# Japan's largest family-restaurant group announced it would finish putting 3,000 floor-service robots into about 2,100 of its roughly 2,980 domestic restaurants on 27 December 2022

Page: https://flyvolo.ai/en/changes/ev-20221221-waiter-2
Date: 2022-12-21 · Stage: Deployment
Can this record move a task judgement? yes
Occupation: https://flyvolo.ai/en/careers/waiter

## Scope

The operator's own release, from a company listed on the Tokyo Stock Exchange Prime market. It states that floor-service robot deployment began in August 2021 and that 3,000 units would be in place across about 2,100 stores by 27 December 2022 — the release is dated the 21st, so the completion date it names is the company's own announced schedule rather than a fact the document establishes. The store breakdown is given: Gusto 1,251, Bamiyan 354, Shabu-yo 271, Jonathan 187, Uoyaro 14, Steak Gusto 3, Yumean 2, against a stated domestic group total of 2,982 stores. The reason this belongs on this page is the effects the company chose to report, and the ones it did not. For Gusto it names improved table turnover at the lunch peak, reduced time to finish clearing a table, and fewer steps walked, alongside a customer survey at 67 stores with 2,513 responses in which nine in ten chose satisfied or very satisfied. It reports no headcount, no hours, and no change to staffing of any kind. It also records that the company sent dedicated robot instructors to every store and iterated on staff and customer feedback, which is a cost of deployment that a shorter account leaves out. One operator, one country, one format — table-service family restaurants.

## Source

- 株式会社すかいらーくホールディングス(東証プライム 3197)——《約2,100店に3,000台のロボット導入完了》 — https://corp.skylark.co.jp/Portals/0/images/news/press_release/2022/20221221_Robot.pdf (primary source)

## What this means

Three thousand robots scheduled into roughly seven in ten of the group's domestic restaurants, and the operator's own account of what changed is that tables turn faster at the lunch peak, clearing finishes sooner, and staff walk fewer steps. The carrying is what moved. The company also sent a dedicated instructor to every store and kept revising the service around staff feedback, which is the part of a rollout that rarely gets reported.

## What it does not show yet

It reports no headcount, no hours, and no staffing change of any kind — and reading fewer steps walked as fewer staff is exactly the inference this site exists to stop. Nor does it separate the robot from everything else that changed in those restaurants over sixteen months. One operator, one country, one format; a robot that carries plates between a kitchen and a table is not evidence about a restaurant where the floor staff take the order, read the room and handle the complaint.

## How to verify it yourself

Count what the machine cannot do in the room you actually work in. It carries along a fixed path; it does not decide which table needs attention first, notice a customer is unhappy before they say so, or handle the moment something is spilled on someone. If your shift is mostly carrying, this deployment is about you. If it is mostly the other three, the same machine changes your walking distance and not your job.


More: https://flyvolo.ai/llms.txt