Digital Twins Revisited: from Valuable Tool to Strategic Asset

This month I’d like to focus on a topic that I already spotlighted back in 2019 and 2021: digital twins. In the years since these posts were published, the role of the tech has changed radically. Digital-twin technology is now about far more than just operational efficiency. In fact, it’s developed into a genuine strategic asset, transforming the way that organizations plan, decide, and compete. And going forward, it’s set to give impetus to Europe’s digital future.

The market outlook for digital twins underscores their pivotal new role: By 2032, Gartner predicts that intelligent simulation will underpin more than 25% of strategic business decisions. And by 2027, the first enterprise is expected to report operational savings of USD 1 billion thanks to digital-twin simulation capabilities. So, it’s hardly surprising that the tech has become a hot topic in boardrooms across the globe. Let’s take a closer look at digital twins, some of their benefits, and some of the challenges they pose.

From Data Visualization to Decision Intelligence: The Rise of Digital Twins

When digital-twin technology first arrived on the scene, its promise lay primarily in real-time monitoring, predictive maintenance, and simulation. Today, the tech is widely regarded as a means of delivering continuous foresight across assets, processes, and ecosystems.

Digital twins now seamlessly combine Internet-of-Things (IoT) data, AI-driven simulations, and domain knowledge. This combination has transformed them from providers of operational insights into living models that enable organizations to rigorously test strategic decisions before translating them into action.

From Cybersecurity to M&A: The Wide-Ranging Impact of Digital Twins

When it comes to cybersecurity, the tech enables companies to model entire systems and processes. These digital twins can be updated continuously with real-time data to exactly mirror their real-world counterparts – including digital infrastructure elements such as networks, servers, and applications.

This approach has many benefits: By creating digital duplicates of networks, for example, organizations gain a “low-risk lens”, which they can leverage to simulate and predict potential hazards. In the event of real-world changes to the network, these simulations and predictions enable smooth transitions with no disruption to ongoing processes.

Energy: Mastering the Challenges of Today and Tomorrow

Another sector where digital twins are making their mark is energy. As Europe’s energy transformation gathers pace, systems are becoming increasingly complex, not least due to the integration of renewables and the associated need to balance grids and modernize transmission structures.

Digital twins can deliver invaluable insight by accurately modeling the flow of energy through these complex systems. Thanks to the tech, energy players can increase efficiency, improve risk management, and make more rapid progress toward decarbonization – and all this while ensuring supply stability.

Robotics and Manufacturing

In robotics and manufacturing, digital twins started out as process optimization tools. However, in recent years, they’ve advanced to become strategic enablers of manufacturing resilience. By allowing companies to simulate production processes under a wide variety of conditions, they help improve flexibility and reduce waste.

One excellent example of this approach in action is Siemens’ fully automated warehouse, which demonstrates a major advantage of digital twins in manufacturing – faster product iterations. Here, Siemens’ goal is to increase productivity by 40%. In addition, the tech saves costs by identifying disruptions at an early stage and reduces carbon footprint through virtual testing.

What’s more, digital twins have a measurable impact on manufacturers’ EBITDA. By scaling digital-twin implementations for production facilities, companies can reduce time-to-market, labor intensity, downtime, and material waste. This can deliver tangible results, including monthly cost-savings of 5 to 7%, 30 to 60% higher productivity, and a 3 to 5% increase in sales.

Digital Twins in M&A

Mergers and acquisitions (M&A) are another area where digital twins are delivering impressive benefits. By creating virtual models of targets’ operations, acquirers can simulate post-merger integration scenarios before actually closing deals. The tech helps generate highly accurate assessments of synergy potential, operational risks, and capital needs, transforming due diligence into a form of scenario planning.

Over and above its technical and operational impact, digital-twin technology drives direct business value – for example by shortening product cycles and eliminating entire process steps. And this ultimately translates into significant EBITDA improvements and margin gains.

But It’s Not All Plain Sailing

The benefits of digital twins are clear. But if the tech is to deliver on its promise, several challenges must be mastered. When it comes to data, integration, quality, and quantity are of the essence. However, a lack of data centers, harmonized data pipelines, and governance standards across systems pose obstacles in this area.

Another issue is interoperability. Ideally, solutions of this kind should work together seamlessly across the multiple stakeholders involved. Here, fragmented industry standards present barriers and limit scalability. A related problem is cybersecurity: Where multiple systems are interconnected, stricter security standards are a must, and cyber resilience becomes critical.

The Human and Financial Dimensions

In addition to these tech challenges, it’s important to consider the human factor. Expertise in simulation, AI, and domain-specific modeling is currently in short supply. As a result, adoption of digital-twin tech may be hampered by the education gap and talent gap.

Finally, investment pressure can be a disincentive. Building and maintaining digital twins calls for sustained investment, especially where integration with critical public infrastructure is involved.

Digital-Twin Technology and European Digital Sovereignty

The rise of digital twins is also related to a core European policy issue – digital sovereignty. To deliver its full potential, the technology requires vast streams of real-time data, often gathered from critical public infrastructure. And this raises questions of data ownership, storage, and interoperability.

Digital twins thrive on collaboration. But where they span multiple sectors, it’s essential to ensure that data is shared securely. This calls for trusted interoperable sovereign data ecosystems, such as Common European data spaces. Only if ecosystems of this kind are in place can the technology be used with confidence.

From Standalone Tools to Strategic Enablers

Over the past decade, digital twins have rapidly evolved from isolated engineering tools to become true strategic enablers. Today, the technology is redefining how industries plan and reach decisions, helping improve EBITDA, and providing additional impetus to data-sovereignty efforts.

Going forward, digital-twin technology will play a key role at the intersection of Europe’s three greatest challenges:

• Decarbonization

• Resilience

• Digital sovereignty

  
  

It will promote decarbonization efforts by optimizing resources and accelerating the energy transition. By strengthening infrastructure and supply chains, it will contribute to enhancing resilience. And because it relies on greater control over the data and systems that shape national and regional economies, it will help foster European data sovereignty. Digital-twin technology has certainly come a long way since its humble beginnings.

Questions? Comments?

Interested in finding out more about digital twins and their growing strategic importance? Then feel free to reach out to me. Got your own ideas about this tech? I’d love to hear them. Please share your thoughts and experience in the comments below.