How technology is changing commercial real estate

How Technology Is (And Is Not) Changing Commercial Real Estate

June 6, 2017 3:05 pm

In this quick YouTube video, IBM shows us how Watson, the company’s cognitive computer project, enables a theoretical American homebuyer to digest data that helps her hunt for an on-budget home in Ireland. Quickly evolving trends in big data, machine learning, smart cities, and more are changing the way many industries function, including real estate. What does this mean for the role of humans? Here we explore how technology is changing commercial real estate (as well as the ways technology is not changing it).

To understand the role of your real estate broker we must first understand what technology is doing for real estate and examine both its benefits and limitations.

Technology is making real estate more efficient

Technological tools today make the job of researching market data much easier for everyone. Leading real estate data companies, Xceligent and CoStar, provide insights to market trends based on a great deal of (proprietary) data. Real estate professionals rely on this data to inform their clients and help broker deals. Technology also makes seeing what is on the market – anywhere in the world – much easier for the general public. It increases how quickly people can find properties, select their favorite location, and schedule a tour. In this way, technology is making the process more efficient.

Technology does not account well for exceptions

Zillow, RedFin, and other listing sites are leaders in providing the public with baseline information about the market. These sites pull from scores of data sources like the MLS, recent closings, and property tax valuations to make estimates of a property’s market value. But they nevertheless depend on that data being accurate and consistent.

Outliers can cause errors in the data. County Assessors sometimes make errors in property valuations (which homeowners are responsible for correcting), listings are often different on paper (or in pictures) than they are in person (e.g. a “3rd bedroom” may be non-conforming), or a family member may have sold a property to another family member far below market value. The algorithms that Zillow and others depend upon do not account well for these many outliers.

A real estate transaction is ultimately a human transaction

Real estate shares many tenets of behavioral economics, which studies the psychological, social, cognitive, and emotional factors that drive economic decisions. While real estate transactions are based largely on market data, trends, and numbers, they are not always so simple. Divorces, weather, family politics, the political environment, regulations, and dozens—if not hundreds—of other variables may dictate how a transaction goes down. The role of a broker is to analyze the best data available as well as juggle the tenuous psychological and emotional variables of a transaction.

Real Estate Technology still relies on humans

CompStak, crowdsourced database of comps on leases, is helpful for buyers, renters, and brokers as they conduct research. But it has two key limitations.

First, it relies on crowdsourced information, i.e. the input of human behavior and actions which provide the data. It is not a computer-to-computer, but a human-to-computer model. The data is only as reliable as the information provided to it by the human.

Second, the technology relies on broad, macro-data which is wrought with exceptions, special circumstances, and irregularities (see above). BOOM recently brokered a lease for a building on Pearl Street. In this arrangement, the tenants were offered far below-market rent in exchange for improvements to the building. For CompStack, which cannot process the many variables of this deal, this has the potential to skew the app’s data on comps.

A broker, armed with considerably more details about a transaction than is available in a database, can weigh this information with what the data provides to provide authoritative information on actual market values.

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