Approach to improvement of restaurant management using machine language

Abstract

The service industry is an important industry that accounts for about 70% of Japan's GDP. However, since the labor productivity of the service industry is lower than that of the manufacturing industry, productivity improvement in the service industry is the country's most important policy issue. In order to solve such problems, we research support method for sophisticated store management based on highly accurate future prediction for face-to-face service industry. As part of it, we research prediction methods using external data existing in the ubiquitous environment such as weather, events and internal data such as POS data etc. In this paper, we describe comparison of forecasting methods and material ordering for dishes based on machine learning.