In the liveable city, is data the new oil?

Data and technology, like oil, have the potential to fuel radical and positive transformation. Andrew Knight, RICS Global Data and Tech Lead, discusses what risks remain, and what must change before the benefits of data can be realised.

Every session at the World Built Environment Forum Dubai 2022 was underpinned by discussion of the opportunities and challenges of adopting data and technology. Conversations examined these at every scale, from the individual asset to the level of city, region, country and ultimately the planet.

Whatever modern societal challenge we are addressing – be it liveable cities, decarbonisation, or making construction more cost-effective – data and technology offer a means of progress.

Data and the built environment

We are all becoming more familiar with the potential of BIM, digital twins, blockchain, the internet of things (IoT) and various forms of artificial intelligence.

Not only must these technologies be applied across new projects, they are also needed to help us understand and manage the 70% of existing buildings that will still be in use in 2050. These represent 70% of the most inefficient buildings on the planet.

There is one common thread that links all these technologies – namely data, and with it the challenges of a lack of standardisation, governance, and ethics.

Many organisations are already some way along the path of digitisation. But with a sector as fragmented as the built and natural environment, best practice needs to be replicated across all organisations.

Is data the new oil?

One phrase mentioned during the summit that bears a closer look was coined by the British mathematician and entrepreneur Clive Humby in 2006: ‘Data is the new oil.’

Humby founded global consumer insights company and worked closely with Tesco in the UK to launch the supermarket’s Clubcard loyalty programme. This could be seen as one of the first uses of big data based on the contents of weekly shopping baskets.

Is data then more valuable than oil for the built and natural environment? It might be in the future – but a cursory analysis highlights why this is not the case at present.

Any discussion of data as oil would also be remiss without highlighting the various characteristics of oil we want to avoid. How do data and oil compare?

• Both need to be processed to create value. Like refining crude oil, processing data can provide information and knowledge to fuel better decision-making.
  
• Crude oil and data can both leak – with disastrous results.
  
• Both can be exploited by cartels. The Organization of the Petroleum Exporting Countries still controls some 60% of oil traded internationally, and around 80% of the world’s proven oil reserves. We must be alive to the danger of a few powerful market participants monopolising property data.
  
• Compared to data, oil is more fungible. One barrel of Brent Crude or West Texas Intermediate is very much like another. Built and natural environment data, however, concerns multiple property types across a range of sectors and disciplines, in myriad languages and formats.
  
• Data is thinly traded and shared between market participants whereas crude oil is freely traded with deep spot and futures markets. Crude oil can only be owned or consumed by a single user, whereas data can potentially be shared, used and reused many times by many different parties.
  
• Oil consumption is a cause of climate change. Although the built environment is contributing significantly to climate change as well, data can also help mitigate this.
  

Building a virtuous data cycle

Data will never, and should never, replicate all the characteristics of oil. But we should aim for data to flow more easily and have a more positive effect on society than oil.

If we envisage a future where data only replicates these positive impacts, it could fuel our economies, underpinning human development, social cohesion and sustainability.

What is needed to ensure we only replicate those positive effects, then? And where on this path to do we find ourselves at present?

Let’s review the challenges.

• Data are either unavailable in a digital form or unstructured and inconsistent.
  
• There is little governance over or sharing of data.
  
• Uncertainty surrounds the provenance, lineage and assurance of data.
  
• There are multiple data standards across sectors, organisations, and jurisdictions.
  
• The sector is not skilled at data design, collection, maintenance or processing.
  
• Innovators from outside the sector are not creating a positive disruption on the market, and this is creating more data silos.
  
• Market incentives actively discourage data sharing or trading.
  
• Data simply can’t flow to those who need it.
  

Making data behave better

We know the applications that will benefit from making data a well-behaved version of oil. These include due diligence, digital twins, automated valuation, benchmarking, and protecting buildings from COVID-19 and fire. Used in this way, data can also support the circular economy, energy performance, carbon reduction, retrofitting and smart cities.

What does the sector need to do, then, to achieve this?

• Ensure convergence between different data standards and taxonomies.
  
• Use artificial intelligence, machine learning and natural language processing to process new and legacy data.
  
• Advance and adopt uses developed on a single, common data model.
  
• Embrace clear governance, ethical and assurance frameworks.
  
• Adopt digital IDs for market participants and physical assets.
  
• Participate in and encourage a change in market behaviour and in thinking about the value of sharing and trading data.
  
• Train real-estate professions in best practice for data.
  

Many technical and cost barriers remain, but the most significant are behavioural. These require education, updated skill sets and a fundamental change in thinking.

But the technology already exists if market participants are willing to collect, collate and share their data. Other sectors have already successfully embraced the principles of data pooling and sharing, and can show the way for the built environment.