Restaurant Analytics


  • Nico De Guzman
  • Christian Bobier
  • Jerald Clarete
  • Jona Belen
  • Oliver Doctor
  • Rosuaro Villalon Jr.


agile methodology, restaurant analytics


Restaurant analytics is a part of the module that can modify the rating of the transactions of restaurants; it can help monitor the sales of the restaurant. Restaurant analytics is the combination of all raw data that is turned into easy-to-use insights that help you make better business decisions. It also creates standardized scorecards to help the restaurant predict sales and profitability by using data sources such as point-of-sale transactions and survey results. To create an excellent system for the company that can produce a quick and reliable transaction, the proponents used the agile method, which uses incremental, iterative work sequences that are commonly known as sprints. Agile uses a timeframe for each sprint; the researchers used 2 weeks as the timeframe to finish sprints. It has a series of sprints; every sprint has multiple tasks with restricted time duration to develop a functional system. The proposed system was tested and successfully launched. Our submodule is the one that provides a graphical report to easily understand the daily, weekly, and monthly sales data by given the point-of-sales data. Restaurant analytics identified the profit margin by using the food and beverages costing that the restaurant owner can monitor and identify their profit daily, weekly, and monthly loss. Our system also has two types of payment, namely, credit card and cash. This system will monitor how many customers pay using the two types of payment. The system provides the overall dashboard from the restaurant to help the owner for the easiest and fastest way to transact. In our system, the owner can view the total product sales.



How to Cite

De Guzman, N. ., Bobier, C. ., Clarete, J. ., Belen, J. ., Doctor, O. ., & Villalon Jr., R. . (2020). Restaurant Analytics. Ascendens Asia Singapore – Bestlink College of the Philippines Journal of Multidisciplinary Research, 2(1). Retrieved from