How Demand Forecast Errors Affect Your Bottom Line

Demand forecasting guide based on the characteristics of each store

Forecasting Maturity Through the T.I.M.E. Framework

How the Fashion Industry Survives in an Era of Compressed Trend Cycles

The Chain Reaction That Starts When You Miss Your Reorder Window

3 Essentials of Demand Forecasting Operations

The Critical Pillar of Business Operations and Strategic Decision-Making

Proposal Writing Strategies to Maximize Your Selection Odds

A Practitioner's Guide to Steel & Construction Demand Forecasting

A Practitioner's Guide to Fashion & Beauty Demand Forecasting

Practice Guide for Demand Forecast by Industry

Practice Guide for Demand Forecast by Industry

If you don't want to be in bad stock, you can't sell it well

What Companies Miss When Searching for Better AI Models

From Unpredictable to Actionable: AI and Black Swan Events

The core competencies that a company should have now

W Company’s New Product Demand Forecasting Case Achieving 94–95% Accuracy in Top-Selling Segments Without Historical Sales Data

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.

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.

An interview with a Deepflow service planner

An Interview with Taewon Yoo, Director at ImpactiveAI

Interview with Jeonghwan Yang, ImpactivAI Developer

Interview with CTO Jeong Hee-won

Interview with Sales Team Director Min Byung-joon

Interview with COO Park Jung-hyun

Interview with Jeong Doo-hee, CEO of IMPACTIVE AI

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