The built environment has access to extensive data sources, but how can we harness this plethora of data to benefit housebuilding and meet the UK’s substantial requirements over the next five years? Naismiths’ chief technology officer, Gareth Parker, discusses.
The built environment has undoubtedly faced a challenging few years. A combination of supply chain disruptions as a result of the pandemic, the ongoing conflict in Europe, and inflation, which has increased costs significantly – has put a strain on the already thin margins within the industry. These escalating costs have been amplified by one of the worst housing crises in recent memory. While there has been encouraging policy discussion from Westminster – such as the proposal for a more streamlined planning system to deliver 1.5 million new homes by 2029 – the reality is that significant issues must be addressed within the built environment before these ambitious numbers can be achieved.
Data driven decisions
One standout solution is the better use of data. The industry generates vast amounts of data but has historically struggled to turn it into actionable insights. However, with the rise of accessible artificial intelligence (AI), we are beginning to see a shift. AI now enables data, that would have once required hours of manual analysis, to be processed quickly. As a result, the industry is increasingly engaging with proptech as the benefits are evident and we need to embrace new ways of working to deliver the UK’s requirements for housing and infrastructure.
In the current context, the most compelling advantage of data is its ability to reduce risk and introduce a degree of predictability into processes that have traditionally relied on guesswork. A key area where this is particularly impactful is demand forecasting and how it translates into more accurate cost projections throughout the lifespan of a project. By using platforms that pull data from multiple sources, such as the Business Insights and Conditions Survey (BICS), more precise predictions about project costs can be made, based on trends identified in the data. We recently applied this approach to a student accommodation project, and the projection based on previous data came in within one per cent of the actual cost.
When projects are forecast incorrectly
When data is analysed correctly, predictive models can provide accurate forecasting and also flag anomalies, identifying high-risk projects. In an industry where margins are increasingly squeezed, understanding and managing this risk is critical – both for funders and for contractors and consultants. The recent troubles faced by ISG highlight how quickly things can go wrong for a major contractor when several projects turn out to be financially unprofitable. We need to be able to identify risks early, mitigate them effectively, and ensure that projects stay on track.
In the housebuilding sector, Vistry’s recent challenges serve as another stark example of the consequences of failing to use data accurately. Mistakes in cost projections for nine of its major housing developments led to underestimations of up to 10%, equating to an overall profit hit of £115m – but the bigger worry for the business is the impact on overall trust and confidence in future developments. These examples, involving businesses that previously generated hundreds of millions of pounds in revenue, underline the importance of investing in data-driven approaches before risks become unmanageable.
Moving forward
The construction industry’s hesitation to embrace digital transformation is well-known, and this reluctance has become even more apparent in light of the vast scale of work required to ‘Get Britain Building’. The sheer volume of the task is enormous, but when factoring in the tight timeframes for completion, the challenge becomes even more daunting. This is precisely where the utilisation of data plays a critical role and cannot be overlooked.
The effective use of data offers a crucial opportunity for the built environment to address some of its most pressing challenges. With the rapid advancements in AI and analytics, the industry is positioned to significantly improve the way it manages projects, reduces risks, and ensures more accurate cost assessments. These technologies provide the tools to better predict and manage the complexities associated with housing and infrastructure delivery, helping to streamline decision-making and accurately resource both tasks and funds.