This paper focuses on the application of Digitalization tools in a traditional restaurant that still employs manual processes for order taking and sales control. The lack of digitalization prevents the use of data generated in daily operations, which limits information-based decision making. Through direct observation and manual data collection on sales, service times, and table turnover, the aim is to identify critical areas for improvement. The methodology to be used includes diagnosing the level of digital maturity, descriptive analysis of the data collection process, and the design of a basic point of sale (POS) system programmed in Python. The scope of this paper is limited to the design of the POS. Nevertheless, the analysis suggests that its implementation will enhance data collection, enabling valuable insights, improving sales tracking, and ultimately supporting data-driven decision-making. The article seeks to demonstrate that even in low-digitalization environments, it is possible to create value through progressive automation and the strategic use of operational information.
Velasco et al. (Thu,) studied this question.