Kraft Heinz

Food and beverage supply chains face uniquely complex demand signals — seasonal patterns, promotional spikes, and SKU proliferation across thousands of item-location combinations. Kraft Heinz, one of the world's largest food and beverage companies with extensive North American operations, found its planning infrastructure increasingly inadequate for this complexity. Material shortages and commodity pricing volatility exposed structural weaknesses: demand planners across sales, finance, and category management operated from siloed, conflicting datasets with no unified source of truth. Spreadsheet-driven forecasting lacked the granularity needed to manage weekly item-location demand at scale, leading to excess inventory buildup, food waste, and deteriorating service levels — compounding costs in an industry where margins are thin and waste carries both financial and reputational consequences.

In 2022, Kraft Heinz partnered with o9 Solutions to deploy their Digital Brain platform across North American demand planning operations. The implementation centered on machine learning and predictive analytics operating at the weekly item-location level — a granularity that spreadsheet-based processes could not sustain. The AI functions as a virtual scientist, continuously running thousands of demand simulations to refine forecasts and optimize inventory allocation and replenishment decisions. The platform integrates demand signals from sales and operations planning, finance, and category management into a single environment, eliminating the conflicting data versions that previously fragmented cross-functional decisions. Forecasts are designed for explainability — planners can interrogate why the system makes specific recommendations, reducing override bias and building trust. The North American rollout was comprehensive, while EMEA deployments followed a more adaptive approach calibrated to regional market maturity.

Kraft Heinz achieved measurable improvements across forecast accuracy, inventory efficiency, and waste reduction since the 2022 deployment:

• 8% increase in monthly forecast accuracy, improving production scheduling and supply stability
• 10% improvement in short-term accuracy at the weekly item-location level, enabling faster inventory allocation decisions
• 70% forecast accuracy at a four-week planning lag, improving supply-demand alignment across the planning horizon
• 25% reduction in excess inventory, advancing the company's goal of zero overstock in North America
• 10% decrease in supply chain losses, directly cutting food waste and reinforcing sustainability commitments

Beyond the metrics, service levels improved materially — ensuring product availability during market volatility. Demand Planning Lead Marcelo Iuki framed these results as meaningful progress toward a higher ceiling, not a final destination.

• Forecast accuracy gains compound downstream: Kraft Heinz's 8% monthly improvement translated directly into a 25% inventory reduction and 10% fewer supply chain losses — outcomes that affect cost, sustainability, and service simultaneously.
• Explainability is a prerequisite for adoption; planners are far more likely to trust and act on AI recommendations they can interrogate and understand.
• Regional deployment pacing matters — North America and EMEA required different rollout approaches based on organizational readiness and market maturity.
• Eliminating cross-functional data silos amplifies AI value beyond what demand-only models can deliver; integrating finance and category management inputs is as important as the algorithm itself.
• In food and beverage, supply chain efficiency and sustainability goals are reinforcing — better forecasting reduces food waste and improves both ESG outcomes and margins.