One of the longest running trends in industrial real estate is the shift of ownership from private hands to institutions. Traditionally, insurance companies, pension funds, and real estate investment trusts (REITs) would purchase new developments and industrial parks after they had been leased and stabilized. It served as both a guaranteed exit for entrepreneurial developers as well as the way investors would acquire property to match long term obligations.
The long-term trend of institutionalization metastasized after the Great Recession when the industry faced low interest rates and the search for yield. Suddenly, institutions grew a fondness for all things industrial. To make sure there were enough assets to buy, they began opening their standards to older and smaller properties by expanding the definition of “Institutional Grade.” Today—at least in major markets—a 25 year old, 50,000 square foot building is now a highly sought-after product type by institutional investors. Continued low-interest rates and below trends economic growth signal that the returns from real estate are still relatively attractive and that institutional activity will continue.
The significance of this trend has become evident to many SIORs. Owners and users—once the dominant buyers of older industrial buildings—have been shunted to the sidelines as they can no longer compete on pricing, terms, condition, and availability. The pathway to wealth by owning and occupying your own building is a vanishing commodity for many business owners.
For SIORs, the trend to institutionalization is a commission bonanza. During the early years of my career, large-scale institutional investors steered clear of older, inner city properties, instead focusing on larger, modern distribution buildings with major credits. Asset sales of this type would normally be brokered by the capital markets teams of major brokerages, or directly amongst the developer/investor nexus. In other words, brokers like me—independent, geographically focused, with an owner/user clientele—were locked out of the big institutional deals. Now, institutional investors are 30 percent of my business—and growing.
Evidence of this shift can be seen at the SIOR Greater Los Angeles Chapter meetings. What were once almost completely dominated by SIOR brokers, meetings are now 50 percent attended by the leading REITS, advisors, funds and private equity investors in the industry. Most have significantly boosted their acquisition teams from the abundance of the investment dollars flowing into industrial. The most lucrative part are the owner/user buildings—those still in private hands—that have become the acquisition targets of big investors.
We are at peak momentum for the shift from private ownership to institutions. This trend, however, will not last once all the assets have been transferred. It mirrors the corporate sell-off of industrial plants in the mid-1980s to early-1990s. Once all of the plants were shut down and sold, it permanently reduced the influence corporations and real estate directors had on industrial real estate markets. Today, once those industrial properties leave private hands, there’s no going back to the owner/user market of old.
It’s important to note that many of the largest buyers are starting to use machine learning, artificial intelligence, and “Big Data” in their searches for properties. These are methods that have been taught by their peers in the stock and bond industry. The results on practitioners are fee compression and a reduction of human interface. Many of the largest buyers are using data and analytics to go direct—willing to pay brokers if they are part of the transaction—but at the same time entitled by their models to find the deals wherever they can.
Strong money flows keep the business churning. Success goes to those who can locate or create the deals, but once those buildings are sold, we will need to search for new opportunities in the industrial real estate universe. Enjoy it while you can.
As seen on SIOR Pulse
Geodata is widely used in many commercial internet applications like Yelp, Google Maps, Twitter, Foursquare and Factual. Many of these web services match your phone’s location to their own mapping programs. In most cases location data is an aid to sell goods and services. I use the same relationship between point data and the connected internet to find more real estate deals using MappSnap.
By using your phone’s location services, anyone can snap a picture and that image will appear at the exact location where the picture was taken. In the field, we routinely take pictures and videos to catalog entire industrial areas. By processing image, location, and parcel data, we forecast which properties will potentially become near term deals and have available space. As we develop better techniques, Artificial Intelligence and Machine Learning will augment human judgement to make better predictions with our data sets.
Location is a natural and intuitive way to organize and archive real estate information. Longitude and latitude coordinates are freely accessible due to Global Positioning Satellites. Visually, whether on satellite or map view, you can comprehensively see the market area coverage. Once images are loaded, most commercial Content Management Systems (CMS) like WordPress, Drupal, or Joomla, will let you automatically create content for each property in an easily retrievable format using common search, location and database functions. I can take individual pieces of point data and grow it on a transactional platform that serves up content depending on specific criteria and inputs. In addition, once data is captured, cleaned and formatted, it’s easy to manually run sorting and selection operations for specific properties you are seeking. The next logical step is to feed this same data to cloud services for more intelligent analytics. In other words, GeoData is the first step to cataloging the industrial building universe for purposes of archiving and transacting.
Geodata comes embedded with many mathematical functions. Most familiar is radius search. For any property, it’s easy to record GPS data and use it to focus on nearby geographies. This allows precision searching under the principle that the closest people are the most interested in any given location. More advanced GIS programs have more complicated alogrithms. One example from the hedge fund industry is the use of alternative data to guide investments. In one case, Thasos is a data company that uses geofencing to analyze shopping mall traffic and predict retail sales. Similarly, point and traffic pattern data is used to measure truck traffic to find the busiest freight nodes to evaluate warehouse locations. In the case of MappSnap, we use location data to find properties in the “off-market” and make individual determinations on the investment and development potential.
Geodata is an underappreciated real estate tool because it only takes a small amount of technical expertise to start. GPS is a free and ubiquitous protocol, maintained by the U.S. Government, that works seamlessly with property. Mobile applications allow you to be in the field and serve up real time location data to a CMS program. Recently, we have been experimenting with live-streaming on the street and research operations in the office for on-the-ground immediacy.
As we invest more in geo-data field operations our biggest obstacle is financing, but even more problematic, is the shortage of capable programmers who can combine web, mobile, geo, and analytics. There are several open source mapping programs that are very useful, including MapBox, Leaflet, and Open Map, but all have limitations when directed to specific commercial applications like the ones we are developing. Luckily, it’s a virtuous cycle that with more geo investments, we find more opportunities that in turn allow for more development. Please contact us if you would like to be a collaborator or user of MappSnap. We are always looking to share.