Why COVID-19 is driving demand for real-time data
Big data is front and center across a real estate industry hungry for insights
The pandemic is pushing the real estate industry to gather and measure data as landlords, investors and governments look for tangible ways to track market performance.
The amount of data available to property professionals has risen steadily in recent years amid an increased adoption of technology, known in the industry as proptech. But despite the hype around the transformative potential of big data, widespread use of the insights has remained a work in progress.
Now the pandemic has renewed the focus on technology and data. From analyzing rent-collection rates, to monitoring crowds in malls and understanding space utilisation in offices, the pandemic has prompted more property industry players to use proptech to deliver real-time data outputs.
“What we’ve seen around COVID-19 is more adoption on the hardware side where landlords have had to quickly re-specify buildings,” says Matthew McAuley, director in global research at JLL.
High-frequency data in particular is in demand to help make decisions – especially relating to health, mobility and space usage.
In offices, data has helped companies to enable contactless movement, track who’s there at any time, and monitor cleaning frequency. The benefit of such insights in a time of crisis is wide-reaching.
“For landlords, data helps them see how they sit among their peers,” McAuley says. “For governments, it’s about seeing where the distress is, and for investors it’s about pricing and strategic implications.”
Real-time data in demand
In the U.S., the National Multifamily Housing Council (NMHC) and the National Association of Real Estate Investment Trusts (NAREIT) pooled data on rent payment rates from property owners within a few weeks of the public health crisis escalating.
This provided visibility into a previously opaque indicator of a residential asset’s financial health and has informed both policymakers and businesses through the pandemic.
“They are pooling data rapidly and continually to have information sources on something that, in the past, has been anecdotal and sporadic,” McAuley says.
Elsewhere, in the interest of public health, Placer.ai – a retail analytics platform that uses machine learning – has made its footfall data available to show year-on-year traffic fluctuations to major brands.
“Governments are interested to see which sectors are hardest hit by COVID-19,” McAuley says. “They want to see who is paying rent and who is struggling, to manage and mitigate the impact.”
Collecting and disseminating nearly real-time data contributes to greater real estate transparency.
JLL’s Global Real Estate Transparency Index 2020 shows that technology adoption has helped many real estate markets boost their position in the ranking – but the majority have had trouble implementing new technology fast enough.
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“Advanced data collection techniques have only shown a meaningful and measureable impact on transparency across the last two to three studies,” says McAuley.
The combination of new hardware and analytical expertise puts the industry at an inflection point where real and rapid gains from data usage are possible and the pandemic is prompting a meaningful shift in how data is used.
“High-quality information that reflects fast-changing market conditions is invaluable during periods of market turmoil and many data providers covering niche property types have illuminated otherwise opaque market metrics,” says Jeremy Kelly, lead director, global research, JLL.
“These innovative efforts, organized in reaction to the market disruption resulting from COVID-19 highlight how transparency progress is possible when it is made a priority,” he says.
The hope is that today’s advances could help to fast-track digitization across the industry beyond the specific data points from managing the Covid-19 crisis.
“Looking ahead to our next transparency index in 2022, niche property-type data is likely to be a primary driver of future transparency advances,” Kelly says.
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