Dongwon Improves Price Forecasting and Inventory Efficiency
Dongwon Group, a South Korean seafood, food, packaging and logistics conglomerate, adopted the Databricks Data + AI Platform to unify previously siloed data across business units and enable enterprise-wide AI-driven decision-making. Using Delta Lake and Unity Catalog, Dongwon built a raw material price forecasting model that reached approximately 96% accuracy and an inventory optimization system that saves billions of won per month, while AI/BI Genie and Databricks Assistant enabled natural-language data exploration for non-technical staff.
Overview
Dongwon Group, a South Korean seafood, food, packaging and logistics conglomerate, adopted the Databricks Data + AI Platform to unify previously siloed data across business units and enable enterprise-wide AI-driven decision-making. Using Delta Lake and Unity Catalog, Dongwon built a raw material price forecasting model that reached approximately 96% accuracy and an inventory optimization system that saves billions of won per month, while AI/BI Genie and Databricks Assistant enabled natural-language data exploration for non-technical staff.
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Inspect the highlighted sourceThe challenge
Although Dongwon possessed more than 50 years of accumulated data, their siloed data structure across business units complicated enterprise-wide utilization. Differences in data definitions, formats and aggregation cycles prevented the creation of unified management metrics and consistent analytical standards.
The solution
Reported business value
The raw material price forecasting model achieved approximately 96% accuracy, becoming a critical component in reducing risk for large-scale procurement decisions. Inventory optimization models generated monthly savings of billions of won, monitoring cycles for manufacturing and logistics KPIs were shortened from daily to hourly, and batch processing times were reduced to mere minutes.
Sources
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