Last Updated： Aggregation Period:Jul 08, 2026～Aug 04, 2026
This ranking is based on the number of page views on our site.
Last Updated： Aggregation Period:Jul 08, 2026～Aug 04, 2026
This ranking is based on the number of page views on our site.
Last Updated： Aggregation Period:Jul 08, 2026～Aug 04, 2026
This ranking is based on the number of page views on our site.
1～6 item / All 6 items
It is possible to realize a unique demand forecasting and sales planning system in a short period and at low cost.
It is possible to build a demand forecasting model tailored to your business, taking into account factors such as grouping of product categories, advertising, seasonality, and other events.
A demand forecasting system that allows small businesses to understand 'the likelihood of sales' and 'the necessary inventory levels' is available for free.
Demand Forecasting System CustomForecast It has been developed as an affordable and easy-to-use system to contribute to the sound management of small and medium-sized enterprises.
You can understand the criteria for decision-making regarding the introduction, from the basics of the demand forecasting system to how to choose one.
Demand forecasting systems support the optimization of inventory management, production planning, and marketing strategies by predicting future demand based on past data. In particular, those utilizing AI are becoming essential tools for many companies due to their high accuracy and rapid analysis capabilities. This article will provide a detailed explanation of the fundamentals of demand forecasting systems, specific use cases, the benefits of implementation, and recommended systems. *For more detailed content of the blog, please refer to the related links. For more information, you can download the PDF or feel free to contact us.*
We have a track record in forecasting demand, inventory, and procurement across various industries, as well as in the used car market!
"AIME-PRECOM" is a solution that analyzes past data and various related time series data to identify trends and patterns, allowing for the prediction of future realizations and outcomes. It has a proven track record in various industries such as manufacturing, logistics, retail, and food service, providing forecasts related to demand, inventory, and procurement, as well as predictions for the used car market. Additionally, it is utilized for residual value predictions for used car dealerships and leasing companies, as well as for credit and value assessments and asset management in banks. 【Features】 ■ Analyzes past data and various related time series data ■ Identifies trends and patterns ■ Predicts future realizations and outcomes *For more details, please refer to the PDF materials or feel free to contact us.
Explaining data design and machine learning that supports order optimization.
From intuition and experience-based ordering to data-driven demand forecasting. How to create an AI system that predicts the "probability of selling" at the product level, including what data to use, what models to apply, and how to operate it. This article explains the key points of implementing and operating demand forecasting that combines sales performance, events, weather, and market attributes. For more details, please refer to the technical column in the related links.
Utilization of IT to improve demand forecasting accuracy and enhance operational efficiency.
In the textile and apparel industry, demand forecasting that responds to market trend changes and seasonal fluctuations is crucial for optimizing inventory management and production planning. Particularly in the apparel sector, where demand variability is significant, accurate demand forecasting is essential. Uncertain demand forecasts can lead to excess inventory or stockouts, resulting in lost opportunities. Our IT utilization support enables highly accurate demand forecasting based on data, contributing to solving these challenges. 【Utilization Scenarios】 - Demand forecasting based on trend analysis - Integrated analysis of past sales data and market trends - Development of forecasting models considering seasonal fluctuations and events - Reflection in inventory optimization and production planning 【Effects of Implementation】 - Reduction of inventory loss - Decrease in lost opportunities - Improvement in production efficiency - Enhancement of customer satisfaction
