How to implement a successful digital twin for the AECO industry
Digital twins offer transformative potential for the AECO industry; however, two main problems are hindering their successful delivery: the sector’s disconnected work processes and the disagreement between building owners and AECO professionals over their value, writes Taylor Cupp, vice-president of Hexagon’s Building Solutions
When it comes to digital twins, a value perception gap exists within the AECO sector. 65% of building owners recognise the high value of digital twins, compared with just 47% of AEC respondents, according to Hexagon’s Digital Twin Industry Report.
This disconnect highlights a fundamental challenge. And, despite documented digital twin benefits – including improved efficiency, better problem-solving tools, reduced risk and 80% of companies reporting a reduction in carbon emissions – the fragmented nature of building projects presents challenges. These obstacles make it difficult to both initiate the use of digital twins and maintain their successful implementation.
The following best practices can help ensure success.
Mandate digital twins for AECO
For the AECO industry, it’s the O, or operations, which not only requires a ‘digital twin’ deliverable but also maintains and utilises it the longest.
A successful digital twin spans the entire asset lifecycle from design through to documentation, bidding, coordination, construction, commissioning and operations.
However, when digital twins are not implemented correctly, creating them can feel like a nuisance to some teams. After all, digital twins touch so many areas of the project lifecycle and involve numerous stakeholders. At first, inefficiencies and silos are likely to arise.
Until the end customer, such as a facility manager or building owner, mandates their implementation, digital twins often remain fragmented tools serving only specific teams working on specific segments of a project. Success begins with a requirement, and with the roadmap outlined next.
Create a roadmap for implementing digital twins
As AECO lags behind other industries in adoption, organisations need a clear roadmap when starting out.
Roadmaps should ensure teams:
- Avoid common pitfalls
New adopters often stumble by attempting to build, on day one, overly complex models that prove unsustainable and difficult to deliver and maintain.
Additionally, when starting out with digital twins, many companies engage their facilities teams too late in the process. By engaging the individuals who will ultimately operate and maintain the digital twin as soon as possible, companies report increased usage and engagement with the digital twin once the construction project is complete, plus reduced handover challenges and resistance to adoption.
The age-old adage of “beginning with the end in mind” applies here more than ever, but it’s just as easy to fall into the trap of “trying to boil the ocean”. Customers who succeed in realising value from the data-rich asset they are creating generally start small, with a clear end goal in mind.
- Start with a pilot project
Companies should start with assets where they control multiple project phases. This helps maintain data continuity throughout the process. It also offers the freedom to shape data requirements from design through to occupancy, keeping processes streamlined and efficient.
Buildings with repetitive elements also maximise learning opportunities while minimising challenges. For example, a healthcare facility with repeating and identical patient rooms, exam rooms and operating rooms can employ the “one-to-many” approach. Applying the same model across multiple instances helps scale the benefits efficiently through a single digital twin solution.
In addition, these rooms are traditionally very system-heavy and frequently undergo renovation, so they can quickly realise value through better system management and planning.
Finally, choose projects where operational efficiency gains have clear metrics that demonstrate a return on investment (ROI). An example of this might be monitoring energy consumption and HVAC system performance and comparing it with the pre-digital twin data.
• Overcome data fatigue
Digital twins rely on quality data from multiple sources. We have the tools to capture an immense amount of data, react to it and gain insight from it.
“But what if the data is wrong?” is a question that frequently arises. Data can certainly be difficult, especially when projects involve tens of contractors, each using separate data systems, inconsistent formats and, occasionally, legacy systems with limited integration capabilities that require extensive reconciliation to build the digital twin.
However, the true value realised in taking a digital twin approach is that it creates a framework for unbiased and automated data entry. When a human is removed from the data entry loop, the lag in entry, errors and biased opinions can lead to well-informed and immediate decision-making.
The journey from fragmented BIM to comprehensive digital twins, which are optimised and maintained by operations teams, requires strategic planning, stakeholder alignment and an ongoing commitment to data quality.
By starting with appropriate pilot projects and establishing robust data integration frameworks, AECO organisations can bridge the perception gap and realise the full potential of digital twins.
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