Forecast Manufacturing Uncertainty in Customer Orders and Raw Material Prices
From unpredictable customer orders to constantly fluctuating raw material prices, Deepflow AI solves the critical forecasting challenges in manufacturing operations that have traditionally relied on manual judgment and intuition.
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Mission
Manufacturing Operations Where
Forecasting Errors Erode Profitability
Manufacturers today face three simultaneous sources of uncertainty: unpredictable customer orders, complex BOM (Bill of Materials) structures, and volatile raw material prices.

Demand forecasting methods that rely on planner experience and spreadsheets typically achieve only 30–50% accuracy, often resulting in delayed customer deliveries or excessive inventory costs. As forecasting errors accumulate, manufacturing costs rise and operating margins continue to shrink.
Case

From battery cell manufacturers to material suppliers, Deepflow solves forecasting challenges across the entire value chain.

By combining order volume forecasting powered by OEM demand as a leading indicator with raw materials price trend forecasting, Deepflow enhances decision-making capabilities in complex and rapidly changing market environments.
글로벌 매크로 지표 기반
원자재 가격 예측
환율, 원자재 지수, 글로벌 경제 지표를 분석해 철광석,
비철금속 등 핵심 원자재의 미래 가격을 예측
철강·구리·니켈 등 변동폭과 수요가 큰 핵심 소재 선제 예측
거시 경제 데이터·수요·공급 데이터를 다각도로 학습
최적 구매 타이밍 확보로 제조 원가 상승 리스크 최소화
글로벌 매크로 지표 기반
원자재 가격 예측
환율, 원자재 지수, 글로벌 경제 지표를 분석해 철광석,
비철금속 등 핵심 원자재의 미래 가격을 예측
철강·구리·니켈 등 변동폭과 수요가 큰 핵심 소재 선제 예측
거시 경제 데이터·수요·공급 데이터를 다각도로 학습
최적 구매 타이밍 확보로 제조 원가 상승 리스크 최소화
글로벌 매크로 지표 기반
원자재 가격 예측
환율, 원자재 지수, 글로벌 경제 지표를 분석해 철광석,
비철금속 등 핵심 원자재의 미래 가격을 예측
철강·구리·니켈 등 변동폭과 수요가 큰 핵심 소재 선제 예측
거시 경제 데이터·수요·공급 데이터를 다각도로 학습
최적 구매 타이밍 확보로 제조 원가 상승 리스크 최소화
글로벌 매크로 지표 기반
원자재 가격 예측
환율, 원자재 지수, 글로벌 경제 지표를 분석해 철광석,
비철금속 등 핵심 원자재의 미래 가격을 예측
철강·구리·니켈 등 변동폭과 수요가 큰 핵심 소재 선제 예측
거시 경제 데이터·수요·공급 데이터를 다각도로 학습
최적 구매 타이밍 확보로 제조 원가 상승 리스크 최소화
고객 발주 패턴 기반
출고 수요 예측
수요 예측 기반
재고 과잉·결품 사전 감지
제조 원자재 가격
변동 선제 예측
AI 예측 기반 발주
의사결정 지원
Shipment Demand Forecasting Based on Customer Order Patterns
Automatically learn customer- and item-level order cycles and irregular patterns
Incorporate external indicators from downstream industries such as automotive, electronics, and chemicals
Provide data-driven guidance for production timing by factoring in delivery lead times
Proactive Detection of Inventory Overstock and Stockout Risks
Continuously monitor projected overstock and stockout risk ranges by item
Provide data-driven insights for determining optimal safety stock levels
Deliver forecasting dashboards that can be shared across production, procurement, and sales teams
Proactive Forecasting of Manufacturing Raw Materials Price Fluctuations
Reflect global raw materials indices, exchange rates, and supply chain issues in real time
Provide both short-term (5 weeks) and mid- to long-term (6 months) price forecasts
Protect manufacturing margins by proactively mitigating cost increase risks
AI-Powered
Order Decision Support
Provide recommended order quantities based on item-level lead times and inventory status
Significantly reduce order planning tasks that previously took days each month
Connect with ERP data through integration or upload workflows

Forecast Accuracy Improved from 50% to 81%,
Reducing Monthly Inventory Costs by KRW 21 Billion

Deepflow leverages AI to forecast irregular customer orders and raw material price fluctuations, enabling manufacturers to make more accurate purchasing and inventory decisions.
After adopting Deepflow to improve its ERP- and experience-based planning process, Company D, a steel manufacturer, improved forecasting accuracy from below 50% to 81%. The scale of inventory overstock and shortages decreased by an average of 31%, resulting in monthly inventory cost savings of KRW 21 billion. In addition, order planning tasks that previously required more than five days each month were reduced to just one day.

Across B2B manufacturing industries—including automotive parts suppliers, chemical manufacturers, and battery material companies—demand is rapidly increasing for solutions that can simultaneously improve customer order forecasting and optimize raw material procurement timing.
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