Impactive AI's
Technology and Insights

Practical Guide to Achieving Inventory Optimization and Cost Reduction

Complex Correlations Among Seemingly Unrelated Factors

Strategic Guide for both practitioners and decision makers to know

The dilemma of the distribution industry, now we can overcome it

Glamorous promises, harsh realities, hidden barriers to introduction

How can we trust demand forecasts?

Key elements to be reviewed before introducing the system

Various data augmentation techniques that can be applied directly to practice

The moment when complex production data comes into view

A strategy for developing new products that compete on data

From Microsoft Dynamics 365 to Oracle Cloud Supply Chain

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.

Successful case of introducing AI inventory management in the manufacturing industry The inventory management method that relies on past experience and intuition is no longer competitive. The AI-based inventory management system can accurately predict demand by analyzing vast amounts of data in real time and automatically calculate the optimal inventory level.

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

Ending the long-standing concerns of manufacturing/distribution companies

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IT Chosun

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