#Japan #Tokyo #AI CROSS #Deep Predictor #ASAHI Industries

Revolutionizing Demand Forecasting in Manufacturing

AI CROSS, a technology company based in Minato, Tokyo, has launched its AI demand forecasting service, "Deep Predictor", in collaboration with ASAHI Industries, a manufacturer specializing in exterior materials located in Toda City, Saitama. This strategic partnership aims to enhance ASAHI's inventory management and streamline their operational processes.

Background of the Partnership

Founded in 1976, ASAHI Industries has been a key player in Japan's construction materials sector, providing insulation materials and decorative exterior products for various projects, from residential buildings to large-scale industrial complexes. Over the years, ASAHI has established a strong domestic presence, with offices and factories across Japan as well as a manufacturing operation in Thailand.

In the manufacturing sector, one common management challenge is balancing inventory levels to prevent stockouts while avoiding overstocking. A report from the Ministry of Economy, Trade and Industry highlights the importance of transitioning from experience-based decision making to data-driven approaches. Despite this, a study by PwC Consulting indicates that only 25% of Japanese companies utilize AI within their supply chains, emphasizing the ongoing struggle to incorporate AI in traditionally human-centric processes.

Recognizing these challenges, ASAHI Industries decided to adopt the "Deep Predictor" service to re-engineer their inventory management processes that had been overly reliant on individual judgement. With this implementation starting in May 2026 across their headquarters and Osaka locations, ASAHI aims to enhance demand forecasting and order processes significantly.

Challenges Faced Before Implementation

In a recent statement, Sato, the Executive Officer of ASAHI Industries, discussed the challenges they faced prior to the integration of "Deep Predictor". He noted that the company's demand planning had been managed by a single employee, which often led to inefficiencies. The order decisions depended heavily on individual assessments, making the process prone to variations. Despite maintaining a relatively large stock of approximately 1,055 items, ASAHI experienced stockouts of about 20 items each month, indicating insufficient predictive capability in their operations.

Why "Deep Predictor"?

The selection of "Deep Predictor" stemmed from ASAHI's desire for a tool that could incorporate a wide range of external variables—estimated at around 7,000—that could influence their business. They found the comprehensive approach of the service appealing, as it moves beyond basic demand forecasting to offer actionable insights into order quantities. ASAHI also noted that AI CROSS demonstrated a high level of understanding during preliminary discussions, which built trust in their collaboration.

Expected Outcomes and Future Prospects

Sato expressed hopes that the new system would significantly decrease stockouts and reduce the time spent on order management. Furthermore, ASAHI aims to standardize their internal decision-making processes related to ordering and improve inventory management sophistication. They also intend to identify critical external information that influences industry trends.

Features of "Deep Predictor"

"Deep Predictor" is an innovative AI demand forecasting and operation service from AI CROSS, leveraging historical shipment, order, and inventory data to generate continuous demand predictions. Key features include:

1. Comprehensive Support: Not only does it provide demand forecasting models, but it also assists in calculating order quantities and conducting post-processing following the company’s workflow.
2. Balancing Stock Levels: The service quantitatively evaluates stockout risks against inventory burdens, enabling optimal order quantity recommendations tailored to item characteristics.
3. Data-driven Order Justification: It visualizes the data supporting forecasts and order numbers, moving away from subjective decision-making to a standardized, data-driven approach.
4. Adaptation to Business Operations: Designed to integrate with existing workflows and core systems, minimizing the operational burden while gradually expanding the service’s application scope.

Looking Ahead

By implementing "Deep Predictor", AI CROSS is committed to supporting ASAHI Industries in the pursuit of more efficient order management and the alleviation of reliance on individual decision-making. The collaboration will involve ongoing evaluations aimed at refining order quantity insights and progressing into a more sophisticated demand prediction regimen.

The roadmap ahead will focus on using the system effectively in its initial sites and expediting potential expansions in both product range and operational sites as success metrics are established. Ultimately, the partnership is designed to elevate ASAHI’s decision-making processes from experience-based to transparent, data-driven methodologies, thereby boosting their competitive edge in the market.

With their motto of supporting easy access to advanced forecasting regardless of a user's expertise, "Deep Predictor" aims to transform how teams approach demand planning in manufacturing sectors, delivering substantial efficiency gains and enhancing overall productivity.

Conclusion

In summary, the alliance between AI CROSS and ASAHI Industries signifies a critical shift towards utilizing AI in manufacturing, with the potential to reshape demand forecasting methodologies across the industry, thus reinforcing the need for transformation in decision-making processes.