Creating a Dynamic Menu Engineering Model for Food and Beverage Operations at Company X
Kiiski, Riina (2023)
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202305109209
https://urn.fi/URN:NBN:fi:amk-202305109209
Tiivistelmä
Menu engineering is a discipline where individual menu portions, can be followed up individually on profit level by examining selling prices, raw material costs and quantities sold.
This project-based bachelor thesis is about creating a dynamic menu engineering model for the commissioning company. The Company X operates multiple restaurants and bars in hotels in Finland but is part of an international chain. The overall objective for this thesis is to create such a model for the Company X that they are able to use it to implement a tool within their current systems environment to increase the profitability of their restaurants through menu engineering strategies.
Traditionally, in the hospitality industry it has been difficult to follow up and predict profitability on menu items and menu combinations. The three global issues, covid-19, high inflation, and the war in Ukraine, have emphasised the importance of being able to react quickly and become fur-ther proactive in the approach towards raw material costs and customer behaviours. The Company X has recognised a potential to increase profitability with dynamic menu engineering tool in their à la carte restaurants and bars.
The theoretical framework was based upon the theory of menu engineering, data collection and data analysis as these elements are required for dynamic menu engineering model. There was a heavy emphasis on the qualitative methods, such as interviews and qualitative survey, as well as use of secondary data to support the thesis. The survey also had a quantitative part to find out current user statistics of menu engineering. The author also used a considerable time on desktop research to find out about the quality of the data in different systems and tools. All data has been collected during the spring 2023.
The results showed that currently there are many manual processes in place and the data is very siloed and hard to get to. The process to update recipes and menu prices is very slow and this has caused the recipe calculations to be missing or wrong. The menu engineering model to work, and it to become dynamic, these manual processes need to be automated and optimised and siloes need to be broken. The author has listed the challenges that were found during the research and recommendations for those issues.
The commissioning company has already started to make steps to address the issues found. To take this project further, the Company X needs firstly to build and implement the tool once the data flow issues have been resolved. And if they would like to explore it even further, there are possibilities even for further automation and even menu planning AI can be included to the future vision.
This project-based bachelor thesis is about creating a dynamic menu engineering model for the commissioning company. The Company X operates multiple restaurants and bars in hotels in Finland but is part of an international chain. The overall objective for this thesis is to create such a model for the Company X that they are able to use it to implement a tool within their current systems environment to increase the profitability of their restaurants through menu engineering strategies.
Traditionally, in the hospitality industry it has been difficult to follow up and predict profitability on menu items and menu combinations. The three global issues, covid-19, high inflation, and the war in Ukraine, have emphasised the importance of being able to react quickly and become fur-ther proactive in the approach towards raw material costs and customer behaviours. The Company X has recognised a potential to increase profitability with dynamic menu engineering tool in their à la carte restaurants and bars.
The theoretical framework was based upon the theory of menu engineering, data collection and data analysis as these elements are required for dynamic menu engineering model. There was a heavy emphasis on the qualitative methods, such as interviews and qualitative survey, as well as use of secondary data to support the thesis. The survey also had a quantitative part to find out current user statistics of menu engineering. The author also used a considerable time on desktop research to find out about the quality of the data in different systems and tools. All data has been collected during the spring 2023.
The results showed that currently there are many manual processes in place and the data is very siloed and hard to get to. The process to update recipes and menu prices is very slow and this has caused the recipe calculations to be missing or wrong. The menu engineering model to work, and it to become dynamic, these manual processes need to be automated and optimised and siloes need to be broken. The author has listed the challenges that were found during the research and recommendations for those issues.
The commissioning company has already started to make steps to address the issues found. To take this project further, the Company X needs firstly to build and implement the tool once the data flow issues have been resolved. And if they would like to explore it even further, there are possibilities even for further automation and even menu planning AI can be included to the future vision.