6.3, women were 32.7 +/- 6.4 and showed that was statistically higher than that of women (p < .0001). The rates of STAR menus were 'Western style (75.0%)', 'guk/tang-ryu (48.1%)', 'jjigae/ jeongol-ryu (23.1%)', 'bap-ryu (17.2%)' in sequence. There were no STAR menus in gui/jorim/jjim-ryu. PLOWHORSE menus were 'gui-ryu (75.0%)', 'guk/tang-ryu (29.6%)', 'bap-ryu (27.6%)' in sequence. There were no PUZZLE or DOG menus in 'jjigae/jeongol-ryu'. PUZZLE menus were 'jorim/jjim-ryu and Myeonryu (each 33.3%)', 'bap-ryu (31.0%)' in sequence. PUZZLE menus were a lots of 'Chinese food (75.0%)' and 'myeonryu (55.6%)'. This study provides the basic data based on regularly menu analysis method applied the scientific menu analysis techniques in government offices food services, I'd like to suggest that the menu management must be done based on the necessity and result of menu analysis according to the seasonal and middle, long-term plans.

Using Activity-Based Cost in Menu Engineering for Restaurant Menu Analysis / 대한지역사회영양학회지

The purposes of this study were to investigate methods of applying activity-based cost to menu engineering and to examine the feasibility. A total of 6 menu items of XYZ restaurant in Seoul were selected and the ledger of September 2005 was used for menu analysis. The menu mix percent of beef sirloin steak (61.95%) and beef tenderloin steak (17.13%) were labeled as high, whereas BBQ pork ribs (4.94%), salmon fillet (2.66%), seafood platter (5.77%), and teriyaki chicken (7.56%) showed low menu mix percent. In addition, the contribution margin for BBQ pork ribs (29,000 won), salmon fillet (25,810 won), seafood platter (22,400 won), and teriyaki chicken (22,000 won) were higher than the average contribution margin (21,957 won), and those for beef sirloin steak (21,200 won) and beef tenderloin steak (21,900 won) were lower than average. When popularity and contribution margin were applied in menu engineering, BBQ pork ribs, salmon fillet, seafood platter and teriyaki chicken were classified as puzzles and beef tenderloin steak and beef sirloin steak as plowhorses. Menu engineering using popularity and operating profit, which was calculated from activity-based cost, also gave the same results, whereas the additional label for activity cost placed BBQ pork ribs and salmon fillet in the brain teaser category. Ranking analysis on variables estimating menu profitability using Spearman's rho revealed that there were no significant correlation between variables, which means the estimation of menu item profitability could differ by methods of analysis. With these results, it was concluded that activity-based cost would help to establish more detailed marketing strategy for a restaurant.

What's the Best Technique on Menu Analysis?

The purposes of this study were to : (a) analyze the menus of food service operations using the menu analysis techniques of Kasavana & Smith, Miller, Merricks & Jones, Pavesic and Uman, (b) closely examine the characteristics of the five analysis techniques. Calculations for the menu analysis were done by computer using the MS 2000 Excel spreadsheet program. Menu mix% and unit contribution margin were used as variables by Kasavana & Smith, sales volume and food cost% by Miller, sales volume and cash contribution by Merrick & Jones, weighted contribution margin and food cost% by Pavesic, and total cash contribution and unit contribution margin by Uman. In each case, a four-cell matrix was created, and menu items were located in each according they achieved high or low scores with respect to two variables. Items that scored favorably on both variables were rated in the top category (e.g., star, prime, signature, group A, winner) and those that scored below average on both were rated in the lowest category (e.g., dog, problem, loser, group D, loser). While the 3 methods of Kasavana & Smith, Miller, Merrick & Jones focus on customers' viewpoints, the others consider the managers' viewpoints. Therefore, it is more likely to be desirable for decision-making on menus if the menu analysis technique chosen is suited to its purpose.

Development and Application of Menu Engineering Technique for University Residence Hall Foodservice / 대한지역사회영양학회지

This article aims to summarize the development and application of menu engineering technique, 'Menu Engineering Modified by Preference (MEMP)'. The site selected for this project was a foodservice operation in Yonsei University residence hall. Sales and food costs data were collected from the daily sales reports for 1 month, and the survey of food preference was conducted during May, 1999. Statistical data analysis was completed using the SAS/Win 6.12 for descriptive analysis. The calculation for menu analysis were carried out with MS 2000 Excel spreadsheet program. This MEMP technique developed had 6 category criteria and 2 dimensions of the contribution margin (CM) and the menu mix modified% (MMM%). The MMM% was calculated by the sales volumes and also weighted by food preference. The CM and MMM% for each item were compared with a mean menu CM as well as a 70% rule. Four possible classifications by MEMP were turned out as 'STAR', 'PLOWHORSE', 'PUZZLE', 'DOG'. 'STAR' items were the most popular and profitable items and required to maintain rigid specifications for quality. The decision actions for 'PLOWHORSE' menu items which were relatively popular, but yield a low menu average CM included combining a plowhorse item with lower cost products and reducing the frequency of serving or serving size. There was a need for 'PUZZLE' items to be changed in the menu combination, improve recipe, and promote menu. The last 'DOG' items were desired to be deleted. This study demonstrates that menu information can be interpreted more easily with MEMP. The use of MEMP is therefore an effective way to improve management decisions about menu of university residence hall foodservice.