Technology advances in areas such as big data analytics, machine learning and artificial intelligence are transforming industries across the globe, providing insights and opportunities for those in the vanguard, while technology laggards risk becoming obsolete. But how much influence are these technology innovations actually having on the real estate sector?
While real estate is still very much dependent on location, advances in property technology (PropTech) have shifted the dynamic. Connectivity and accessibility are now coming to the fore as key market factors, and the trend only looks set to grow.
The risk for late adopters is they will be left behind, warns George Thomas, Chief Information Officer for JLL Asia Pacific. “As more investors, developers and landlords move towards additional PropTech features and services, those that fail to adopt even the most basic technology services will find the competitiveness of their assets erode over time as tenants are offered more choice.”
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Real world applications
Technology use has long been a differentiating factor within the real estate industry, with leading developers and asset managers selectively deploying various PropTech features across their assets and portfolios.
“For instance, security sensors, and climate control sensors to optimise the comfort of office building tenants have been in place for years,” notes Thomas. “We’ve also seen use cases around building monitoring, particularly for energy efficiency in various markets.”
Data analysis is another long-running theme. Historically, planners and retailers have leveraged demographic and geospatial analysis of local government-collected traffic data patterns to help inform their location selections. More recently, the focus has shifted to tapping the rich flow of big data now available.
“With the advent of smartphones and more advanced Wi-Fi/Bluetooth sensors, malls – particularly those in mature markets – have utilised the different types of big data to optimise their retail tenant distribution, product allocation, and footfall patterns,” says Thomas.
Big names that have leveraged big data, and AI to integrate customers’ online and offline experiences include Alibaba’s Hema stores in China, and Amazon’s cashier-free convenience stores. Behind the scenes, logistics players are also utilising big data to better plan and further automate and optimise their distribution processes and support to meet the demands of the offline retail sector.
Rapid innovations, falling cost of technology, and the growing sophistication of available toolsets are benefiting incumbents and new start-ups/disruptors alike. These trends are also giving technology leaders a keen competitive edge, making deployment of the latest technology capabilities increasingly affordable and vital.
“We expect there to be a growing emphasis on integrating technology with offline assets and processes, and for real estate to move further towards a service-based product,” says Thomas.
One area Thomas highlights is the value machine learning can offer to investors and portfolio managers. For example, it can be used to enhance the predictability of the lifespan of an asset, such as an elevator, from a capex investment perspective. It can reveal if a retailer is getting enough footfall to pay next month’s rent. Similarly, tracking whether there are more or fewer employees coming in and out of a building during office hours can help gauge whether a tenant should upsize or downsize their footprint.
Technology is also changing the way office staff work, adds Thomas. “We are seeing this in the integration of virtual or augmented reality services. These can help draw in new tenants or customers, and increase the stickiness of the provider’s services. Meanwhile, heat-mapping employee movements enables corporate tenants to optimise their floor space, to meet the demands of the changing workforce.”
Beware the pitfalls
Yet while the latest breed of PropTech initiatives holds out the promise of enhanced efficiencies and optimised returns, there are a number of significant associated challenges. A major one – especially as industry participants increasingly use and rely on big data and artificial intelligence – is to remain in compliance with countries’ privacy standards, says Thomas. The Internet of Things (IoT) also raises questions about data privacy and security protocols.
Scalability of the technology is an additional challenge.
“Developers and landlords tend to view their assets as unique, resulting in site-specific apps that cater towards their particular tenants or occupiers,” notes Thomas. “Deploying services in such situations would therefore require a bigger technology investment. Plus, the speed of any rollout will be constrained by the time it takes to physically install and implement the strategies on an asset by asset basis.”
A further complication is that the available technologies are evolving rapidly. So as Thomas points out: “Significant ongoing investments will be required to update each property and its related services to keep pace with tenants’ and occupiers’ shifting needs and demands.”
But with occupier expectations evolving in lockstep with the latest technology innovations, real estate investors, developers and landlords may find they have little choice but to move with the times.
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