Bridging the divide between BIM and smart buildings

By contrast, the smart buildings space can be characterised as more of a “fragmented frontier”. That is not the operational world itself, but rather the result of the diverse range of proprietary systems and protocols used to make buildings smart. This environment involves the deployment and integration of a multitude of disparate systems, from IoT sensors to complex operational technology and ICT infrastructure. It’s one that has certainly fostered innovation, but despite technology advances improving interoperability and maturing client understanding, the integration challenges can require pragmatism, particularly in retrofitting scenarios, making more standardised solutions more complex. On top of this, the two communities, as Alex and I concluded, often fail to speak the same language. This is a crucial point, as you can’t solve a problem until you agree on what it is.

The very structure of the industry, with its separate BIM and Smart Buildings Overlays within frameworks like the RIBA Plan of Works, highlights this institutional disconnect. This separation underscores a significant opportunity: the on-going review of the Smart Buildings Overlay could be a chance to bridge this gap, perhaps by helping to define a much-needed formal digital soft landings framework.

Coming back to standardisation, a key question that arises is whether more of it in the “fragmented frontier” of smart buildings could help drive technology adoption, not least by making specification more straightforward for clients. Yet, to understand why this remains a question and not a market certainty, we must look to what seems to be at the heart of the issue.

This communication gap could be seen as rooted in a financial divide. As Alex explained, BIM is relevant through all stages, but it has seen most traction and funding through capex budget (i.e where money is spent on building and design). These budgets can absorb the cost of creating comprehensive data models, and this financial model is also reflected in the support for various BIM initiatives.

The operational world, however, is funded by a building’s opex. With squeezed margins in FM, there is often little budget to pay for expensive consultants or skilled operators to maintain a complex BIM model. The models, therefore, become static, disconnected artefacts at handover, quickly losing their operational value. This highlights that the problem isn’t the technology, but the misaligned financial incentives of the stakeholders involved.

This brings us to a fundamental question: if the BIM community is asking, “Why aren’t you using our brilliant models?”, they are asking the wrong question. Instead, they should be asking: “What are your biggest headaches, and what information do you actually need to make your day easier, given we understand you operate under different financial constraints?”

Following on from those communication and financial issues, my conversation with Alex helped to illuminate several key pathways forward, all centred on finding a way for these two communities to communicate effectively.

Our discussion explored how the philosophical shift of a “Start with Smart” approach is intimately linked with the practical role of the master systems integrator (MSI). The idea is to reverse the polarity: instead of a ‘data push’ from a BIM model to operations, the process should be a ‘data pull’. This starts with asking the operational team: “What are your biggest headaches? What information do you actually need to run this building efficiently?” This creates a demand for data that the BIM model is then built to serve.

Alex stressed that the MSI is the human element required to bridge this gap. As the ‘translators’ between these two worlds, MSIs possess the unique expertise to normalise data, establish consistent naming conventions and align the diverse documentation that exists across a project. They are the practitioners who can bring the “Start with Smart” philosophy to life by turning operational needs into actionable data requirements.

We dicussed the need for a top-down approach to drive change, which can be both regulatory and client-driven. As the government’s 2011 mandate for BIM Level 2 demonstrated, a similar top-down push is needed for smart buildings. This is exemplified when clients include specific smart building requirements in their Exchange Information Requirements. A new and powerful form of this is the use of performance-related contracts, where main contractors are incentivised to meet sustainability and energy targets, often through a performance-oriented rating system like NABERS. These dual top-down pressures force the entire supply chain to adopt a new mindset and engage in the cross-functional dialogue necessary to bridge the gap.

Looking ahead, the discussion landed on the potential of data, digital twins and AI to serve as a powerful solution for bringing the BIM and smart communities together to help plug the project-operations gap.

BIM can be thought of as the foundational structure, a static information model. Digital twins, however, is where the two worlds converge, transforming that model into a living, dynamic asset. This coming together can be seen in terms of a passive twin – the project information model (PIM), funded by capex and the asset information model (AIM), funded by opex. The difference, as Alex explains, is the AIM would most likely cover static (non-telemetry data) and also things like documents out of scope of the PIM. But he adds that IFC might be able to form the ‘asset twin’ side of the digital twin. However, it is the real-time data that transforms a passive digital twin into an active or performance one.

AI is already providing autonomous maintenance and decision support in operation from real-time data. However, when combined with digital twin technology, AI may further help to bridge the project-operations gap and meet the demands of performance contracts. Alex suggested that a key role for AI and machine learning will be to automate the time-consuming process of identifying and modelling the relationships between building assets, as well as playing a role in structuring unstructured data (e.g. transforming things like emails into model updates). This could help transform BIM models into a standard ontology for smart buildings, leveraging their structured data for operational gain. This is the ultimate promise of a truly intelligent built environment – one where the two worlds no longer operate in isolation, but communicate seamlessly to deliver real value.

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