Reducing CO₂ Emissions & Food Loss through Supply Chain Optimization
Planning Time86% reduction
Food Loss15 % reduction
The Customer’s Challenge
CPF, a vertically integrated food producer and exporter based in Thailand, manages a complex supply chain from hatchery to distribution.
Operating across 40 countries, the company struggled to meet diverse customer demands for meat size and quality, as its operations relied on manual spreadsheets. This led to a critical inability to provide customers with accurate shipment dates.
Our Approach and Solution
Deploying Blue Yonder Demand and Supply Planning Solution
Demand and Supply Planning
By consolidating all supply chain information into a data lake, the solution provides end-to-end visibility. It enables lean production by optimizing planning based on AI-powered demand forecasting and expertly handling complex processes like the reverse bill of materials (BOM) — where a single raw material is processed into multiple products.
Benefits* and Business Impact
Reduced Waste
Achieved a 15% reduction in residual waste from meat-cutting operations through precise, demand-driven production planning.
Improved Planning Efficiency
The time required to optimize the meat-cutting process was reduced from one week to about one day — an 86% time saving. This speed is critical when dealing with highly perishable products.
Enhanced Customer Satisfaction
End-to-end supply chain visibility enables a stable supply while precisely meeting detailed customer requirements for meat size and quality.
*The stated benefits are based on customer estimates. Actual results may vary depending on conditions and environment.
Contributions to Sustainability**
Reducing Food Loss
The shift to demand-driven production curbs overproduction, leading to a significant reduction in food loss.
Reducing CO₂ Emissions
Optimizing feed supply and production processes prevents over-feeding, which achieves both cost and resource savings. Furthermore, CO₂ emissions are reduced by monitoring energy consumption across the entire production process and supply chain.
**The contributions described are based on a specific case study. Results may vary depending on conditions and environment, and similar outcomes are not guaranteed in all implementations.