Digital twins hold significant promise for the AEC industry, but their widespread adoption is hampered by two key issues: the disconnected nature of current work processes and a fundamental disagreement between building owners and AEC professionals regarding their true value, explains Taylor Cupp, vice-president of Hexagon’s Building Solutions.
A notable “value perception gap” exists within the AECO sector concerning digital twins. Although 65% of owners recognize their strong benefits, fewer than half (47%) of AECO practitioners agree, as highlighted in Hexagon’s Digital Twin Industry Report.
This disparity underscores a core challenge. Despite documented advantages such as boosted efficiency, stronger troubleshooting, diminished risk, and findings that 80% of organizations reduce emissions through digital twin implementation, the fragmented nature of projects makes it difficult to launch and maintain these solutions effectively. Bridging this gap and fully realizing the potential of BIM and digital twin integration will require establishing clear requirements, fostering early collaboration, and upholding rigorous data quality standards.
Make digital twins a project requirement early on
In practice, the “O” in AECO (Operations) often drives and maintains digital twins the longest. A truly successful digital twin spans the entire asset lifecycle—from design through documentation, bidding, coordination, construction, commissioning, and finally operations. That means building owners and facility managers should require a digital twin deliverable tied to the BIM workflow from the outset.
When digital twins are not implemented correctly, creating them can feel like a nuisance: they touch so many parts of the project and involve so many stakeholders that inefficiencies and silos easily arise.
Until the end customer (for example, the owner or operations team) mandates a cohesive digital twin, these models often remain isolated tools for specific teams. In short, success begins with clear requirements: The owner must define the need for a BIM-informed digital twin and then follow with the roadmap steps outlined below.
Build a practical, scalable roadmap
New adopters often make the mistake of attempting to create overly complex BIM and digital twin models from day one, which are then difficult to deliver or maintain. Instead, develop a clear roadmap that starts small and engages all stakeholders early. For example, involve facilities and operations teams while modeling existing conditions and planning the digital twin.
Bringing in the people who will use the digital twin the most increases adoption and engagement once construction is complete, and it reduces handover challenges and resistance to change. In practice, this means defining pilot projects (often buildings or systems where you can control multiple phases) so that data requirements can be shaped from design through occupancy. With a focused pilot and a clear end goal, teams avoid “boiling the ocean” and ensure that BIM data flows into the digital twin in a controlled, continuous way. The result is a roadmap that avoids common pitfalls and keeps BIM and digital twin development on track.
Ensure high-quality data from day one
Digital twins rely on high-quality data from many sources, and it’s natural to ask, “What if the data proves unreliable?”. Data quality becomes especially challenging on large projects with dozens of contractors, each using separate systems and formats, plus legacy records that don’t easily integrate. For Voyansi and our clients, the best solution is to capture the best data up front.
We emphasize BIM-integrated data strategies and professional capture, utilizing advanced 3D laser scanning, UAV photogrammetry, or detailed point-cloud surveying to accurately gather existing conditions. Working with high-precision equipment and experienced modelers minimizes errors and lags in the data entry loop, and it removes the bias that can occur when data comes from disparate sources. This disciplined approach leads to well-informed, near-real-time decision-making and ultimately a reliable digital twin.
The true value of a digital twin lies in its ability to create a framework for automated, unbiased data updates. However, moving from a fragmented BIM to a comprehensive digital twin (maintained by operations teams) still requires strategic planning, stakeholder alignment, and an ongoing commitment to data quality. By starting with well-defined pilot projects and establishing robust data integration frameworks— essentially a digital twin integration strategy—AECO organizations can bridge the perception gap and achieve the full benefits of digital twins.
Voyansi draws on over two decades of experience in BIM modeling, reality capture, and digital twin integration. Like Hexagon’s Multivista team, which emphasizes over two decades of experience in reality capture and end-to-end digital twin analysis, Voyansi combines advanced capture equipment with powerful BIM tools. We integrate data into the Hexagon ecosystem (and other BIM/FM platforms) to automatically analyze and drive efficiencies throughout the project lifecycle.
Ready to start your digital twin journey? Contact us for a free 30-minute consultation, and let’s discuss how Voyansi’s expertise and data-quality strategies can set up your next project for success.
