Blue Yonder Order Sequencing helps Shanghai PepsiCo balance complex demand and production constraints
Shanghai PepsiCo relied on manual analysis, experience, and intuition to manage complex production planning, but human planners were overwhelmed by the volumes of real-time data needed to balance demand, inventory, capacity, and supply chain constraints.
Human planners could not successfully handle the complexity of real-time supply chain data at scale, making it impossible to create and continuously update an optimal production sequence.
Shanghai PepsiCo achieved significant benefits, including reduced inventory investments, carrying costs, and production changeover expenses, while consistently achieving high order fill rate metrics and matching sales demand with product supply at a new level of precision and agility.
Frequently asked questions
What did this team achieve with this AI workflow?
Shanghai PepsiCo achieved significant benefits, including reduced inventory investments, carrying costs, and production changeover expenses, while consistently achieving high order fill rate metrics and matching sales…
What tools did this team use?
Blue Yonder Order Sequencing, Blue Yonder Production Planning, PWC.
What results were reported?
Overall business benefits: significant; Inventory investments, carrying costs, and production changeover expenses: reduced; order fill rate (OFR): consistently achieved high order fill rate (OFR) metrics (source-reported, not independently verified).
What failed first in this deployment?
Human planners could not successfully handle the complexity of real-time supply chain data at scale, making it impossible to create and continuously update an optimal production sequence.
How is this supply chain AI workflow structured?
Real-time data ingestion → Optimal sequence calculation → Automatic sequence adjustment → Demand-supply matching output.