Delivering on a simple retail promise — the right product, in the right place, at the right time — requires millions of decisions long before a guest makes a Target run. When those decisions work together, guests are more likely to find the products they came for. When something goes wrong, the effects can ripple through our supply chain and impact store shelves. That’s why we’re continuously accelerating our use of technology to help our teams make better decisions, elevate the guest experience and support Target’s long-term growth.
Our supply chain, product and engineering teams developed Proxima, built specifically for the complexity and scale of Target’s network. Proxima is a digital twin of our middle-mile inventory positioning system — the part of our supply chain that helps determine how inventory moves between facilities and towards our stores. It uses the same data and logic as our modern inventory platform to test how decisions could play out before teams put them into practice.
Solving real problems before they reach stores
Proxima gives teams room to test new approaches, compare outcomes and challenge assumptions, without first changing our live network. If a digital twin emulation through Proxima surfaces a potential problem, teams can correct the issue or take another path. If an approach works, they can move forward with greater confidence.
That faster feedback loop helps teams
- Improve product availability for guests
- Reduce potential disruptions across our supply chain network
- Test and modernize complex supply chain processes with more certainty
Proxima creates faster feedback loops and helps us see around corners so we can modernize complex supply chain processes with confidence while continuing to deliver for guests.
Turning digital twin results into guest impact
Tests from Proxima aren’t just theoretical. They're already helping teams make better inventory decisions across some of the most operationally complex parts of our supply chain.
For example, fresh food adds a layer of complexity to inventory planning because teams need to account for lead times and product expiration dates. In a small-scale pilot with Proxima of 63 fresh food items, the team was able to simulate changes to inventory flow and correct issues before launch. This improved the products’ on-shelf availability by 2.5% — making it easier for guests to find what they were shopping for.
Proxima also supported the launch of our Houston Receive Center. Before the facility opened, teams used it to emulate how inventory would move in and out of the building with approximately 98% accuracy. That gave teams greater confidence as the new building came online and helped minimize inventory flow issues after opening.
Forecast accuracy modeling inventory flow for the Houston Receive Center before launch
Improvement in on-shelf availability across 63 fresh items in a small-scale pilot
At Target, we’re focusing on connecting signals, systems and decisions so our teams can move faster and solve increasingly complex problems. Proxima is a powerful example of that vision in action. The result is a more resilient operation and an even more reliable experience for guests.
Continuing to learn and improve
As Proxima scales across more network functions, our teams will continue comparing digital twin emulations with real results and applying what they learn to future decisions. Over time, the insights Proxima generates could also inform future AI-powered, agentic decision-support capabilities, helping our teams evaluate options, prioritize actions and automate operational responses. It’s another way we’re accelerating technology to help our teams elevate the guest experience, improve availability and create a more reliable Target run.
