Impactive AI's
Technology and Insights

Innovate the old distribution system and grow sustainably

Discover the 6 major demand forecasting models for 2025: from basic statistical approaches to advanced AI platforms. A comprehensive guide for non-experts to choose the right model for their business needs and improve decision-making.

Non-linear relationship between demand forecast accuracy and investment costs

What criteria should I choose?

Enterprise competitiveness determined by technological innovation capabilities

Global Businesses' Strategy to Deal with Supply Chain Crisis

A Strategic Choice for Continuous and Sustainable Cost Reduction

Stop Blaming Data for Forecast Failures

Technology That Quantifies Risk

A Strategic Approach to Overcoming Uncertainty

The 1% Difference That Improves Demand Forecasting Accuracy

Tech

Achieved an average forecasting accuracy of over 96% for Rebar, Copper, Hot-Rolled Coil, and Coking Coal.

Dramatic Results: 14-49% Accuracy Improvement Depending on Data Inclusion

Recently, the use of AI technology in the pharmaceutical industry has been notable. It has achieved results that have been proven by specific figures, such as a 55.1% reduction in inventory costs and a 22.6% reduction in out-of-stock rates. In particular, it is notable that it predicted the number of patients with an accuracy of 96.5% and based on this, it predicted the sales volume of pharmaceuticals.

How did the AI demand forecasting system solve the chronic problems of the manufacturing site? And what changes did the site workers experience? This article contains vivid examples of how AI technology solved the problems of demand forecasting and inventory management that the manufacturing industry was struggling with.

Inventory management in the manufacturing sector has become a key factor in determining a company's competitiveness. The inventory management costs of global manufacturing companies account for an average of 32% of total operating costs, a trend that has been on the rise for the past five years.

Interview with Researcher Yoon Jin-seop of IMPACTIVE AI Researcher

Interview with Eun-jin Yoon, IMPACTIVE AI Planner and Manager

Ending the long-standing concerns of manufacturing/distribution companies

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