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How Data Can Improve Commercial Real Estate Investment Opportunities
By Narendra Srivatsa ‚ÄúIn God we trust; all others must bring data.‚Äù ‚Äî W. Edwards Deming, statistician and author of The New Economics for Industry, Government, Education As the Internet economy becomes yesterday‚Äôs news, it‚Äôs clear that millennials are bringing a generational change to markets. The impact of the shared economy and discussions about the ‚ÄúInternet of Things‚Äù aren‚Äôt limited to dynamic business models such as Uber and AirBnB. The commercial real estate market‚Äîone of the world‚Äôs oldest investment vehicles‚Äîis undergoing dramatic changes on a similar scale. With the data and analytics tools available today, investors can analyze these trends and make necessary adjustments more easily. Instead of resorting to ‚Äúgut feeling‚Äù and the rudimentary methods of past decades, investors can now work with fresh insights powered by data and analytics. The recent upheaval in the commercial mortgage-backed securities (CMBS) market is a prime example of the need for data. It was nearly impossible to predict the large CMBS market reduction in the first-quarter 2016 year-over-year volume just by going with a gut feeling... The situation was a warning that the mortgage industry needs to heed in the immediate future: nearly $200 billion in what‚Äôs come to be known as the Great Wall of Maturities of CMBS may potentially come to fruition in the next year or two. How is that wall going to be addressed in light of the CMBS market slowdown and the tightening of commercial real estate investment? More data and analytics tools are likely going to be necessary. Levels of data In general, the mortgage industry frequently views data and analytics on two major levels: macro data and address-level data. Macro data can help identify new market opportunities and could forecast a CMBS market decline. Address-level data provides insight on how to place capital within a given market. Yet there are several things about data that need to be understood. Data often needs to be analyzed for veracity, volume, and velocity before investors can move forward with any confidence.
- Veracity: Poor-quality data results in bad outcomes. It‚Äôs important to have the right verification of the data.
- Volume: If data is statistically insufficient for an analysis, the analyst may make too many assumptions, which can often lead to bad outcomes.
- Velocity: The pace of specific data available over time and the changes in data values constitute velocity. If the required data isn‚Äôt available at sufficient speed or the analyst can‚Äôt see any changes over time, then it‚Äôs static input. Dynamic changes in data often provide greater insight.
- socioeconomic resilience of a given region
- infrastructure fragility
- consumer potential
- capital potential
- market access and adaptive capacity
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