Data is king in today’s business environment and student housing is no exception. But the lack of technology solutions purposely built to address the unique investment and operational issues of student housing firms suggests there is a real opportunity for Proptech and Fintech startups.
A quick survey of the sector’s leading operators suggests they largely rely on a hodge-podge of systems that have been cobbled together, but further exploration also shows progress in several areas.
Market data attract institutional capital
One area where student housing providers are able to tap into technology to inform decisions is through existing market-by-market databases that compile college application figures, enrollment numbers, occupancy rates, pre-leasing trends, new construction and more.
These databases are altering the way investors make decisions and have eliminated the time- and shoe-leather-consuming process of collecting market data phone call by phone call. The availability of market data at scale has helped attract institutional capital into the industry and replace “gut feeling” investment decisions with real-time information.
Market databases have “played a huge factor” in the influx of institutional capital into student housing, says Jonathan Reyes, assistant vice president at Harrison Street Real Estate Capital in Chicago.
Data platforms aren’t the only reason for these investors’ burgeoning interest, but the easy availability of market intel has attracted their attention and that interest has created more liquidity and what Reyes calls a “more competitive dynamic” in the industry.
As investment capital enters, good data becomes even more valuable for land acquisition, development, investment and property management purposes.
Digging into the data
As operators increasingly rely on third-party market data, the question must be asked: does a marketplace of competitors who are all tapping the same database result in a herd mentality, driving up asset prices in obvious markets and missing or neglecting harder-to-find opportunities elsewhere?
Student housing executives say no. And they have reason for faith in their own differentiated strategies. They’re going beyond the market databases in ways that are proprietary, nuanced and surprisingly old-school.
One executive says that while he’s a little embarrassed by the old-school nature of his solution, he has built a “massive” spreadsheet that he “customizes the heck out of” to analyze data and decide where to invest and where not to. The company has looked at off-the-shelf software and concluded it’s just not flexible enough to do the job they want done.
Casey Petersen, chief operating officer at Peak Campus in Brookhaven, Ga., says, “Real estate gets managed at the local level and you have to be there to manage it.”
At Peak, market data is used to set the general direction of investment opportunities, but Petersen says it still takes people going out to target markets in person to validate development and investment decisions.
“All of these systems are only as good as the data going in,” he says. “The boots on the ground are where we can actually dig into the nuance of what the data are telling us that we couldn’t necessarily do at a high level using a third-party.”
Despite that approach, Petersen is anything but data-shy
In fact, he says, Peak has a data warehouse that’s updated nightly with a download from multiple company systems, including property management, human resources, accounting, training, compliance and more. The equivalent of two full- and one half-time employees in the company’s IT department spend all of their working hours figuring out new ways to aggregate the company’s data across different platforms and analyze it to meet decision-makers’ investment and property management needs.
“We can query the data as we see fit and use that information to drive our business in the way we want to drive it,” Petersen says.
The data warehouse isn’t new. So far, it’s been used primarily to identify and measure what already exists. In the future, Petersen wants to take that farther, beyond descriptive and into predictive. The goal is to use data modeling to anticipate market trends before they occur.
“If we can help our clients and investors better forecast what’s going to happen with their assets, they are able to make their investment decisions on a better, data-driven basis,” he says.
This points to an evolving need in not just the student housing sector but in the multifamily industry in general. As firms bring more data analytics in house, there may be a need to create jobs that we don’t even know how to describe today. But it seems apparent that the both sectors will increasingly rely on more data scientists to help process all their data.
The next big thing
Predictive modeling isn’t the only tech solution on student housing’s wish list. Indeed, a wide variety of creative ideas to modernize student housing management and investment are out there in what might be called the cyber-ether.
Reyes favors greater data transparency among the industry’s competitors, a strategy he says would not only help investors understand markets more quickly, but also translate to the property level, giving everyone greater insight. Transparency would require many more operators, including both corporations and mom-and-pops, to open up their books to the tech companies that aggregate the information and make it available to their customers.
“It’s a tough ask,” Reyes said, but “the more transparency there is in the industry, the better.”
Students and their parents might benefit from more transparency in a different way. Reyes points out that there’s currently no student housing mobile device app that allows housing shoppers to research their options when they visit colleges and universities.
“That doesn’t exist in our industry right now,” Reyes says. “It would be tough, but I think it definitely could happen.”
Better pricing models
Reyes’ quest for greater transparency links directly to what’s on The Scion Group COO Mitchell Smith’s wish list: a yield management system for student housing that uses high-speed computer algorithms to analyze real-time demand and supply metrics and calculate revenue-maximizing prices on a dynamic basis. But the biggest barriers to creating such a system for student housing are a relatively small market with a high degree of fragmentation.
Smith explains that, in a typical market, 25 to 30 percent of students rent purpose-built institutional-quality student apartments campus, and the rest are commuters or occupy non-professionally managed units or second bedrooms. Thus, a yield management system likely would lack information on the 70 to 75 percent of the market offerings.
Another complication is that if the available data is comprised of 20 properties owned by three companies using different property management systems, no one tech company would have enough data to feed the algorithms. In addition, such limited data sources might raise antitrust issues.
“That doesn’t come close to what you need to create a yield management program,” Smith says.
Pulling it all together
Smith also spotlights what he sees as another gaping hole in student housing technology, that is, a software solution to measure, monitor and manage the customer experience, which, he says, “dramatically impacts the value and price (customers) are willing to pay.”
A system that combined market intelligence, property management and customer experience data would be a big win, Smith suggests.
“There’s a significant opportunity for the right tech company to create a real solution for our industry,” he says.
The bottom line is that data means business intelligence, whether it comes from property management systems, custom data-slicing-and-dicing algorithms, or third-party market data aggregation companies. And today, business intelligence means better management and investment decisions.
But there are clearly still opportunities for additional sector-specific solutions. Student housing providers hope that some of the $12.6 billion in venture capital funding directed at commercial real estate last year (up from $4.2 billion in 2016) finds its way into their industry.
This article provided by NewsEdge.