For the uninitiated, building information modelling (BIM) is a technology platform predicted to revolutionise how we visualise and use data within the built environment. Consisting of broadly two elements, BIM can be summarised as:
- 3D representations of buildings or infrastructure;
- Interoperable data to support digital models and collaborative working practices.
In April 2016, housing providers were mandated to use BIM technologies for their new-build developments where the government provided funding for those schemes. A year after the introduction of BIM level 2, what has been its impact on the sector? From an asset management perspective, where BIM arguably delivers the most benefit, very little.
With new-build completions accounting for less than one per cent of social homes, what is the driver to embed this technology and the visual enrichment that it promises in the operational lifecycle of our assets? The usefulness of BIM in managing assets is unambiguous. From providing a deluge of data at the handover of new developments to the facility to allow tenants to interact with a model of their home to self-serve repair reports, the benefits are tangible. But with so little coverage of housing stock currently integrated, BIM’s value will not be fully realised in the delivery of operational efficiency and data accuracy. So, what opportunity exists for housing providers to bridge this data-gap and to baseline their requirements? My answer, and the central theme of this article, is the stock condition survey.
Stock condition surveying is a mature practice in collecting information to assess the performance of buildings and assets. They are carried out by all housing providers and are therefore the perfect intervention to collect the relevant asset data to extend the practice and coverage of BIM. However, aside from increased surveying costs, which I feel are offset by the resulting enhanced data and 3D representation of the building, the biggest barriers to align current stock condition practices with those required to support BIM are information depth and reach.
In my experience, building elements are captured at a generic level, revealing a disconnect between characteristics held in a database and the asset physicality. For example, housing providers are likely to record ‘windows’ collectively for the dwelling as a single asset, along with the installation date, quantity, condition, unit cost and life expectancy. This is perhaps a legacy from the Decent Homes standard and other national standards which focused on monitoring these elements at this high level. Still, this recording method prevents us from correlating repairs, servicing and replacement events with the actual assets and 3D model.
Against the backdrop of a real-term cut of 15 per cent from rental income, housing boards are stress-testing their business plans with a greater emphasis on exactitude so that their asset and development investment plans are ‘sustainable’. To achieve this, organisations use net present value (NPV) or variants of NPV when appraising the sustainability of their existing and future stock. However NPV on its own is a blunt tool for making this assessment because it doesn’t take into account social factors; after all, social homes are not simply financial assets. But it also hides the relative paucity of data used for asset spending over the lifespan of the business because it may not contain sufficient information to factor in repair, refurbishment and servicing costs into its calculations. The data provided by BIM could increase the precision so that bad decisions are avoided when considering the divestment of housing stock.
As part of the process to broaden the reach of BIM, the same techniques organisations use to extrapolate their sample survey data can be engaged. Using archetypes, the housing provider can extend this more detailed data to those like-typed buildings and blend this information into the existing data for those dwellings not surveyed. Though not to the depth of a 100 per cent BIM survey, this approach would enhance the prevailing data to form a more semantic picture of the asset performance and condition, while keeping costs down. Likewise, models and floorplans constructed as part of the survey can be mapped using the same techniques.
By its nature, BIM, along with its near-horizon siblings the internet of things and big data, requires granularity. Granularity provides nuance, semantics and accuracy. I would argue that surveys should be collecting the level of data commissioned at the development handover. This provides synergies with these other technologies to unlock data possibilities to better inform day-to-day decision-making. With manufacturers getting on board with BIM representations of their products, the management of this wealth of data becomes more automated as the supply chain collaborates. ‘Right first-time’ repairs are delivered more frequently as the contractor is armed with the parts information ahead of their visit to the tenant’s home. Your offices may never hear the question, “do you know where your stop tap is?” again.
Not so long ago, we planned road journeys with the ubiquitous ‘map of Britain’, supported by the city A-Zs that clogged up our car boots to get us to our destination. Nowadays we think nothing of using Google Maps on our smartphones and tablets to direct us from A to B, pinching to zoom to focus on the fine detail provided by Street View.
I’m hopeful that this analogy will extend to how we communicate with our tenants, contractors and other stakeholders in the coming years when reporting reactive maintenance and planning major repairs to our housing stock, using BIM as the platform for that collaboration. If we recast how we think about commissioning stock condition surveys, we might just get there sooner.
Justin Fisher is a housing product specialist at Capita.