Page 28 - RC21 EDGE Summer Issue

Business Solutions
DIGITAL TWINS: A MISUNDERSTOOD CATALYST FOR DIGITAL TRANSFORMATION IN REAL ESTATE
DEAN HOPKINS
COO
Oxford Properties
BY NOW YOU HAVE PROBABLY HEARD about digital
twins and likely think about them as a way to visualize a building using software; a version of CAD on steroids. You aren’t alone, as early vendors in the digital twin space have played up that aspect of this powerful capability in order to bring it to life.
However, visualization only scratches the surface of what digital twins bring to our industry and misses the point about the true nature of a digital twin. Digital twins are much more about what is “under the hood,” namely the accurate digital representation of how a building operates, connecting all the data across multiple systems into a living model of the mechanics of a physical building. When understood more completely, it is clear that buildings with a fully conceived digital twin will be worth more than those without. And, when combined with other elements like simulation engines, machine learning and robotic process automation, digital twins create an innovation surface for buildings that promises to help us re-imagine how real estate services are delivered.
Let’s start at the beginning, though, with a definition. A digital twin is an exact digital replica of a physical object or system that allows us to better understand and optimize its performance and design. The concept of digital twins dates to 1991, but it took until 2002 for Dr. Michael Grieves to
apply the concept to complex product engineering (jet engines, turbines etc.). His work was motivated by the
fact that complex products are difficult, expensive and time consuming to design, manufacture and operate. By creating a “digital twin” rather than a physical prototype the whole process of designing, testing and refining a product could be accelerated and made much less expensive using powerful software.
It took until relatively recently for digital twins to make their way to commercial real estate, and even then, the most significant use case was as part of the construction process. This was a natural evolution of the advanced BIM modeling that was already mature in the construction industry. By combining the spatial models from BIM
with static and live sensor data from the buildings, an operational twin emerged for newly constructed buildings.
While this was an important step forward, the narrow application of digital twins to new construction has constrained their true value to commercial real estate and missed the point that buildings with a digital twin are inherently more valuable than those without. New construction accounts for a small proportion of the overall stock of buildings in the world. Imagine, instead, if every building had a live model representing the up-to-date status of the building and all of its services,
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