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 the retailer giant’s supply chain and impact store shelves.
That’s why Target Corp., a general merchandise retailer, continues to accelerate its technology usage for products in more than 2,000 stores and digital channels. They have found it elevates the guest experience as well as successfully supports the company's long-term growth.
Target’s 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 Target’s middle-mile inventory positioning system — the segment of the retailer’s supply chain that helps determine how inventory moves between facilities and toward its stores. Target uses the same data and logic as its current inventory platform to simulate and test how decisions could play out before teams put them into practice.
Proxima enables teams the ability to test new approaches, evaluate potential outcomes and challenge assumptions before making changes to Target’s 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 to accomplish the following:
Tests from this new digital platform are not just theoretical. They're already helping teams make better inventory decisions across some of the most operationally complex parts of Target’s 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 more than 60 fresh food items, the team was able to simulate changes to inventory flow and correct issues before launch. This allowed Target to gain 2.5% improvement in its on-shelf availability, making it easier for guests to find what they were shopping for, when they needed it.
Proxima also supported the launch of Target’s 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.
As Proxima scales across more network functions, Target says its 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 the retailer’s teams evaluate options, prioritize actions and automate operational responses. It’s another way Target Stores is accelerating technology to help its teams elevate the guest experience, improve availability and create a more reliable Target run.
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