How Big Data, Mobility Impact Property Values
Without a shot fired, the Mobility Revolution has begun. Big Data, smart transportation and new mobility technology are affecting property owners and communities in myriad ways. Projecting the effects of these changes on future property values is difficult, but a look at recent innovations suggests where we are headed.
Many property investors associate the Mobility Revolution strictly with driverless, interconnected autonomous cars. This view misses the larger, unfolding disruption story. Indeed, the shift is transforming the transportation of goods and people. Paraphrasing former U.S. Transportation Secretary Anthony Foxx, “smart transportation” is not about concrete and steel alone; it’s about how people want to live.
Mobility is more than a transportation issue. It involves the digital marketplace that now competes with retail real estate, with growing implications for retail property values. Offices offering shorter and alternative commuting options to workers are more valuable than those that don’t. Mobility also involves ride-sharing services and the personal choices we make to get from one place to another.
Deloitte researchers wrote in 2015 that change is coming to transportation whether we’re ready for it or not. “You can see it in public-sector investment, intelligent streets and digital railways, automakers’ focus on next-generation vehicles and smart mobility services, and the widening recognition that the ‘information everywhere’ world will utterly disrupt the transportation status quo.” The Wall Street Journal predicts that autonomous vehicles alone could reshape one in nine American jobs.
The U.S. Department of Transportation heralded the revolution in December 2015 with the announcement of the “Smart Cities Challenge.” Over 70 mid-sized cities responded, sharing ideas for an integrated, first-of-its-kind system that would use technology and the Internet of Things (IoT) to help people and goods move faster, cheaper and more efficiently. Progressive governments like Columbus, Ohio, are using Big Data to guide infrastructure investments.
There are two primary areas of mobility disruption: one is data intelligence, or the ability to obtain better-quality data; and the other is new modes of transportation.
Data intelligence captures and processes Big Data to deliver real-time analytics of roadways, helping communities deal with increasing congestion. Improving access to a retail site or reducing commute times to an office or industrial property can dramatically increase its value.
Big Data and analytics needn’t seem threatening. Nearly 20 years ago, the Oakland Athletics baseball team famously used the Big Data concept of “moneyball” to identify and hire promising players on the team’s small market budget.
More broadly, professors Daniel Kahneman and Amos Tversky helped create the field of behavioral economics by showing how to use Big Data studies. Fortune 1,000 companies increasingly incorporate Big Data insights into their strategies.
Think of the Mobility Revolution as “mobility moneyball.”
New and developing data collection techniques offer previously unobtainable and useful transportation insights, tracking where vehicles start or end their journeys, the distance travelled, elapsed time and points used to access roadways. Smart transportation companies beta-testing in the United States, Israel, Estonia and elsewhere are demonstrating how to acquire and use these new insights. Many drivers now use Waze to choose travel routes and monitor live-time traffic, thereby traveling more efficiently.
If the data is obtainable, why wouldn’t a city, like a driver accessing Waze, use it to make smarter, more informed transportation decisions? Similarly, why wouldn’t an assessor, like a smart property owner, use this data in valuing properties?
Policy makers and property owners must apply the right questions and analysis to collected data to make appropriate investments. They must be open to changing uses of data and to using new transportation systems as aging transportation models fail. The Smart Cities Challenge recognized that new and improved forms of transportation, not simply driverless cars, offer incredible opportunities.
We may be describing 20th century fantasy, but the Challenge recognized that today’s developing transportation technology is tomorrow’s reality. Few retailers had heard of drones 10 years ago, for example, but some retailers are now considering drone product delivery. How many had heard of Waze 10 years ago? The next bus rapid transit (BRT) or personal rapid transit (PRT) systems may follow a similar path to prominence.
Communities should consider all transportation solutions, even those still under development, before committing tens of millions of dollars to solutions having multi-decade ramifications. Relying solely on data generated by traditional trip counters and opinion surveys leads to less well-informed decisions.
For example, new and theoretical rapid transit technologies promise substantial improvements over the PRT system developed in 1975 in Morganton, West Virginia. However, it is critical that the technology a community adopts eventually qualify for federal grants. Theoretical solutions that are decades away are not solutions.
Some proposed transportation technologies may make operating costs affordable to public-private partnerships rather than requiring ongoing government subsidies. Residential developments with multiple commuting options are clearly more valuable than those that lack alternatives. Varied transit options increase property values by improving livability.
Smart cities will use smart mobility technology to attract new business. Professors Tversky and Kahneman proved that data-driven decisions outperform subjective decisions based on subjective beliefs. Armed with newly obtainable data and the prospect of new transportation modes, property owners can make smarter economic decisions regarding a property’s value.
Property tax implications
E-commerce has dramatically reduced the need for, and value of, retail space. Smart retailers now use customer analytics to increase sales. Smart property owners are adding more restaurants, entertainment and other “experience” tenants to boost traffic, something unavailable to online sellers. Smart transportation should be a part of that strategy.
Big Data and improved analysis in projecting values will revolutionize the ad valorem property world.
Assessors valuing properties as of a specific valuation date try to discern a market pattern to apply to the hypothetical sale. They have used data, though not Big Data, for years to make initial property valuations in the “mass appraisal” process.
Similarly, private companies are beginning to offer automated valuation models. Current mass appraisal techniques and automated valuations work well in valuing homogeneous properties such as tract homes in a subdivision, but not as well in valuing unique properties.
Mass appraisals of commercial or industrial properties are frequently challenged. Assessors build models based on property types and obtain data from subscription services such as CoStar Group and multiple listing services. On the cost side, assessors use services like Marshall & Swift to build similar models. Analyzing Big Data is in its infancy, but clearly evolving.
The keys to analysis are obtaining data and then asking and answering the right questions. No matter the model used, however, property tax disputes will continue to involve assessors, property owners and their counsel, who must analyze available data to value an individual property. Big Data can reduce, but not eliminate, subjectivity.
But ready or not, mobility moneyball and the revolution are here to stay.
Morris Ellison is a partner in the Charleston, S.C., office of the law firm Womble Carlyle Sandridge & Rice LLP. The firm is the South Carolina member of American Property Tax Counsel, the national affiliation of property tax attorneys.