Digital Twins: Unlocking Real Business Value with Virtual Asset Replicas

The concept of Digital Twins dates back to early computer‑aided design, where virtual models were used to explore “what‑if” scenarios. Today, artificial intelligence, advanced analytics, and the Internet of Things elevate these models into powerful, real‑time digital replicas.

Digital Twins rank among Gartner’s top ten strategic trends for 2019, a status well‑deserved. By mirroring a physical object, system, or process with precision, they enable engineering simulations that answer “what if” and “then‑what” questions—tasks that would otherwise be costly or impractical to perform on the physical counterpart. Anna Solana, Science & Technology writer for IoT Solutions World Congress 2019, emphasizes this capability.

Consequently, Digital Twins are gaining traction across diverse, asset‑intensive sectors—including aerospace, oil and gas, automotive, and industrial manufacturing—where they support modeling, simulation, testing, and real‑time monitoring powered by IoT sensor data.

Concrete scenarios abound. For instance, a Digital Twin can predict how changing a component’s material will affect device performance, or assess whether a car seat will pass safety tests under specific conditions. In manufacturing, it can optimize robotic positioning on a production line, eliminating wasteful movements. These insights empower companies to dive into innovation confidently.

According to Gartner, by 2021, half of large industrial firms will have adopted Digital Twins, driving roughly a 10% boost in operational effectiveness. The current emphasis lies on IoT‑driven Twins. Deloitte projects the global Digital Twins market to grow at 38% CAGR, reaching $16 billion (€14.2 billion) by 2023.

New avenues to revenue

The proliferation of these versatile avatars is evident. As Deloitte partner Maximilian Shroeck noted at IoT Solutions World Congress 2018, “the ultimate purpose of a Digital Twin is to deliver tangible business outcomes—whether by enhancing existing products within established value chains or by launching new products and services in emerging ecosystems.”

He added that Digital Twins open fresh revenue streams, whether through value‑added services, innovative solution stacks, or monetizing data and insights in novel ways.

But where should an organization begin? Mark Gallant, Senior Director of IoT Solutions at PTC, advises: “If you manufacture high‑complexity, low‑volume products, start with the product’s Digital Twin. For low‑complexity, high‑volume production, begin with the machines and processes—those are the Twin’s foundation.” Ultimately, the starting point hinges on your business model.

In practice, deploying Digital Twins is a collaborative effort, transforming enterprises across all functions.

Applying human knowledge

Teresa Tung, Managing Director at Accenture Labs, stresses that human expertise is pivotal to realizing Digital Twin potential. A key maturity milestone involves capturing and applying human knowledge to complement AI and automation.

Gallant also cited an example from IoT Solutions World Congress 2018: a floor manager with 30 years of experience could immediately detect an anomaly in a critical machine. The lesson? Listen to frontline insights and address concerns raised by all stakeholders interacting with the data.

With billions of assets slated for digital representation over the next five years, the challenge is vast—requiring robust distributed data management from edge to cloud, safeguarding against security threats, and navigating data ethics.

To stay competitive, organizations must adopt Digital Twins to enable data‑driven decisions and scenario experimentation that fuel innovation. Teresa Tung notes that the option to forego Digital Twins is increasingly untenable. This shift may even redefine what constitutes a product—though that is a broader discussion.

The author of this blog is Anna Solana, Science & Technology writer and contributor to IoTSWC 2019