BIM adoption is at an all-time high, with it already being an established standard practice across the built environment. Statistics from recent years show that over 73% of construction processes have adopted BIM, with a mere 1% of the industry not aware of its benefits.
Building Information Modelling, better known as BIM, lays the foundations for building projects, with many manufacturers, specifiers, and architects around the world weaving it into their common practices. Europe remains a leader of BIM adoption, with nations such as the UK, France, Germany, and parts of Scandinavia either having, or pushing for, mandatory BIM integration into key projects. Likewise, there has been a noticeable rise in North America, Australasia, as well as parts of The Middle East and Asia.
The benefits of BIM adoption are immense. BIM encourages efficiency in design and construction, reducing overall costs and improving accuracy in all operations. By taking accountability and integrating BIM models from the earliest design stages, specifiers and architects help connect the ‘virtual dots’ from the outset to ensure effectiveness in all projects. In doing so, they also help establish the foundations of a Golden Thread, creating a clear, traceable line of information throughout the building’s lifecycle.
Additionally, when it comes to sustainability, BIM enables design teams to evaluate material choices, reducing waste and optimising energy efficiency before any components are even installed.
The benefits of BIM are clear; but how can we take these technologies even further?
BIM as a Foundation
BIM can act as a structural baseline for digital twins, advanced technological models that mirror real-world assets, enabling teams or individuals to manage, analyse, and continuously monitor performance of a building long after construction ends.
Technology is constantly evolving to meet user needs. The growing intersection between BIM and digital twins highlights how these technologies can complement one another, without one necessarily being dependent on the other to function.
BIM components are data-rich models which promote accuracy, accountability, efficiency, and asset data, enabling architects and specifiers to optimise their designs. BIM is an incredibly useful and powerful tool for specifiers, helping them to make more informed decisions, co-ordinate more effectively with project partners, and improve clash detection. While BIM delivers greater project understanding, visualisation, and detail, its traditionally deliverable-based structure has driven the evolution toward advanced data structures, such as digital twins.
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Digital twins are dynamic (for all intents and purposes) ‘living’ versions of BIM models. They are live, digital replicas of physical assets or systems that are continuously maintained and updated with real-time data streams and operational insights, such as IoT sensors, BMS systems, maintenance systems and operational documentation, optimising performances with an unprecedented level of precision.
Additionally, digital twins can enhance the sustainability of a project, as well as occupant experience and operational efficiency due to their ability to monitor performance data and optimise energy usage.
The demand that led to the birth of digital twins emphasised the strides that technological advancements make, particularly as the industry adapts to rapid changes. Digital twins represent a natural evolution in how building data is used. By increasing the long-term value of BIM, digital twins bridge the gap between design and ongoing building performance.
This prevents the loss of information-rich data, perpetuating the legacy of the BIM model as a means of becoming a real-time asset that benefits a building throughout its entire lifecycle. For clients, BIM is a long-term investment that can benefit the entire building lifecycle, from earliest design stages to a building’s decommissioning. BIM models paired with digital twin technology become strategic assets that consistently grow in value. Providing a dynamic environment for a physical asset that updates in tandem, digital twins extend BIM beyond design and construction, integrating ongoing operational data and ensuring intelligent asset management.
Through the live-monitoring of key-building assets, and the centralisation of facility oversight, platforms such as Twinview offer invaluable tools. Twinview help ‘turn building data into building intelligence’ by using digital twin technology to streamline content collaboration, validate construction data, and drive operational efficiencies.
Twinview projects such as the New Zealand Archives highlight the potential of digital twin technology for large-scale projects. The newly constructed Archives in Wellington provide a secure and stable environment for preserving national collections and safeguarding New Zealand's heritage.
For this project, a digital twin was developed using BIM as the foundational model, then integrated with the environmental monitoring, storage condition analytics and building management systems. This enabled real-time oversight of humidity, temperature and energy use, ensuring optimal preservation conditions for the archival materials. By combining BIM and digital twin technology, the project's entire lifecycle is optimised, from more intelligent design decisions to streamlined workflows and long-term asset protection.
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What Does the Future Hold?
The future of digital twins and BIM technology is vast and full of opportunity. As these technologies continue to advance, the opportunities for growth prevail. What simply began to help model buildings more accurately, has paved the way for a powerful ecosystem that can enhance our decision-making, boost efficiency and sustainability, and reveal immeasurable value for asset owners.
It is likely that digital twins will become standard for complex assets, supporting an increased need for predictive analytics, carbon modelling and automated operation. As the industry evolves from a build-and-hand-over to continuous digital lifecycle management, new regulations and standards will support the increased need for these new technologies, and AI will drive faster data retrieval, anomaly detection, and the need for a unified data classification.