Digital Twin: The Next Level for Supply Chains

Digital twin is an emerging technology that will transform supply chains, bringing unprecedented levels of efficiency and value. As it matures into a mainstream technology, understanding how and where to invest in it will be key to unlocking the benefits.
|Written by Sabine Mueller

Supply Chain Trends

digital twin of a person

Technology innovations continually reshape the supply chain landscape. One technology I am convinced will bring our supply chains to the next level is digital twin. Digital twins are already making an impact on several other sectors. They offer many possible use cases for our industry, too.

I believe digital twin technology has the potential to significantly change supply chain and logistics processes. It can make them much more flexible and efficient, allowing us to better react to problems and changes in real time. As the COVID-19 crisis showed, the ability to react quickly is critical. During the pandemic, we were missing real time visibility and flexibility in our supply chains. It meant long lead times to react to shortages. Digital twin holds the promise to improve this and other areas of logistics.

Here, I’ll outline the benefits of digital twin and give my outlook on where I see this trend going.

What Is Digital Twin?

First off, let’s define what we mean by digital twin technology. A digital twin is a digital replica of a physical object, process, or system (in the context of logistics, we’ll call these a “shipment” – and a shipment can be every possible unit). It’s connected to the shipment and updates itself in real-time in response to changes in the shipment’s condition. This allows us to understand exactly what is happening to the shipment in the moment.

We refer to digital twin as a technology when in fact it’s a concept enabled by multiple technologies, including virtual/augmented reality, IoT, cloud computing, machine learning, and AI. A digital twin analyses real-time data and obtains conclusions through AI. With machine learning, it taps into historical and real-time data to make predictions about future conditions. Thanks to VR/AR technology, a digital twin appears visually “real” to the user.

Unlike simulations that need to be fed data in order to show what may happen under certain conditions, digital twins extract data to show both what may and is happening under current conditions.

The Many Benefits of Digital Twin

What makes digital twin so exciting, in my view, is that it enables us to bring the physical and digital worlds so close together that we can manage them as one. It gives us greater visibility over logistics assets and processes, and allows us to make sense of huge amounts of data and complex systems. As a result, digital twin can help us solve incidents and implement improvements better and faster. It can run simulations and test scenarios to help us plan. Finally, it can also leverage AI to predict operations and potentially make decisions.

Here are a few examples: Logistics providers or supply chain managers can monitor operations (even remotely) and immediately address incidents as alerts are triggered. They can visualize the flow of material, shipments and people and spot inefficiencies and waste. They can predict maintenance and repair needs to avoid asset downtime. Pulling enormous amounts of data together, digital twins can run simulations to measure the impact of potential changes.

Digital twin holds huge potential, yes. But it’s also important to note that it is still a maturing technology. Understanding how, how much, and when to invest in it is the key to tapping into the benefits.

How Best to Implement Digital Twin

I don’t recommend that companies rush toward the digital twin trend blindly, as attractive as it is. Rather, I suggest they implement it in a way that is sustainable and value-adding over the long term.

Here’s what I consider the three prerequisites for a sound application of digital twin:

  1. Assess investment attractiveness. Digital twin requires considerable investment in technology and maintenance. What are those costs, immediate and over time? What about profitability – when will benefits exceed costs?
  2. Put in place cybersecurity and data protection measures. Digital twin technology amasses all information about processes / systems in a short period of time. How will intellectual property, customer, and employee data be protected?
  3. Prepare for organizational changes and challenges. Using this technology can have profound effects on an organization. Consider how it will affect the company’s labor needs, IT landscape, training requirements, and corporate culture. And don’t leave out the governance question: Which policies and practices should be developed to ensure the appropriate use of technology?


It’s wise to take the time now to work through these questions and determine at which implementation stage your organization is. It’s also useful to have some practical examples of digital twin in action – so read on.

Digital Twin: Warehouse Use Case

How does digital twin technology work in a real warehouse facility management use case? Having a fully connected digital twin of the facility, including warehouse platforms combined with inventory and operational data, could enable companies to improve space utilization and productivity. A digital twin can also support the design of new warehouses that will be even more efficient.

Here are a few specific areas where this technology can be practical:

  • Digital twin of a warehouse system: Companies can visualize material flow in real time to make quick changes, evaluate results and continuously optimize.
  • Digital twin of a picking station: Being able to predict unexpected maintenance tasks can help facilities plan maintenance and reduce downtime.
  • Digital twin simulations: By simulating a real warehouse, companies can experiment with different workflows and floor plans to assess the impact before rolling out changes in the physical warehouse.


Now imagine use cases extended to the entire supply chain network: vessels, trucks, containers, airports, etc.

The Outlook on Digital Twin in Logistics

Investment in digital twin technology overall is booming. This year, the market size is predicted to be $7.1 billion. By 2026, that figure could be up to $86 billion, according to analysts. But most of that growth is happening in a handful of sectors, mainly manufacturing, energy, and automotive. Implementation of digital twin in supply chain and logistics is lagging behind, but I expect this to change in the next few years.

To date, few logistics companies have been willing to make significant investments in it due to the steep start-up costs. Digital twin technology, however, is reaching a mature state and has gone mainstream. And that means implementation costs are coming down. The price of many digital twin components – sensors, data storage, AR/VR tools – have dropped. More software vendors offer digital twin as an individual product to enterprises. With lowering implementation costs, the business case for this technology has become even more compelling.

It’s clear to me that investing in digital twin for logistics is worth exploring. The efficiencies and value it can bring to companies and their clients are too big to miss. I’m excited to see these changes coming in the coming years.

How do you view the potential of digital twins for your business? I look forward to hearing your perspectives below in the comment section or on LinkedIn.

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