Digital Twins in Retail: Modeling the Physical Store

Digital twins let retailers model the physical store with live operational data, enabling teams to test layouts, inventory strategies, and workflows before spending real capital. Instead of guessing what will happen when you move a category or introduce a new pickup flow, you can simulate it and see the downstream effects on labor, stockouts, and customer experience.

Why Digital Twins Matter in the Store

Retail is a game of tradeoffs: speed versus service, margin versus availability, consistency versus local optimization. A digital twin makes those tradeoffs visible by connecting data from planograms, sensors, inventory systems, and shopper behavior into a unified model. Leading retailers are already using this approach to explore new operating models and empower store associates with better visibility into what should be happening in the aisle versus what is actually happening on the floor.

Core Use Cases That Drive ROI

Digital twins are valuable when they influence daily decisions, not just annual redesigns. The strongest retail deployments focus on operational use cases that compound over time:

• Layout and planogram simulation: Test new aisle layouts, adjacencies, and promotional endcaps in a virtual store before committing to a rollout.
• Inventory visibility: Combine shelf sensors and POS data to model stockouts in real time and alert teams before lost sales occur.
• Labor optimization: Simulate staffing models under different traffic patterns to prevent bottlenecks at peak hours.
• Omnichannel orchestration: Coordinate in-store picking, curbside, and delivery flows so the physical store can serve multiple channels without chaos.
• Associate enablement: Provide teams with an “expected state” view of shelves and fixtures to speed audits and restocking.

These use cases are less about flashy visualization and more about controlling the variables that affect unit economics: labor, shrink, inventory turn, and conversion.

The Data and Systems Foundation

Digital twins are only as good as the data that powers them. A practical retail twin needs three layers:

• Structural data: Store layouts, planograms, fixtures, and capacity constraints.
• Live operational data: POS transactions, inventory feeds, shelf sensors, and traffic analytics.
• Decision workflows: The actual playbooks teams use to adjust pricing, merchandising, or labor based on what the model surfaces.

When these layers are connected, store leaders gain a single source of truth that makes experimentation safe and repeatable across hundreds or thousands of locations.

Start Small, Then Scale Intelligently

Retail teams can get trapped trying to model everything. The better approach is to launch with one store format and a narrow set of decisions, then expand once the workflows are validated. A practical rollout sequence looks like this:

• Pilot a single format: Pick the store archetype with the highest operational pain and build the initial twin there.
• Instrument the aisle: Focus on one or two categories to prove that the data is trustworthy and actionable.
• Codify the decisions: Define what happens when the twin detects exceptions (restock, reflow, reprice).
• Scale by playbook: Repeat the same model and workflows across similar stores, not one-off customizations.

This discipline keeps the initiative grounded in store-level results rather than drifting into a visualization-only project.

The Junagal Perspective: Twins as an Operating System

Digital twins are not just a modeling tool—they are a new operating system for retail execution. The most valuable deployments connect the twin to the teams and processes that control margins: merchandising, operations, and supply chain. When the twin becomes the shared source of truth across those teams, the store stops being a black box and becomes a system you can tune. That is where compounding operational advantage is built.

Sources

• Reinventing Retail: Lowe’s Teams With NVIDIA and Magic Leap to Create Interactive Store Digital Twins (NVIDIA Blog | 2022-09-20) - Lowe’s is using an Omniverse-powered digital twin to explore layout planning, restocking support, and associate workflows in-store.
• Delivering the Connected Shopping Experience: How Microsoft and Avanade Are Reimagining Retail (Microsoft Azure Blog | 2021-11-09) - Avanade’s Intelligent Store uses a real-time digital twin to deliver visibility and automation across omnichannel retail scenarios.

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