In this article, learn about:
How digital twins are used in the retail supply chain
How retailers and suppliers are using digital twins to test decisions before rollout
Supply chain leaders are under pressure to improve offerings, control costs, and support growth. But changes come with risk. For example, optimizations to fulfillment, inventory management, or store operations can create bottlenecks if you get them wrong in the real world.
That’s why more retailers and suppliers are exploring digital twin technology. In this article, we’ll dive into what digital twins actually mean in a retail context and where retailers and suppliers are using them today to deliver real value.
What is a Digital Twin?
At its core, a digital twin is a digital replication of something physical. According to IBM:
“A digital twin is a virtual representation of a physical object or system that uses real-time data to accurately reflect its real-world counterpart’s behavior, performance and conditions.”
A digital twin is not simply a “3D model” or a pretty visualization. A digital twin provides a living model that updates as data changes and can be used to run “what-if” scenarios and make informed decisions.
This technology already shows up across industries: manufacturers use digital twins to optimize factory lines, utilities model power grids, and airlines simulate fleet and maintenance decisions. In the supply chains, it can be used to create a virtual version of your network, inventory, or operations to test decisions before they're rolled out.
How Does a Digital Twin Work?
Digital twin workflows look different across industries and applications, but most share a few common building blocks:
1. A defined “system” you want to model
This could be your end-to-end supply chain, your DC network, or even a single store format.
2. Data that describes how that system behaves
For a retail supply chain, that could include data points like:
Historical and near real‑time sales or POS data
Inventory positions across DCs, stores, and channels
Orders, shipments, and lead times
Supplier performance and fill rates
Transportation lanes, modes, and costs
3. A model that connects the pieces
The digital twin uses that data to model how the system, product, or machine behaves with different inputs or conditions. This is where you can start to test “If we change X, what happens to Y and Z?”
4. A feedback loop
As new data comes in, the twin updates. That makes it possible to:
Compare what you expected to happen vs. what actually happened
Refine the model over time
Continuously run new scenarios on a more accurate representation of your network
The result is a test environment where you can experiment with minimal risk.
How Are Digital Twins Used in the Supply Chain?
In the supply chain, digital twin technology already shows up in a variety of practical ways. Common applications include:
Network and inventory modeling: Simulate how changes to DC locations, capacities, or roles will affect service levels, transportation cost, and inventory placement across the network.
Demand and supply planning scenarios: Test how different demand patterns, safety stock policies, or allocation rules ripple through production, replenishment, and on‑shelf availability.
Logistics and fulfillment optimization: Model transportation routes, carrier mixes, and fulfillment methods to understand cost and service trade‑offs before you change the playbook.
Risk and disruption planning: Run “what if” scenarios for supplier outages, port delays, or extreme weather events, and see how different responses would perform.
For both retailers and suppliers, digital twins make it possible to test supply chain decisions in a virtual environment before those decisions affect stores, partners, or customers.
Where Digital Twin Technology Adds Value
Digital twins can move a business beyond static reporting and single function tools. Dashboards can tell you what happened, and individual planning systems (demand planning, inventory, TMS, WMS) can optimize within their own domain. But it’s still hard to see how a change in one area will ripple across the rest of the supply chain.
Digital twins connect data and logic from multiple systems, like planning, inventory deployment, transportation, warehouse operations, and even store execution, so you can see the end‑to‑end impact of a decision before you make it.
That makes digital twins especially useful for decisions that are expensive or disruptive to reverse. Instead of asking, “What do we think will happen?” teams can model those real-world scenarios in a virtual environment.
Digital Twins in the Supply Chain: Real World Use Cases
Nestle: Scaling Product Content
Nestlé is using digital twins of products like Purina, Nescafé Dolce Gusto, and Nespresso to speed up how content gets to market. By creating exact 3D replicas of physical products, teams can localize packaging, update content, and generate new visuals for ecommerce and digital media without reshooting every asset.
That means product changes, packaging refreshes, and new market launches can be supported with accurate, up‑to‑date content much faster. Instead of content becoming a bottleneck for launches, Nestlé’s digital twins help marketing and commercial teams keep pace with product and packaging changes happening upstream.
Walmart: Reducing Equipment Issues and Disruptions
Walmart has built digital replicas of thousands of its stores, covering everything from floor plans and shelving to refrigeration, HVAC, electrical, and plumbing systems. These digital twins are connected to real‑time equipment data, so the system can flag issues early, trigger a work order, and prompt teams to act before there’s a loss.
Walmart reports a 30% reduction in emergency alerts and a 19% reduction in refrigeration maintenance costs. The same models are being extended to fixtures, backroom shelving, and docks, which can support better inventory tracking, faster restocking, and tighter coordination of inbound loads.
Lowes: One View of Store Layouts, Inventory, and Operations
Lowe’s uses digital twins of its stores to give teams a single, visual representation of what’s happening in each location. The models are updated daily and tied into store CADs, fixture layouts, planograms, and operational data like inventory and financials. The platform “knows” the location and status of fixtures, signage, equipment, and even some devices and people.
This technology supports multiple use cases: planning seasonal resets, testing store layout changes before rollout, standardizing visual merchandising, and improving how associates navigate and maintain the store. Instead of piecing together flat spreadsheets or photos, teams can see the real environment, understand constraints, and model changes before they impact customers or in‑store operations.
Related Reading: Manufacturing Automation: Technologies Transforming Modern Production
What the SPS Network Can Do for You
Digital twins are only as strong as the data feeding them. For retailers and suppliers, that means:
Accurate, timely POS and inventory data
Reliable order, shipment, and fulfillment information
Consistent product and partner data across channels and systems
That’s where a network like SPS Commerce becomes foundational. With more than 300,000 trading connections and billions of retail transactions, the SPS network:
Standardizes and connects data across retailers, suppliers, and channels
Improves visibility into demand, inventory, and fulfillment performance
Provides the trusted inputs needed to power stronger planning, simulation, and decision-making
Learn how the SPS network can give your team the data foundation needed to power accurate digital twins and better end‑to‑end decisions.
