The digital twin is a technology featured in many 2023 trends lists. A recent report by CNBC noted that “like artificial intelligence a few years ago, digital twin technology has tipped from highly specific applications into becoming a widespread management best practice.”

This is certainly true for FM and other important functions in the built environment space. Innovation in digital twin technology— virtual representations of physical objects—has the potential to create operationally rich, continuous data feeds across workplace, asset, and inventory systems.

Not rocket science

The origins of the technology were undoubtedly highly specific. In the early 1970s, NASA developed what it has described as a “living model” for the Apollo program. After Apollo 13’s oxygen tank exploded, forcing the crew to abort its mission to land on the moon, NASA ran multiple simulators to determine what had failed and equipped the physical lunar module with sensors that could capture the required data. According to the agency, doing this enabled “a continuous ingestion of data to model the events leading up to the accident for forensic analysis and exploration of next steps.”

Considering its NASA roots, it’s easy to understand why the technology is still somewhat misunderstood, maybe even mysticized. There is a lingering perception that digital twins are complicated and specialized, a technology that is right for someone else’s organization but not one’s own. But it’s not rocket science. A digital twin can be as simple or static as a 2-D CAD file and it doesn’t have to be identical. However, the more advanced a digital twin is, and the closer it resembles the real-world object, the powerful it can be.

A basic example of a digital twin is the virtual replica of an engine which captures pressure, temperature, vibration, and fuel efficiency information. Armed with this data, a user can take more accurate readings of the engine’s condition and make more informed decisions on its maintenance.

At the other end of the scale – and this is where it gets exciting for facility managers — a fully dynamic digital twin of a building (or portfolio of buildings) can bring together design, construction, and real-time operational data to simulate, predict, and inform decisions based on real-life conditions. By combining the sensor data from assets, spaces and different systems, and an intelligent analytics platform, a cloud-based digital twin has the potential to render a 3D replica of every door, elevate, AC unit, smoke alarm, and desk.

The four pillars

It’s important to think about digital twins as part of a maturity journey, where the technology develops in conjunction with the functions that oversee technology implementation, operations, and collaboration. This journey consists of four pillars:

• initial asset data (e.g., asset registry and space inventory);
• the visual model (i.e., 2D CAD and asset imagery);
• operational data (e.g., space utilization and work orders); and
• analytics (i.e., business intelligence and predictive analytics.)

The fourth pillar is impossible to realize without the other three in place, and only by integrating these four pillars can an organization develop a dynamic, fully 3D, identical digital twin.

Bridging the knowledge gap

A recent IBM survey of 4,000 global business leaders found that more than three-quarters plan to prioritize or invest in technology in 2023 despite the economic headwinds. Top among their reasons were better employee experience and to make their organizations more sustainable and resilient.

One of the ways that technology can do this is by providing business leaders a clear picture of the future, allowing them to anticipate challenges and adapt to changes — which helps explain the growing demand for digital twins, especially in the built environment. According to research firm Verdantix, interest in facility optimization and more predictive analytics has led to increased intent to spend on the technology. More than a third (31%) of organizations reported planned investment in digital twins over the next 12 months. Similarly, over a quarter (26%) said they are already using predictive analytics extensively, with one-fifth (20%) using it to some limited extent.

For many practitioners in the built environment, digital twins have the potential to not just look in the future but also help fill in the past. An endemic issue for facility managers is the lack of transparency, cohesion, and useful data throughout the building lifecycle, from design and construction phase and all the way through operations, which often results in the need for avoidable yet costly repairs or more significant changes to facility strategy.

Digital twins can act as a single source of truth. Capturing building information modelling data in a digital twin ensures crucial information isn’t lost in the handover and that users spot potential problems before they intensify or accumulate. During the operational phase, the digital also ensures that workplace, asset, and system data has a home, an especially important factor in an FM industry that sees the contractors (and potential data owners) responsible for maintenance and other services change frequently.

The enterprise metaverse

With its ability to capture, render, and analyze both historic and real-time data, digital twin technology of facilities can be seen as an anchor for all the IoT, smart building systems, and workplace platforms. Users can eliminate planning and operations blind spots by making it easier to connect asset and facilities data, enabling users to explore, locate, interact with, and report on space and asset data that was previously difficult to access as well as scenario plan in a digital safe space.

These are the qualities that have convinced McKinsey and others to describe digital twins as the enterprise metaverse, “a digital and often immersive environment that replicates and connects every aspect of an organization to optimize experiences and decision-making.” Unlike the metaverse as it’s more broadly understood, however, there is little skepticism around the application of digital twins and their usefulness.

Nick Stefanidakis has more than 20 years of progressive experience in the fields of real estate and facility management, mechanical and application engineering, and enterprise software deployments. In his current role, he leads business process design, technology consulting, and project management for IWMS, BIM, and IoT at Eptura, a global worktech company.