Fujitsu is delivering an AI demand forecast service to Toridoll noodle shops throughout Japan.

The service aims to improve operational efficiency, reduce food loss, and realise efficient energy management at 823 Marugame udon shops.

This should let Toridoll accurately forecast the customer numbers and sales by day and time for each shop, based on weather and PoS data.

Fujitsu will help digitally transform operations for shop managers, optimising complex manual processes including the ordering of products and food quantity planning to deliver more overall efficiency, help reduce food loss, and realise efficient energy management through the optimisation of staff allocation and air conditioning in shops.

Moving forward, Fujitsu and Toridoll will continue to leverage AI and other technologies, as well as various data and business know-how, to promote the digital transformation of Toridoll restaurants globally.

In November last year, Toridoll formulated its DX Vision 2028 to transform into a global food company. In 2021, Toridoll started testing the effectiveness of an AI demand forecast service for predicting the customer numbers and sales of its Marugame udon brand by shop, day and time, to realise automated shop management using AI demand forecasts and energy management using IoT.

Toridoll decided to deploy this at all of its 823 shops in Japan.

The AI forecast service is based on Fujitsu’s AI demand prediction offering, which enables users to predict future customer and sales numbers with high accuracy based on various data held by companies, including PoS data, sales calendars and sales promotion campaigns, as well as weather data.

Toridoll and Fujitsu will use the AI demand prediction service to automate and improve work schedules and optimise order processes, food quantity planning and energy use.

The operational data management and analytics demand forecasting SaaS forms the base of the AI forecast service and provides stable and accurate demand forecasting using AI and machine-learning technologies.

Using a Fujitsu Research model for dynamic ensemble forecasting that leverages AI and machine-learning technology to imitate human thought processes to make predictions from data characteristics, Fujitsu realised an optimal combination of multiple demand prediction models through automatic tuning. In this way, the service can offer stable and accurate forecasts without the need to select from different forecasting methods by leveraging a learning model that accurately captures the characteristics of individual prediction objects that change according to various factors including periodicities, external factors and trends.

As Fujitsu offers the forecast service via the cloud, required forecast data can be easily linked with various SaaS applications and APIs running in the cloud, thus supporting the use of forecast data in various planning operations including order placement, production planning and work scheduling.

Toridoll says it will continue to offer further new food experiences by combining the two principles of developing quickly and efficiently and taking time and effort. Fujitsu will continue to promote Digital Shifts, one of its key focus areas under its global business brand Fujitsu Uvance, to realise data-driven management and an agile shift to the new normal.

Fujitsu will present this project on its stand at the Retailtech Japan event in Tokyo from February 28 to March 3.