How data uncovers value above the dirt

In an unpredictable world, how do we forecast the features that will have the biggest impact on real estate asset valuations?

Machine learning will have the biggest impact on asset pricing decision-making, according to 52% of the property professionals polled by EY Australia & New Zealand and MIT Real Estate Innovation Lab during a recent webinar on the future of valuations. And yet 59% of the industry is still hamstrung by “skills and knowledge gaps.”

This came as no surprise to my co-host, Dr. Andrea Chegut. Andrea is co-founder and director of MIT’s Real Estate Innovation Lab, and teaches data science and machine learning at one of the world’s top universities. She has also spent close to two decades developing asset pricing models for commercial real estate, green buildings and digital infrastructure. 

After a “sophisticated machine learning process,” MIT has uncovered a host of environmental, social and governance parameters – from daylight and views to the level of street-level greenness – influence financial outperformance. 

For example, the Lab has found buildings with high access to views command a 6% rental premium.

MIT’s hard data confirms what many in the industry understand through instinct. Our audience was asked which building features would have the biggest impact on future valuations, with healthy building features coming out on top (33%), followed by flexible, collaborative space (21%), smart building technology (19%), connection with nature (15%) and energy efficiency (12%).

But failing to understand how design features impact long-term valuation can lead to “millions of dollars in lost revenue,” Andrea warned. And she had a clear call to action for real estate professionals who thought they could dodge the data and digital discussion.

How to build a hunting machine

So, what does this data science framework look like? 

Dean Hopkins, Chief Operating Officer of Oxford Properties, and Joanna Marsh, Investa’s General Manager for Innovation and Advanced Analytics, have spent the last two years working together to build “hunting machines.” These sophisticated algorithms can be “pointed” at any real estate market to understand and unearth undervalued real estate.

Rather than “trading information over bottles of wine,” as Joanna said, a hunting machine looking for the next build-to-rent project analyses a data set with six million records and 30 years of data. Financial data – rents, leases, valuations and more – is overlaid with demographic and geographic information, from school profiles to development application histories. The machine can spot infinitesimal changes to the data and “the anomalous pieces of dirt or buildings that can be repurposed,” Dean added. 

“Our models need to be porous enough to take in human weighting, knowledge and understanding and blend it with the data to augment it,” Joanna noted. Humans are then “supercharged” and can set to work on their highest and best use – which is relationship building and negotiation.

A post-pandemic revaluation of the power of place

Real estate values are dynamic. A new development up the street or a smart placemaking strategy can “light up” a whole neighbourhood, Dean Hopkins said. So, how do we dig deeper into the drivers to create new value in the sectors hardest hit by Covid-19?

Everyone who has money invested in a pension or superannuation fund has a stake in the future of our CBDs and the office towers that scrape the sky. But after two years of lockdowns, transforming nine-to-five commercial hubs into central experience districts is a tough task.

Real estate isn’t easy to reinvent, and the complexity and scalability of the property ecosystem can make change a challenge.

EY’s research report, Reimagining our Economic Powerhouses, told us people want city centres that are destinations, not just a collection of office towers. They want spaces that are green and sustainable, and places that celebrate creativity and culture. But how do we respond to this research to enhance asset values?

A “coalition of the willing” is about to trial a range of evidence-based interventions in a tiny space EY has dubbed a ‘microdistrict.’ A site in Sydney’s CBD has been chosen for proximity to public transport, green space, small food and beverage businesses, large office landlords, and room for improvement. State and local governments, planners, asset owners, tenants and retailers are working together to create a brand that enhances value. A digital fabric will harness data, analysis and user insights to understand what works and what doesn’t, and EY will publish a microdistricts playbook to help others build the framework and governance structure, implement, measure and improve.

Three key takeaways:

1. Invest in information: The largest asset class in the world is still basing decisions on instinct. But to understand and invest in a fiercely competitive environment, decisions can no longer be made on gut feel, Dean Hopkins said. Securing an “information advantage” requires speed, accuracy and a “contrarian viewpoint” so assets can be purchased “before the margin is stripped out of them.”
2. Look beyond location, location, location: Dr. Andrea Chegut has spotted a common pattern in the “long tail” of highly valued assets. While location will always underpin real estate values, 50-plus research studies confirm “environmental mindfulness” is a strong indicator of financial performance, Andrea said. Buildings MIT classifies as “smart, green and connected” transact at a 23.7% premium. Healthy buildings lease for 7.7% more per square foot than their nearby non-certified peers. And street-level greenness delivers a transaction premium of up to 10% and a rent premium of 7.8%. Andrea said this data paints a clear picture: “Pay attention to these basic human experience factors as we re-enter buildings.”
3. Embrace a curious mindset: More than half (59%) of our audience said “skills and knowledge gaps” were the biggest barriers preventing property companies from harnessing the power of AI and machine learning for valuations. Joanna Marsh encouraged people to embrace a “curious mindset” and to be “interested in a new way of looking at data.” Andrea agreed. “When people say data science it sounds very abstract. But really it’s just listening to a lot of stories.”

Valuations in the hardest hit real estate sectors won’t rebound overnight. Just over half (51%) of real estate professionals polled by EY Australia & New Zealand and MIT thought valuations in office, retail and hotels would take around two years to recover, with another quarter (26%) expecting a three-to-five-year recovery. Will that buy you some time to build your own hunting machines?