Vending

Japan rail stations to deploy AI management tool across 6,000 vending machines

Image courtesy of Hivery.

December 16, 2020

Hivery, an Australia based artificial intelligence provider, will roll out its AI driven vending machine management solution to 6,000 machines across East Japan Railway's train stations, according to a press release.

The two companies have been collaborating since 2017, leveraging Hivery's AI technology to optimize product assortment and column space for individual vending machines in Japan. Validated results from proof of concepts increased sales by 5.27％overall, up to a maximum of more than 50%, as well as reducing replenishment trips and improving operational productivity.

Hivery Enhance enabled JR East Water Business to streamline operations and reduce replenishment trips by automatically recommending the optimal product assortment and quantity for the vending machines.

Hivery Enhance leverages the power of AI and JR East Water Business' point of sales data, to automatically determine which products need to be stocked in which vending machine, as well as the optimal timing to swap products for individual machines. This enables the operator to efficiently make the right product assortment choices that will lead to a profitable outcome.

Benefits include:

• Select products that are likely to sell well. By analyzing the vast amount of sales data from the full fleet of vending machines, it identifies patterns in the sales data and identifies products that are likely to sell well in any particular location.
• Optimize product assortment. By understanding the demand for individual products and the effects of cannibalization of demand between products in each location, it can determine which products should be inserted and which should be taken out, to lead to the optimal outcome.
• Reduce replenishment trips. From the demand forecasts of products in any location, it can calculate the number of days before each product is likely to go out of stock and recommend the optimal quantity and column allocation to maximize the time between replenishment trips, thereby reducing labor costs.
• Optimize a group of vending machines. Rather than only focusing on individual vending machines, it can also assess a group of banked vending machines in the same area at the same time, and optimize the products for the entire area as if it were one large vending machine.