How to Build a Digital Twin for Your Warehouse: Tools, Platforms, and Approaches

From Concept to Reality

Digital twin technology is no longer a future-state idea. It’s here—and increasingly accessible to warehouses of all sizes.

But once you’ve decided you want one, the next big question is:

How do I actually build a digital twin?

There’s no one-size-fits-all answer. Some companies adopt twins through their WMS provider. Others invest in third-party platforms. And many explore custom or modular setups that grow over time.

This article will break down the three main paths to implementation—along with real-world pros, cons, and decision criteria.

What Do We Mean by “Building a Digital Twin”?

Building a digital twin means creating a live, digital representation of your warehouse that reflects its physical state in real time. That could include:

• Inventory positions
• Equipment status
• Environmental conditions
• Workflow tracking (e.g. pick paths, staging delays, dock activity)
• Visual layout (2D or 3D)

The twin might include simulation tools, alerting systems, or AI recommendations—but at its core, it’s about bringing visibility and flow to life.

🔗 Related: What Is a Digital Twin? (In Plain English)

Approach 1: WMS-Embedded Digital Twin Features

What It Is

Some modern Warehouse Management Systems now include built-in digital twin functionality—usually in the form of:

• Visual warehouse maps
• Heatmaps of inventory movement
• Zone-level congestion reporting
• Slotting optimization tools
• Labor activity tracking overlays

Vendors like Manhattan, Körber, Blue Yonder, and even mid-market WMS providers are starting to integrate real-time visual tools directly into their core platform.

How It Works

The WMS already has access to most of your operational data—location scans, inventory movements, task assignments, timestamps. These systems use that data to power interactive floor maps, live dashboards, and scenario testing tools.

Pros

• No integration headaches—uses existing system data
• Data is clean and structured
• Seamless user experience for supervisors and ops teams
• Often supported by your existing WMS vendor contract

Cons

• Functionality varies wildly by vendor
• Customization is often limited
• Might require an expensive upgrade or premium module
• Usually focused on inventory and labor, not full facility simulation

Ideal For

Companies already planning a WMS upgrade, or using a top-tier provider with built-in digital twin support.

Approach 2: Third-Party Digital Twin Platforms

What It Is

These are dedicated software platforms built to create and manage digital twins across industrial operations. Think of them as the “engine room” for simulation and live modeling.

Leading providers include:

• Siemens Teamcenter / NX (enterprise-grade)
• Matterport (3D mapping + layout)
• Cognite Data Fusion
• Reekon Systems (construction/logistics focus)
• Doxel, NavVis, or Unity Reflect for visual modeling

Some focus heavily on 3D visualization and layout scanning. Others emphasize data modeling, scenario testing, and AI-driven optimization.

How It Works

These systems are typically fed by:

• API links to your WMS, LMS, or ERP
• IoT sensor data (e.g. temperature, equipment telemetry)
• Camera and scanner feeds
• CAD layout files or point cloud scans (for 3D twins)

They offer powerful tools—but usually require significant IT support, integration effort, and internal training.

Pros

• Deep functionality for modeling, forecasting, simulation
• Vendor-agnostic—works across WMS/ERP systems
• Supports AI overlays, digital twin of the organization (DTO), and lifecycle analytics
• Strong 3D and AR/VR potential for training or walkthroughs

Cons

• High cost, especially at enterprise scale
• Integration complexity—especially for legacy WMS setups
• Steep learning curve
• May require outside consultants for rollout

Ideal For

Larger facilities, multi-site operations, or companies looking to centralize ops planning and digital infrastructure across functions.

Approach 3: Custom Integration and DIY Frameworks

What It Is

This is the most flexible—and potentially cost-effective—approach: build your own digital twin using a combination of:

• WMS data exports
• IoT sensors (temperature, vibration, motion)
• Power BI, Tableau, or another dashboard tool
• Layout maps or 2D CAD drawings
• Manual inputs (e.g. floorwalk data, cycle count variance reports)

This isn’t “digital twin in a box.” It’s a tailored solution built with the tools you already use—designed to reflect your specific process needs.

🔜 We’ll explore this approach in detail in:

DIY Digital Twins for Warehousing: A Practical Guide

How It Works

You manually map your warehouse layout, then feed it real-world data through:

• CSV exports or live links to WMS/LMS
• Sensor gateways (e.g. using Raspberry Pi, Arduino, or commercial IoT kits)
• Reporting dashboards that layer flow and event data over the layout
• Visual tools like Miro, Lucidchart, or Visio for updates

Over time, this evolves from a simple floor overlay to a functioning twin capable of highlighting flow gaps, slotting inefficiencies, or environmental risks.

Pros

• Flexible and affordable
• Build exactly what you need—no license bloat
• Great for Lean-minded teams who want full control
• Scales as you grow

Cons

• Requires internal skills or support (data handling, visualization)
• No plug-and-play experience
• Limited 3D or simulation tools (unless you build them)
• Data governance and version control need discipline

Ideal For

Small to mid-sized warehouses, Lean CI teams, or any operation that wants visibility and experimentation without committing to full platform investment.

Comparison Table

Feature/Need	WMS-Embedded	Third-Party Platform	Custom/DIY
Ease of use	✅✅✅	✅✅	✅
Setup effort	✅✅✅	❌❌	❌
Cost	✅✅	❌❌❌	✅✅✅
Simulation tools	✅	✅✅✅	✅ (limited)
Integration flexibility	❌	✅✅✅	✅✅
Best for…	Existing WMS users	Large or complex ops	Mid-size / DIY culture

Choosing the Right Path: 5 Questions to Ask

1. What’s your operational goal?
   Layout testing? Real-time flow monitoring? Condition alerts?
2. What data do you already have?
   Do you have scan timestamps, sensor feeds, or just static counts?
3. What’s your internal capability?
   Can your team manage integration, or do you need plug-and-play?
4. How important is visual layout?
   Some twins are about visuals. Others focus on data modeling.
5. What’s your budget and timeline?
   Enterprise tools take longer. DIY twins can start in a spreadsheet tomorrow.

Final Thoughts: You Don’t Have to Build Everything at Once

A digital twin isn’t an all-or-nothing project.

Whether you start with a WMS heatmap, a DIY Power BI model, or a full-scale third-party twin, the key is the same:

Create a live, trusted window into your operation—one that helps you plan, test, and improve flow.

Start small. Build iteratively. Learn as you go.