BIM4HOUSING OPERATIONS WORKING GROUP MEETING 26-03-2026
Date: 26 March 2026
Purpose of the Session
The session focused on practical challenges in operational asset management, particularly around building safety compliance, information management, AI adoption and the gap between design, construction and operations. The discussion aimed to surface real-world experiences and identify where improvements are needed to support safer and more efficient building operations.
Key Themes from the Transcript
1. Building Assessment Certificates – low awareness and limited adoption
The initial discussion explored Building Assessment Certificate (BAC) applications under the Building Safety Act.
Key findings:
- Limited experience across participants
- Lack of awareness, particularly outside England
- Perceived relevance mainly to high-risk residential buildings (HRBs)
This highlights a knowledge and engagement gap in operational teams, despite the growing regulatory importance.
2. Safety Case approach – evidence-based assurance
The concept of the Safety Case Report was clarified as:
- a structured process of claim → argument → evidence
- used to demonstrate that a building is safe
This approach, derived from sectors such as nuclear, requires:
- clear documentation
- traceable evidence
- structured information
It reinforces the need for robust, auditable asset information across the lifecycle.
3. Fragmented information and operational challenges
A consistent issue identified was the fragmentation of information across systems and formats, including:
- BIM models
- O&M documentation
- certificates and compliance records
Operational teams often:
- struggle to locate reliable data
- duplicate work due to missing or inaccessible information
- receive poorly structured handover data
This creates inefficiency and increases compliance and safety risk.
4. AI and automation – emerging but inconsistent adoption
AI is being explored across several use cases:
- Document processing and validation
- extracting data from certificates
- automating compliance tracking (up to ~90% success in some cases)
- Asset inspection and diagnostics
- drone surveys detecting defects (e.g. roof issues)
- Data structuring and modelling
- machine learning to convert unstructured data into usable models
However, key limitations remain:
- inconsistent accuracy
- reliance on structured inputs and templates
- need for human validation
AI is therefore seen as a productivity tool, not a fully trusted decision-maker.
5. Data standards, interoperability and the “translation problem”
A major discussion centred on how data is structured, exchanged and used operationally.
Key issues:
- multiple formats (COBie, IFC, proprietary systems)
- lack of standardisation across organisations
- difficulty translating technical data into usable operational language
A critical insight:
Data must be translated from structured formats (e.g. IFC codes) into terms that operational teams understand (e.g. “gas boiler”).
This highlights the need for:
- data dictionaries and taxonomy alignment
- consistent classification systems
- interoperability between systems
6. Failure to define information requirements early
A recurring problem is that information requirements are not defined at project outset.
Consequences include:
- late-stage requests for data
- inconsistent or incomplete handover information
- increased cost and rework
The group emphasised the importance of:
- defining Asset Information Requirements (AIR) early
- aligning design, construction and operations
- involving operational teams from the beginning
7. Contractor delivery and accountability gap
A key risk identified is the inability of contractors to consistently deliver required information.
Challenges include:
- inconsistent documentation quality
- lack of structured outputs
- reliance on manual processes
This reinforces that the handover phase is a critical failure point in the lifecycle.
8. Skills gap and client capability
The discussion highlighted a significant skills and knowledge gap, particularly at client level:
- clients often request BIM outputs they cannot use
- lack of understanding of information requirements
- insufficient capability to manage or maintain data
This results in:
- underutilised digital deliverables
- wasted effort and cost
- poor long-term asset performance
9. Need for standardisation and industry alignment
A strong consensus emerged that the industry requires:
- greater standardisation of data structures and processes
- alignment across systems and stakeholders
- a common “anchor” for information (taxonomy + classification)
Without this, the Golden Thread cannot be delivered effectively at scale.
Overall Conclusion
The session reinforced that the core issue is not the absence of data, but the lack of structure, standardisation and alignment across the lifecycle.
To address this, the industry must:
- define information requirements early
- improve contractor accountability
- adopt consistent standards and taxonomies
- bridge the gap between technical data and operational use
- leverage AI carefully to support (not replace) validation
Ultimately, delivering safe, compliant and efficient buildings depends on connecting information, people and processes into a coherent, lifecycle-driven system—aligned with Golden Thread principles.