Let’s look at how you can utilize big data in commercial real estate. Over the past few years, new computer technology has made data analysis — assessing and using datasets that are too large for conventional analytics — increasingly practical for businesses in and outside the tech industry.
Big data can provide new, profound insights that you couldn’t uncover with less comprehensive information. New analytics techniques are also making nontraditional, unstructured datasets more accessible. As a result, new tools and approaches have made it possible for landlords and real estate companies to take advantage of the tech.
Some commercial landlords are already using data analytics for marketing, building management and investing. Over the next few years, the tech could radically transform the way commercial landlords buy real estate, market to potential tenants and oversee their properties.
Using Data Analytics for Intelligent Building Management
In some buildings, property owners are already using big data and new analytics technology to make building management more efficient and eco-friendly. For example, a building owner might install new Internet of Things sensors that collect minute-to-minute data on humidity, temperature, lighting and air quality. In aggregate, this information could give building owners and their tenants a nearly real-time picture of where renters might be underserved — like inadequately ventilated or poorly lit rooms. The data may also show where building resources may be going to waste Property managers may use this information to make building lighting, cooling and heating more efficient — shutting off lights and cutting temperature control in unoccupied rooms. In some buildings, this information will help smart HVAC and lighting systems manage these changes automatically, allowing building owners to reduce costs and improve the building’s energy efficiency.
The right tool might also help building owners identify areas for potential improvement. For example, they may find rooms that are harder to heat or cool due to poor insulation, hallways that may have inefficient lighting setups or areas where natural lighting may allow tenants to cut down on their use of electric lights.
Preventing Building Systems Failure With Big Data
IoT sensors and big data analysis can also help detect energy fraud and failures in metering systems — both of which can lead to inaccurate billing measurements.
Big data is “smart” enough to identify failures in other building systems — potentially reducing maintenance costs or preventing costly repairs. Data from air quality and humidity sensors, for example, can give building owners an idea of when HVAC systems are beginning to fail, or when simple fixes are necessary — like a new filter. These sensors might enable a kind of predictive maintenance strategy, which could cut down on the need for frequent maintenance checks and help reduce the risk of sudden and unexpected building system failure. This use of data can even help some buildings qualify for green building certifications like LEED certification. Recently, these certifications have become a significant draw for tenants looking for ecofriendly buildings. In some areas, they’ve also improved buildings’ property value by a substantial margin.
The adoption of analytics in commercial real estate is ongoing, but not mainstream yet. Even in buildings where systems are already collecting data, it mostly goes underused. One survey found that 77% of smart building owners store the data their building management systems collect, but 42% of those owners don’t analyze that information.
However, before too long, the tech is likely to be a standard fixture of modern buildings. Current industry estimates forecast that, by 2035, there may be as many as 45 trillion connected sensors in operation in the built environment. All these sensors will be collecting massive amounts of data, at volumes that will make big data critical for commercial landlords.
Data Driven Marketing of Commercial Real Estate
Big data could also transform how commercial landlords market to and negotiate with potential tenants Collected market data might give landlords a better idea of which potential tenants are looking for commercial space in their area, or how much they should charge for a particular building based on floor space and building amenities. This information could help improve marketing efforts — allowing landlords to create targeted advertising campaigns or adjust rents to better reflect tenant income and local property values.
Data Analytics for Real Estate Investment
Soon, this data might also help landlords develop new investment strategies. Market analysts have found that there may be significant, untapped power in nontraditional data for real estate investors and commercial landlords. big data analysis could evaluate information drawn from new sources of real estate data — anything from residential surveys to online restaurant reviews to the number of permits issued to build swimming pools in the area.
Insights in that data can reveal hyperlocal patterns in the real estate market — giving investors a better sense of how property values may change over time. These patterns might help them create more informed investment strategies, and develop the best possible understanding of the local real estate market. Insights into market trends, coupled with data on comparable properties, may also help improve estimated property valuations. Better estimates might enable real estate buyers to develop better bidding approaches, helping them secure valuable properties without overspending.
How Big Data May Change Commercial Real Estate and Property Management
Over the next decade, the big data market is likely to grow significantly — and the industry will probably produce even more data-based solutions for commercial landlords. Right now, landlords can already use this data and IoT tech for building management. With the right information, building owners can adjust and optimize systems to cut down on wasteful energy use, reducing costs and making buildings more eco-friendly. It might even be possible to automate entire buildings.
At the same time, data analytics can also help property companies improve their marketing and investing efforts. More comprehensive data sets drawn from traditional and nontraditional sources can give businesses a better picture of their local real estate marketing — allowing for more effective targeted advertising and informed investment strategies.
Rose Morrison is a residential and commercial real estate writer and the managing editor of Renovated. To see more of her work visit: https://renovated.com/