Five new technology solutions in commercial real estate
The real estate industry has been more resistant to technological change than other industries, but with so much at stake—us$ 54 trillion globally—the first firms to break through with leading edge technology stand to gain a fortune.
Technological solutions that will provide a competitive advantage include predictive analytics, smart building hardware, and the Internet of Things. Today Lamudi intends to educate you about the 5 new technology solutions in commercial real estate.
TECHNOLOGICAL ADVANCEMENTS WILL TRANSFORM INVESTORS INTO OMNISCIENT BUYING MACHINES WHERE NO PURCHASE IS LEFT TO INTUITION AS PREDICTIVE ANALYTICS ADVANCES, AGENTS WILL HAVE AN OPPORTUNITY TO BUILD DATA IN DIFFERENT LOCATIONS; NOT JUST THEIR TOWN, OR CITY
The Internet of Things (IOT)
No discussion about the future of real estate technology can commence without mentioning IOT.
The technology that works with smart sensors and apps integrated with a feeder system is going to change how we design, use, and maximize the efficiencies of buildings. In the future, if a building encounters an issue a signal will be communicated to a management center, where a work order will be generated automatically; no need to call a technician. Clients will be better able to manage their capital spend as the predictability of equipment replacement will be easier to monitor, by using sensors on commercial boilers for instance.
Predictive analytics
Knowing what the future holds is a dream of every investor, but predicting what lies ahead may not be a fantasy for much longer.
Predictive analytics can be cleverly used by real estate professionals to decide on the next big investment project. By analyzing information from several data points such as workforce trends, demographic patterns, and the cost of capital a broker can much more easily convince a CRE firm that a building will work well in their portfolio.
As predictive analytics advances, agents will have an opportunity to build data in different locations; not just their town, or city. Before an investor makes a decision to buy say, office space, he will expect to have the future rental rates in many competing areas to make a more informed decision.
Real-time market comparables
Companies like Compstak are leading the way when it comes to live data for CRE. Investors can easily track competitors, discover undervalued assets, build bespoke market reports, spot acquisition opportunities, and model future trends. Technological advancements will transform investors into omniscient buying machines where no purchase is left to intuition.
Networks for office space
The use of office space has historically been inefficient. New options are available to connect individuals with a broad network of office space suppliers.
Even if you are a two person practice that needs just four hours of office space per week that is now possible, and landlords can aim to get full occupancy for their building. The leading companies in the sector offer real-time space availability in a flexible marketplace thus reducing the costs and challenges that come with traditional leasing.
“We get a lot of inquiries from individuals looking to rent an office just for two or three people, but the options are limited if its just a short term arrangement,” said Kian Moini, managing director of Lamudi— the global property platform.
The demand for flexible, temporary, and costcutting corporate leasing is growing, and companies like Lamudi welcome the tech advancements that meet this new office space dynamic.
Machine learning
Deep learning promises to change CRE in a dozen ways, but one that will save time and costs is a data platform that will support the lease completion process; allowing firms to be compliant with their country’s accounting standards in the easiest possible way. Artificial intelligence will help at every stage of the sales process. Experienced agents will have the data to make educated assumptions about their clientele and market.
They will know the best time to send an email or make a call, or what tone to use with each customer. It might take a lifetime for an agent to learn the nuances of each particular market, but a machine can process reams of input data in seconds. The machine will be an agent’s loyal servant in the future.