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Big data is the new buzzword in commercial real estate—and for a good reason. Think of it as a vast data mine with both traditional and non-traditional data sets that would be too big or cumbersome for an individual to process alone. Backed by AI, big data can manage and process these large and complex data fields.
Most commercial real estate developers and stakeholders today are leveraging big data to understand new trends and create an informed investment strategy—but big data can give investors more than a macro view of the market. With big data, investors can run a thorough analysis on individual investments to accurately predict returns before ever placing a bid.
It’s almost like seeing into the future, and what investor doesn’t want a crystal ball?
A recent report on technology integration in commercial real estate from JLL said new technology “built around data integration software and AI techniques to drive more granular analysis and process automation” is “leading to new capabilities in understanding, managing and designing buildings and spaces.”
Here are the top ways that investors are using the valuable analytical insights provided by big data analytics for real estate to make investment decisions.
Investment and development strategies typically have a narrow focus. They outline many characteristics, from big picture items, like geographic market and asset class, to more nuanced details, including proximity to job centers, average area income and education and access to transit and amenities. Pinpointing opportunities that align with investment criteria can often feel like finding a needle in a haystack—but it’s also time consuming.
Big data technology manages complex and large data sets through automation, allowing investors and developers to filter through potential investment opportunities that meet a set of predetermined criteria.
Even better, investors can use big data to get infinitely more precise in their search, processing data sets for a micromarket, a street or even a block. When used in conjunction with internal data, investors can curate a comprehensive picture of an asset and make smarter, strategic and metric-driven investment decisions.
Big data can also tap historical site-specific information, like past permits, zoning and former uses that could reveal environmental issues. This data can eliminate assets that don’t support the firm’s investment strategy, highlight assets that do and expedite the due diligence process.
Underwriting & Valuations
Automated valuation models (AVM) have been around for a while, but they historically haven’t met the diverse and specific needs of most commercial real estate investors. New startups are beginning to change that by leveraging big data benchmarks to provide more accurate valuations.
According to research from JLL, these benchmarks include local amenities, ESG accreditations and occupant reviews, all of which can have an impact on valuation. With this data, AVMs can deliver updated property or even portfolio valuations throughout ownership.
During the acquisition process, valuation data will drive efficiency in internal underwriting and provide accurate projections. It can actually differentiate investment strategy and give investors the ability to look at assets differently than competitors by including non-traditional data sets in the underwriting process.
Big data reveals appreciation trends on a specific asset, forecasts pro forma rents on new developments and renovation projects and provides critical insight into demand. It can also look deeper into financial records and cash-flow models that can provide better net operating income (NOI) projections.
Predicting Returns & Assessing Risk
Thorough underwriting and site selection are already a solid hedge against downside risk on an investment asset. But, by harnessing big data, we can do more.
While there is no way to predict a global pandemic that shuts down the supply-side of the economy (sorry!) or any other unimaginable event, big data can evaluate economic and capital trends that can help predict risk factors and enhance returns.
Using proactive intelligence data, investors can better forecast future trends that can impact the success of an investment. This is especially valuable for developers and value-add players that are delivering and exiting from a project in three to five years. Everything from interest rate trends and yield curves to presidential elections, trade and economic growth can affect returns on delivery. According to Deloitte research, data is one of the best ways that investors can manage and mitigate rising risk factors to actually relieve outside pressure on profit margins.
Construction Cost & Timing
Technology integration into construction is one of the biggest trends in CRE to come out of the pandemic. Building information modeling software, drones, and site sensors are all ways construction sites use big data to drive efficiency.
In construction, big data analyzes cost information and site details, labor productivity, supply chain trends and even the weather and traffic patterns that can impact construction schedules.
This data can provide real-time insights during construction to mitigate risk and allow for swift reaction to issues and can also help forecast pricing to keep budgets and development timelines in check.
While the financial incentives are always the most weighted, big data can use sensor data to create safer and healthier job sites and reduce waste.
Tracking Urban Governance
In the transition to smart cityscapes, local governments are using big data to drive flexibility and support hybrid property uses. The data includes everything from mobile phone records that track people's movements throughout the city and energy grid activity to geospatial land registry data.
Cities are making this data more transparent and accessible to the real estate community in an effort to democratize the planning process, according to research from JLL. This is already happening in other global cities. Barcelona and Sydney have launched pilot programs for open data portals, encouraging residents to both utilize and share data.
This data is also driving efficiencies in urban management by connecting infrastructure. Using IoT sensors, cities better understand noise and light pollution, energy inefficiencies and structural defects.
This information is a goldmine for CRE investors. While many of these programs are early in their inception, investors should take early note of which governments have digital strategies and how they are evolving. These could become key investment markets in the future, and the data could inform future developments.
At Northspyre, we understand the tremendous benefits that AI-powered data and analytics can bring to a project—and we have seen it first hand. With the help of Northspyre’s AI technology, our clients have managed more than $30 billion in projects over the last three years, saving up to 6% in construction costs and driving more efficient development timelines.
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