Restaurants store management based on demand forecasting
Takashi Tanizaki, Tomohiro Hoshino, Takeshi Shimmura, Takeshi Takenaka
Abstract
In this paper, restaurants store management based on demand forecasting is proposed. The restaurant service industry has low productivity due to the simultaneity of service goods. In order to solve such problems, we are researching how to manage restaurant stores such as employee placement, food material ordering, etc., based on highly accurate demand forecasting by machine learning with internal data such as POS data and external data exiting in ubiquitous such as weather and events. In this paper, we discuss the forecasting results of customer order quantity and shop inventory order quantity of draft beer using forecasting method with machine learning for restaurant chain R.