PepsiCo

PepsiCo operates one of the world's largest consumer packaged goods supply chains, spanning a massive network of manufacturing plants and distribution facilities across multiple continents — a footprint the company describes as extending 'from farm to shelf.' Modifying warehouse layouts, reconfiguring conveyor systems, or testing new distribution strategies required physical changes to live infrastructure, risking costly downtime and operational disruption at scale. Traditional planning cycles for supply chain configuration stretched over weeks or months, limiting the company's ability to respond quickly to shifting demand. For an enterprise of PepsiCo's complexity, the inability to validate changes virtually before committing capital represented a compounding operational and financial liability across every facility in the network.

In January 2026, PepsiCo announced a multi-year partnership with Siemens and Nvidia, deploying physics-based digital twins across its US plants and warehouses using Siemens' Digital Twin Composer software, built on Nvidia's Omniverse platform. The system constructs photorealistic, physics-accurate virtual replicas of warehouse environments — modeling layouts, conveyor systems, operator movements, and pallet flows with high fidelity. Supply chain planners can test configurations, identify bottlenecks, and validate equipment placement entirely within the simulation, without touching physical infrastructure. Multiple scenarios run simultaneously, compressing decision cycles that previously took weeks. Siemens' solution creates industrial metaverse environments that merge digital twin data with real-time physical information, providing continuous visibility across warehouse operations, inventory flows, and logistics networks throughout each facility's lifecycle. The initiative began as a pilot across select US locations, with a planned rollout to PepsiCo's global network.

Early pilot results show a 20% improvement in warehouse throughput, achieved alongside near-complete design validation before any physical changes were made. Capital expenditure was reduced by 10–15% by eliminating costly trial-and-error modifications to live infrastructure. The technology detected up to 90% of operational issues during simulation, significantly reducing real-world errors and minimizing downtime during implementation phases. Key outcomes at a glance:

• +20% warehouse throughput in early trials
• 10–15% capex reduction from virtual-first validation
• ~90% of operational issues caught pre-implementation
• Near-complete design validation before any floor changes

Leadership described the deployment as 'the first digital blueprint that reimagines how the supply chain is designed, built and scaled — a first for the industry.'

• Physics-based simulation — not schematic modeling — is what drives PepsiCo's 90% pre-implementation issue detection; accurate rendering of conveyor dynamics and pallet flows is non-negotiable.
• Partnering with established platform vendors (Siemens for industrial software, Nvidia for simulation infrastructure) accelerates enterprise deployment compared to building custom tooling.
• Pilot in a controlled set of facilities first; early US trial data validated the ROI case before committing to global rollout.
• The capex and throughput gains compound when digital twins are integrated across all facilities rather than deployed in silos.
• Design the end state as a 'self-anticipating' supply chain — facilities that adapt to demand before it materializes, not just after.