English 
Japanese 
The time it takes to confirm shifts has been reduced from one week to two days. Pachinko parlors have reformed their operations by using data analysis as a tool for all employees.
Nishinomiya Moco Co., Ltd.
Issues before implementation
- It took a week from consolidating shifts to finalizing them, and each shift required 4-5 hours of work.
- Detailed data such as the number of balls dispensed was limited to specific devices, making it difficult to share with on-site staff in a timely manner.
- There were no IT experts in the company, and there were technical barriers to autonomously systematizing and improving business operations.
Effects after implementation
- By using Gemini to build GAS, we were able to reduce the amount of work required and shorten the time it took to confirm shifts to two days.
- By using AI to share and utilize data across the company, the limitations of specific devices were eliminated, and the quality of meetings was improved through instant analysis.
- With AI as a thought partner, we fostered a culture where inexperienced employees were involved in system construction themselves.
table of contents
Company Introduction
Nishinomiya Moco is a family business that has been running the "amusement industry" together with the local community for about 40 years since its founding in Nishinomiya City, Hyogo Prefecture in 1986. Founded by my grandfather, passed down to my father and then to me, the third generation, it is not just the management of a pachinko parlor, but also a strong sense of mission to "protect the local community."
Our store is more than just a place for competition; it is also an essential "everyday social gathering place" for local residents. Even if people don't know each other's contact information, there is a bond there where "if I come here I'll meet that person and see their cheerful face." In order to maintain and further expand this "community bond," we continue to pursue a "new store format" that combines the warmth of a traditional family business with the latest technology.
Issues before introducing generative AI
"Shifts" and "analysis of numbers" were the biggest burdens on on-site man-hours.
Staff shift management was an analog method, where requests were manually entered into Excel and any remaining slots were individually requested. In addition to the heavy workload, it took about a week from the initial request to all responses and the final confirmation, slowing down the organization.
Furthermore, machine data analysis, which is essential for sales, was only accessible to those with specialized computer skills. Extremely detailed figures such as "how many shots were inserted and how many were dispensed" for each machine could only be viewed on dedicated terminals, and measuring the effectiveness of events and other such data required time-consuming manual calculations, making it difficult to share and utilize information across the company.
Furthermore, the lack of in-house personnel with IT expertise was a major obstacle to improvement. Systemizing complex shift adjustments and data analysis on one's own was highly difficult, and technical limitations that made it impossible to do so even if the company wanted to had been an issue for many years.
Effects after generative AI introduction training
After the training, we were able to build a powerful in-house system with AI as our partner.
First, they introduced shift management, which uses GAS to automatically process requests collected via Google Forms. This dramatically reduced the manual work that previously took 4-5 hours for staff, as well as the waiting time required to communicate with staff. The time required to confirm shifts was shortened to just 2 days. In addition, by consolidating communications on Slack and introducing objective allocation rules using AI, they have evolved into a more transparent operation that eliminates personal dependency.
In terms of data analysis, by having AI learn past hall data, we have created an environment where any on-site employee can utilize the figures. The AI can instantly answer the document reading and analysis tasks that previously took 5 to 10 minutes. As a result, meetings can now go beyond the task of "producing figures" and can involve deeper discussions on "what to do next based on the analysis results."
There has also been a major change in awareness within the organization. With the support of AI, employees have gained confidence that they can improve their work processes on their own, and this has produced even greater-than-expected results, such as bottom-up improvements in digital literacy across the entire organization.
Future outlook
Currently, we are focusing on analysis and administrative efficiency, but in the future we plan to focus on using AI in the creative field. We aim to use the latest AI to in-house produce sophisticated industry-specific announcements and images for social media, and to create a system where one person can handle the design of multiple stores.
We view AI as a partner that brings out the sensibilities of our staff, and we hope to continue pursuing amusement business management that combines the warmth of a family business with the latest technology.
