Digital twins sound like the stuff of science fiction. But digital twin technology is increasingly popular thanks, in part, to the emergence of data analytics, artificial intelligence and the internet of things (IoT).

Digital twins make it possible to create a software-based representation of a physical object, which — with the help of a series of sensors within the physical object — can be used to monitor the object’s health, movements, location and other pertinent conditions.

Take, for example, a car. Data collected by sensors in the car can be used to help create a digital replica or digital twin of that car on a remote computer. The twin then provides a real-time understanding of the vehicle’s status, such as location, engine performance, fuel consumption, temperature or even tire pressure.

In the manufacturing industry, this technology has historically been used in the engineering environment. Today, however, it is moving quickly into other areas of the company.

The reason? Digital twin technology can help companies take better advantage of IoT devices and their data. It also provides a range of additional efficiencies, from enterprise decision making to organizational business processes.

Case in point: According to research firm Gartner, Inc., 13 percent of organizations implementing IoT projects already use digital twins, and an additional 62 percent are either in the process of establishing digital twin use or are actively planning to do so. From a monetary perspective, according to Juniper Research, digital twin revenues are expected to reach $13 billion by 2023, up from an estimated $9.8 billion in 2019.

Let’s take a closer look at some real-world advantages:

Efficiency gains 

First, digital twins can help enhance efficiency. Perhaps a device in your corporate environment is producing data required by a range of applications in different departments. If that device has a digital twin, applications requiring data can simply poll the twin so the original physical device can continue working uninterrupted.

We can take that concept even further. According to a report published earlier this year by Gartner, “When combining the twin data with business rules, optimization algorithms or other prescriptive analytics technologies, digital twins can support human decisions or even automate decision making” (How Digital Twins Simplify the IoT).

For example, you can create a digital twin of your entire organization — including business rules and organizational processes — and then conduct what-if scenarios implementing potential performance-enhancement changes to the twin, so you can understand the impact on the company before any actual implementation.

Some leading-edge organizations are taking the efficiency concept further by integrating their digital twins with other technologies. By integrating these digital instances and applying AI and advanced analytic technologies, corporate operations centers are creating performance trends and baselines; improving asset maintenance, tracking and management; and incorporating automation into nearly any business process.

The final barrier, removed

One of the few barriers to digital twin adoption is the difficulty of creating the twin instance. It’s a complex process requiring a unique skill set. So, with the market potential growing at a double-digit rate, organizations are turning to leading technology vendors for support.

Technology companies are starting to offer digital twin platforms. According to one technology provider, “Digital Twins is an IoT service” to “help create comprehensive models of physical environments” and “create spatial intelligence graphs to model the relationships and interactions between people, places and devices.” A replica like this allows you to query data from a physical space rather than disparate sensors, so that reusable, highly scalable, spatially aware experiences can be built to link streaming data across the physical and digital world.

With more organizations moving toward digital twin technology and big players already in the game, expect this technology to become mainstream very quickly.