Is CRE Ready for the Big Tech Transformation?

Experts at ULI’s Europe Conference offer a snapshot of the industry’s efforts to embrace technology and detail the challenges ahead.

Clockwise: James Scott, Gabrielle McMillan, Andrei Girenkov and Ross Bailey. Image via Urban Land Institute

Data was the main theme at the Innovation Mindset panel of the virtual 2021 ULI Europe Conference, where James Scott, lead researcher at MIT Real Estate Innovation Lab, led the discussion. Panelists Gabrielle McMillan, CEO of Equiem, Andrei Girenkov, senior managing director of technology at Greystar Enterprise Services, and Ross Bailey, CEO & founder of Appear Here tried to find answers to this compelling question: Are real estate companies on track for the great tech leap forward?

Some catching up to do

Are companies innovating fast enough? What are the steps taken for transforming a slow-moving industry? “There is a lot of (digital transformation) going on thanks to COVID-19,” said Girenkov—who transitioned to real estate from a variety of technology roles in the financial services industry and has a clear view of where the real estate industry is in terms of data innovation and where it needs to head to. According to Bailey, whose company is an online marketplace for short-term retail space, real estate was lagging 10 years behind in terms of tech innovation when the coronavirus pandemic broke out, and the industry has a long way to go. But even the fact that technology has become such an important topic in the real estate world “is a bit of a tipping point on its own,” he noted.

“Realistically and candidly,” real estate is only at the beginning and still lags behind other industries, according to McMillan—who has been leading Equiem, an experience platform focused on engagement solutions, flex space management and smart buildings—since its inception in 2011. There has been a lot of change in operation digitization and an increase in demand in the adoption of digital transformation, McMillan said, but “the ball was rolling before COVID-19,” and there was already a huge shift happening prior to March 2020.

Challenge accepted?

When it comes to challenges in adoption, McMillan pointed out the top historical obstacle: “You need to have the right people sitting on the consumer’s side for (adoption) to work, because otherwise, you have a massive gap in knowledge, experience and capability.” Another issue is legacy systems that in many cases are not even cloud-based and the structure of the data isn’t easy to work with. Furthermore, the tech aspect of the real estate industry is “quite nascent,” McMillan noted.

“The real estate sector is sort of a closed-off group and hard to penetrate,” compared to other sectors that tend to be somewhat more open to collaboration, Bailey added. And while real estate relied on optionality before, the industry is now being pushed to adopt technology by outside factors, such as certain tech features required to be implemented into new developments. This way, real estate players are now compelled to share and work together in order to navigate the current crisis.

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But who pays for and who benefits from this digital transformation? Is it property owners, managers or tenants? According to Girenkov, the pandemic has forced industry players to adopt a “we just need to get this done” mindset, focusing on monetizing the process and making sure everybody wins. “Forward-looking insight is the purpose,” he pointed out. Greystar, for example, has invested in an enterprise data platform to tie together different vendors and presenting the data back to analysts. When working toward predictive analysis, companies should “pay the price to get to a level of maturity when you can take advantage from your data insights.”

The art of contextualizing data

When making business decisions, ensuring that the best quality data is available is paramount, Girenkov said. To that extent, the goal should be collecting data from different sources that can later be meshed together and “presented for consumption in a consistent way.” Furthermore, data should be used to analyze the past and predict the future. Data is a lagging metric, according to Bailey, and it won’t replace someone’s mind; instead, it will reduce the possibility of making the wrong decision. “Collecting data is complicated,” and having too much of it only confuses the user, McMillan noted. Contextualizing data is a lengthy process, but at the end of the day, that is the main point.

Privacy concerns are also an intricate aspect of digital adoption. “A big aspect of data governance is knowing what your data is, be thoughtful about what you capture and how you store it, how to prevent access and how to recover (data) in case of a breach,” Girenkov explained. There is “often a mistrust of landlords,” Bailey added, as many retail tenants are reluctant to share data, but value comes from that in the long run.

Where to now?

Going forward, real estate is in for quite a metamorphosis, if industry participants are willing to implement changes. “We’re in a good spot, we can use the more mature technologies and accelerate real estate digital transformation,” Girenkov noted, adding that data science is the biggest opportunity for the industry. “Data is not worth much unless we can wrangle it and we can clean it up, ensure high quality and get insights,” he concluded.

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According to McMillan, “real estate needs to start thinking like a product company or retail consumer company,” with the focus on the end-user’s daily experiences. The industry needs to shift its mindset and transform its business model—while many investors think of properties on a spreadsheet and not as a product that is experienced by people on a daily basis, there is high value in getting closer to the consumer and providing a great experience. And in order to make that happen, “if we believe that it will create more value, new people must be brought in, because it’s not the people who traditionally worked in real estate,” she added.

“Data is not complicated,” Bailey said, noting that real estate companies will have to decide whether they are an asset holder or an operator. “Operators will have a bigger job coming out of this. If the owner wants to become an operator, data will be integral to that.”

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