AI Demand Forecasting "Deep Predictor" Sees Adoption Rate of "Operational Optimization Option" Exceed 90%

AI CROSS Inc. (Minato-ku, Tokyo, CEO Noriko Harada, hereinafter "AI CROSS") announced that the adoption rate of its "Operational Optimization Option" for its AI demand forecasting and operational service "Deep Predictor" has surpassed 90% among companies implementing "Deep Predictor." This option automatically converts forecast results into a format that can be directly utilized in business operations.

This option features a function that converts and outputs demand forecast results into formats tailored for various business scenarios such as ordering, shipping plans, and sales plans. Its design, which allows on-site staff to directly use AI demand forecast results for business decisions, has been highly praised.

Background

A common challenge many companies face when implementing AI demand forecasting for ordering, shipping adjustments, and sales planning is "operational adoption." Even if AI produces highly accurate forecasts, significant effort is required to convert these results into actual business decisions (such as calculating order quantities) by on-site staff, involving the reflection of company-specific logic, rules, and constraints. If this conversion process is not systematized or automated, it leads to operation dependent on individual staff skills and experience, hindering the realization of the operational efficiency that predictive AI should provide.

Conversely, attempting to resolve these issues through scratch development (developing uniquely from scratch without using off-the-shelf products) requires substantial cost and time, making it an unrealistic option for many companies.

AI CROSS has directly addressed this challenge since the initial development of "Deep Predictor," concretizing it as the "Operational Optimization Option."

Overview of the Operational Optimization Option

The "Operational Optimization Option" is a function that automatically converts and outputs the AI demand forecast results from "Deep Predictor" into "actionable business outputs."

Key Features

- Provides forecast results in formats tailored to each business scenario, such as ordering, shipping adjustments, and sales planning, allowing on-site staff to directly use AI outputs for business decisions.

- Automates business decisions beyond just forecasting, enhancing operational efficiency and on-site adoption rates.

- Incorporates internal decision logic, constraints, and proprietary information into forecast results, outputting them as actionable decisions. This simultaneously resolves the issue of operational dependency on individuals and reduces workload.

- Designed for on-site staff to operate independently, addressing the industry-wide challenge of operational adoption after AI implementation.

Image: Deep Predictor Project Screen

Image: Change in Ordering Workflow: "Typical AI Demand Forecasting Service" vs. "Deep Predictor + Operational Optimization Option"

Case Study: Implementation Effects at IKO International, Inc.

As a concrete example demonstrating the effectiveness of the "Operational Optimization Option," there is an implementation case at IKO International, Inc. (hereinafter "IKO International"), a US subsidiary of the Nippon Thompson Group.

This company sells bearings and precision equipment across five locations in the US, and the weekly inventory ordering process was managed manually by four staff members using Excel, posing a challenge due to its individualized nature.

When considering the implementation of "Deep Predictor," IKO International compared multiple AI demand forecasting products. The deciding factor for adoption was "the ability to complete the entire process, from demand forecasting to recommended order quantity calculation and post-processing based on business rules, within a single service." This is precisely the function performed by the "Operational Optimization Option."

Implementation Effects (Quantitative)

- Inventory ordering work time: Reduced from 3.8 hours per week for 4 workers to 1.4 hours (approximately 63% reduction).

- Annual time savings: Approximately 124.8 hours.

Implementation Effects (Qualitative)

- Eliminated variations in order quantities among workers and duplicate orders between locations, overcoming individual dependency.

- Facilitated easier handover of duties, leading to standardization and routinization of operations.

*Related Press Release: https://prtimes.jp/main/html/rd/p/000000277.000021834.html

AI CROSS's Concept of "AI Usable in the Field"

AI CROSS upholds the corporate philosophy of "Smart Work, Smart Life," supporting companies in improving operational efficiency and productivity through AI and technology. For "Deep Predictor," the company continues to develop and enhance its features with the core principle that its value is realized only when the forecast results directly contribute to on-site business decisions and operational adoption, not just by providing highly accurate forecasts.

The achievement of a 90% adoption rate for the "Operational Optimization Option" demonstrates the significant need for solving the "last mile" after forecasting and serves as a basis for AI CROSS to promote this function as a key differentiator.

Future Outlook

AI CROSS will continue to promote the adoption of AI in manufacturing, distribution, and other industries by enhancing the functionality of Deep Predictor and improving implementation support. The company aims to contribute to the business transformation of more companies by providing a solution that supports the entire decision-making process after forecasting, not just improving demand forecast accuracy.

[What is Deep Predictor?]

"Deep Predictor" is an AI demand forecasting and operational service designed with the concept of "Any forecast, easily by anyone." It is a service that supports high-precision forecasting and decision-making by utilizing company data, even for on-site staff without specialized knowledge.

Its feature is the ability to generate outputs directly linked to business operations, going beyond mere forecasting. It is designed as "AI that can be used immediately in the field."

Details here: https://aicross.co.jp/deep-predictor/category/demand/

[AI CROSS Inc. Company Overview]

Company Name: AI CROSS Inc. (Stock Code: 4476)

Location: Shirokane Trust Tower 20F, 4-3-1 Toranomon, Minato-ku, Tokyo

Representative: Noriko Harada, CEO

Established: March 2015

Business Activities: Guided by the philosophy of "Smart Work, Smart Life," the company supports corporate operational efficiency and productivity improvement through technologies such as SMS/RCS distribution and AI predictive analysis, and generative AI implementation support. Listed on the Tokyo Stock Exchange Growth Market in 2019.

Corporate Website: https://aicross.co.jp/

[Inquiries Regarding This Matter]

Company: AI CROSS Inc.

Public Relations: Abdul

TEL: 050-1745-3057

E-mail: pr@aicross.co.jp

AI CROSS Inc.

AI CROSS Inc. is a company that provides messaging services for corporations and AI-powered solutions. Its main services include the SMS distribution service "Zettai Reach! SMS," the RCS distribution platform "Zettai Reach! RCS," and various AI-based data analysis services such as "Deep Predictor," supporting corporate operational efficiency and smooth customer communication.