Helping Restaurants Organize Menus: A Pizza Case Study
When I step into a restaurant, I can’t help but analyze the menu and cooking processes. For me, a good restaurant should offer a vast array of options made from fresh, high-quality ingredients, and served quickly. However, running a restaurant is no small feat, as it requires excellent organizational skills, efficient delivery services, and the ability to serve multiple customers simultaneously. Among these challenges, menu organization is one of the most important.
Most restaurants offer either traditional or fancy dishes to cater to their customers’ needs. The former prioritizes quantity, while the latter emphasizes quality. Regardless of the approach, restaurants must ensure that they have the necessary ingredients to satisfy their customers’ cravings. One dish that has become a worldwide favorite is pizza, a versatile and beloved Italian creation that has given rise to numerous variations and flavors.
In Brazil, pizza has become a staple food, with numerous pizzerias in every city serving delicious meals that bring people together. However, with so many options, choosing the perfect pizza can be challenging. To help with this, I took a sample menu from a local pizzeria and converted it into a non-structured JSON file. I then used the Eule library, which I developed in Python, to find common ingredients and similarities between the pizzas. You can find the results of my research in this repository: https://github.com/alloyha/experiments/blob/main/data/pizzayolo/pizza-ingredients.ipynb.
By leveraging my expertise and knowledge, I have developed a method to help restaurants organize their menus, ensuring that they offer a wide range of tasty dishes while minimizing costs and optimizing the use of ingredients. So if you’re a restaurant owner looking to improve your menu or a pizza lover trying to choose the perfect pie, don’t hesitate to explore the resources I have developed.
