As data becomes easier to attain, the relationship aspect of commercial real estate is becoming less of a competitive differentiator.
Despite the long-awaited and much-heralded embrace of tech in the CRE industry, there are still some noticeable gaps in what type of technology is being adopted. For example, a new Deloitte Insights report points out that most CRE managers and investors continue to make heuristic, or instinct-based, decisions rather than ones informed by data analysis.
There are several reasons why. Habit is a powerful explanation. “The industry has long thrived on relationships, which is how many investors have traditionally gained access to unique information,” according to the report. “Traditionally, most investors have combined this information with their gut instincts to make investment decisions.”
Other reasons why investors may not see the need to embrace data analytics is that they are unaware of the wide variety of datasets available for CRE or perhaps lack the analytical capabilities to generate insights from that data.
Even for those who are aware of its capabilities, there are challenges to adoption, Deloitte Insights writes. Some may be unsure where to start; others may not know which new skills and capabilities should be added to begin. Most CRE executives are certainly savvy enough to worry about the uncertainty of a return on investment.
No longer competitive
So a heuristic approach to decision-making continues. But Deloitte Insights notes that this approach may not remain competitive for much longer. With increased availability and transparency of data, it says, access to information may not be a competitive advantage anymore. Investors will find they have a growing number of blind spots as they seek to diversify portfolios. For instance, Deloitte Insights notes, some of the newer business models, such as short-term rentals for co-sharing spaces, have different dynamics and a limited track record of performance and returns. “For investors and managers evaluating these new business models, relying on intuition may not be enough,” it says.
Indeed, there is much more data available today than there was even just a few years ago. “Information such as net effective rents, leasing spreads, lease comps, market demand, and tenant information have now become much more accessible and granular,” the report says. Also, alternative datasets from IoT sensors, social media, geospatial information, and satellite imagery are increasingly being used.
How it works with CRE
There are many ways data analytics can be applied to CRE. They can be used in acquisition, disposition, and portfolio management processes to manage rising risks and complexities more effectively and mitigate fees and margin pressure, according to the report.
For instance, during due diligence, investors can use diagnostic analytics to understand the correlations between property performance and user movement within and around the property, weather conditions, and energy prices, the report says.
Another example it gives: retail mall investors can use traditional property data around performance, combine it with alternative retail sales data from mobile sensors, social media, and physical store sales, and use machine learning algorithms to analyze consumer buying behavior for a geography or to profile retail tenants.
“Advanced analytics can help investors and managers better understand the sources of risk—from asset level, to macroeconomic, to regulatory—so they can draft appropriate mitigation measures,” it says. “For a diversified CRE portfolio, this could involve assessing risk and return across multiple property types, geographies, and regulators.”
How to get started
For any company that isn’t in the tech sphere, investing in a new—and particularly—advanced application may seem daunting. Expert consultation certainly may be warranted. In the meanwhile, here is a cheat sheet that can get executives thinking about what they may need.
Develop a data management plan. Deloitte Insights suggests investors and managers first assess existing processes to identify areas in which they are lagging and those in which data analytics and AI would likely most benefit them.
“For instance, some investors may need data analytics to improve their deal sourcing and bidding capabilities, while others may use it to help generate smarter portfolio management options.” Part of a data management plan also calls for investors and managers to better understand the different types of datasets and analytics solutions currently available.
“They should ensure these tools are compatible with the existing architecture and conduct due diligence of data sources in terms of quality and potential privacy risks.” Also, investor firms should identify the skill sets they expect to use for advanced analytics, Deloitte Insight says.
Embrace a data-driven mindset. Deloitte Insights readily acknowledges that adopting a new approach and changing behavior throughout an organization is not easy. “C-suite leaders will need to clearly articulate the benefits of utilizing alternate datasets and analytics,” it advises. “They should act as change champions, taking ownership and being accountable for setting a data-driven culture. Communications should focus on the vision, strategy, and benefits of data-backed decision-making.”
It also advises adding a chief data officer or equivalent to the C-suite to signal how seriously the organization is taking this effort.
Author Erika Morphy, globest.com
