Michael is Chief Executive Officer of LendingHome.
Real estate has begun to undergo the same sort of radical disruption that brought profound changes to the auto industry, credit cards, insurance and even Major League Baseball.
An information revolution isnât responsible. Neither is artificial intelligence (AI) or quantitative analysis, a la âMoneyball.â Driving this massive change is the merging of all three factors. This is the same kind of convergence that disrupted and transformed other financial sectors, including payments (PayPal, Square), personal loans (Lending Club, Upstart), student loan financing (Sofi) and retirement investment (Personal Capital).
AIâs introduction into real estate has been closely covered by the media, but what hasnât received enough attention is the scope, the sheer breadth of the transformation thatâs on the horizon. If real estate follows the same course as the aforementioned sectors, I believe the technologists and entrepreneurs who build innovative new real estate solutions, as well as their investors, stand to forever redefine the industry. The size of the opportunity canât be overstated.
Zillow, the web real estate marketplace, reported that the value of U.S. housing grew by nearly $2.5 trillion in 2020, driving the total worth of U.S. housing stock to $36.2 trillion. In May, Zillow reported that three-quarters of homes (76%) were on the market in April for less than a month before being listed as pending, and nearly half (47%) were on the market less than a week.
The good news for consumers is that data-driven analysis will also bring more benefits in the form of a more efficient, transparent and cost-effective real estate market. If history is a reliable indicator, those companies in real estate who possess access to the greatest amounts of high-quality data and do the best job of interpreting that data will almost always fare better than those who rely on old-school, outdated methods.
Quants team with techies to create a revolution.
To understand how real estate arrived at this point, it might be helpful to watch the hit 2011 film Moneyball, starring Brad Pitt and Jonah Hill. The story chronicles the pioneering efforts by the Oakland Aâs baseball team to build a winning club through the use of statistical analysis. The Aâs made the playoffs in 2002 and 2003 while spending far less than rivals to acquire players.
With the help of quantitative analysis, the team stripped away flawed thinking about the playing skills that should be valued and, by doing this, dramatically changed the game. This example of how data analysis improved and reshaped an industry is likely the most famous but not the first. Following World War II, a group of experts often referred to as âquantsâ helped turn around a then struggling Ford Motor Co.
Quantitative analysis relies on mathematical and statistical techniques to identify and predict trends, help determine the allocation of resources and assess operational performance. This kind of analysis isnât new to real estate, but several events supercharged the number crunching.
An ocean of data pertaining to real estate became available when municipal governments began posting this kind of information to the internet. New services have emerged that aggregate the data. That, combined with the significant increase of information made available about consumers, means we possess far more knowledge regarding property values, home buyers, renters, commercial property and mortgage rates, as well as some things you might not expect, such as the value of chimneys, granite countertops and mahogany doors.
In business today, knowledge truly is power.
Vast quantities of housing information have existed for generations, but the volume made it nearly impossible to work with. AI tools help change that. They can scour mountains of data to unearth critical revelations. As a result, AI has become the nexus between data and decisions. You may possess piles of information, but if you canât translate that information and turn it into action, you have nothing.
If youâre a technologist, the CEO of a real estate company or an investor, you might be wondering about the tools needed to participate in real estateâs AI revolution?
For starters, youâll need the money and other resources required to collect and store enormous amounts of information. For example, everywhere you connect with a customer, the data must be collected and stored. Then you need to hire the people who can manage the data and extract value from it. This isnât easy. Skilled machine learning engineers are tremendously sought after, and typically donât come cheap. But if you find them, odds are theyâll be worth every cent.
Finally, to reap the full value of AI and data analytics you must have the courage to act on the insights that they yield. Iâm not trying to be dramatic. I truly believe this is one of the reasons some companies fail with AI. Returning to the Moneyball example, the Oakland Aâs werenât the only team with access to the data and analytical tools the Aâs used to win, but they were the ones who had the courage to act on it.
Because decision-making within companies frequently involves culture and belief systems, sometimes the revelations AI uncovers contradict leadershipâs instincts or preconceived notions. In those cases, managers must decide who theyâre going to trust.
If youâre going to go with your gut, then donât waste your money on data. Youâre better off just doing what youâve always done. Be warned though, itâs my experience that those who embrace data can be a step ahead at spotting trends, market shifts and discovering opportunities. Ask yourself if you want to be the Oakland Aâs of your business sector, creating unique value and performance, or one of the traditionalist teams that spent more and won less.