Acroquest Technology Co., Ltd. implemented an AI demand forecasting system for San-ai Oburi Co., Ltd. and achieved inventory optimization for 150 auto chemical-related products. This enabled the forecast error to be kept within 20%, and succeeded in reducing excess costs and lost sales opportunities.
In recent years, as inventory management has become increasingly important in the manufacturing industry, Acroquest has strengthened its provision of demand forecasting solutions that utilize AI technology as part of its support for promoting digital transformation in the manufacturing industry. In this project, we resolved the inventory management issues that San-Ai Obri had by building an AI demand forecasting system on AWS.
San-ai Oburi is a trading company engaged in energy-related businesses such as the petroleum business, while in the chemical business it manufactures and sells auto chemical-related products and anti-corrosion and anti-fungal products.
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Previously, SAN-AI OBURY had been manually forecasting product demand and creating sales plans, but this had resulted in errors of up to 30%, as well as issues such as excess costs due to excess product inventory and lost sales opportunities due to stock shortages.
To address these challenges, Acroquest used Amazon SageMaker Canvas to build a forecasting model that took into account seasonal and environmental factors, thereby reducing forecast error to within 20% and optimizing inventory.
Furthermore, by automating form output and integrating with existing business flows, the system reduces the amount of time sales representatives spend on administrative tasks, freeing up time for sales activities and making production plans more efficient, thereby contributing to improved productivity across the business.
SOURCE: PRTimes
