Analytics

How Can I Leverage Predictive Analytics in Commercial Real Estate?

How Can I Leverage Predictive Analytics in Commercial Real Estate?
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Leveraging analytics and predictive analytics is how commercial real estate investors can take advantage of the information available to them. Rutherford D. Rogers described it well when he said, “We are drowning in information and starving for knowledge.” 

Predictive analytics has come a long way in the past few years for industries such as marketing, insurance, and healthcare.  But, the commercial real estate industry has made limited progress catching up with technology. Alarmingly, nearly 80% of institutions and commercial real estate investors manage nearly $24 trillion in assets using spreadsheets and disconnected systems. Real analysis is difficult at best with this method, and furthermore, it is time-consuming to compile the information. Another problem is that the information is quickly outdated, so it is a tedious task to stay current.

Nucleus Research completed a study across multiple industries, and they found a revealing correlation in companies that utilize analytics. For every dollar someone spent on analytics, they received an average return on their investment of $13 dollars. Now, in an industry with such a high asset value, utilizing analytics has the potential to dramatically reduce workloads and boost profits. Imagine being able to focus on things that will provide your business with the greatest value, reduce risk, and increase returns, so you can run your business more efficiently. Analytics could do that.


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More Facts on Analytics

The analytics: Competing in a data-driven world was a report produced by McKinsey Global Institute (MGI) back in 2011. This report discussed the growth of applications with analytics, and MGI admits they underestimated the full potential of where the power of analytics would take us as a society. Several industries stand out in their adoption of predictive analytics, but the commercial real estate industry is among the later adopters.

The commercial real estate industry is beginning to gain traction, and new sector leaders are beginning to rise. The brokerage segment of the commercial real estate has embraced predictive analytics to some degree, but on the other hand, the commercial portfolio management trails in their adoption of predictive analytics. In part, this delay is due to lack of accessible data or data that resides behind firewalls. But, the world is shifting.

To begin, let’s explain a few terms, so you can gain a better understanding of descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.

Type of Analytics

Descriptive:Provides insight into the past showing what has happened during a given period.
Diagnostic:Provides insight into the past showing why something happened during a given period.
Predictive:Shows what might happen in the future based on past data.
Prescriptive:Identifies the best actions one should take based on past data.



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What is Descriptive Analytics?

Descriptive analytics is probably the most commonly used analytics, and they provide information about what happened in the past. Good businesses everywhere rely on these metrics to understand how their businesses have performed. Common descriptive analytics in the real estate realm are Loan-to-Value (LTV), Debt Coverage Ratio (DCR), and Return on Investment (ROI). These metrics show how your assets have performed in the past, or at least to the present moment. Their past performance might provide you a sense of how these same metrics will perform in the future, but they are not predicting the future.

What is Diagnostic Analytics?

We are most familiar with diagnostic analytics when we think about looking backward in time to analyze or diagnose why something happened. Doctors diagnose all the time and share what has caused us to have certain ailments. By understanding why something happened you can take corrective future action. In the realm of real estate, for instance, one might look at previous leasing data. With that, you might discover a pattern in filling open leases. Perhaps you would find when you only advertised a certain way, you were less likely to fill the lease. This is powerful information. It provides evidence to make a positive change in your business. Diagnostic analytics is the foundation for both predictive and prescriptive analytics.

What is Predictive Analytics?

Predictive analytics are forward-looking analytics. They predict what you might do or might like in the future. One of the easiest examples to understand this concept is to look at Netflix. Netflix now provides the viewer with information about how closely their previous viewing habit matches other TV shows or movies. For instance, Netflix is telling me right now that I am a 97% match for Captain America: Civil War based on my previous viewing habits. Likely, Netflix is right. Of course, Netflix could be wrong. Yet, with this suggestion, I have reduced my risk that I am wasting my time on a TV show I do not like.

stratafolio-analytics-for-commerical-real-estate

How could this same concept be applied to your real estate portfolio? What if based on the trending stock price of one of your tenants and their paying habits, you could predict the likelihood they would renew their lease? Or if they are more likely to request to renegotiate their renewal terms? That is powerful when you are trying to forecast your future earnings. In summary, predictive analytics highlights your risks and allows for you to plan accordingly.




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What is Prescriptive Analytics?

The final type of analytics we are going to talk about today is prescriptive analytics. This is an area of huge growth globally over the next decade, and in its simplest form, it prescribes what you should do or provide advice on the best course of action based on your predictive analytics results. Perhaps the easiest way to think of it is predictive analytics on steroids. There are elements of predictive analytics, experiments, simulations, and even artificial intelligence (AI) involved that suggest the best decision. 

The Current State of Affairs in Commercial Real Estate

Analytics bring better decision-making, better planning and increased profits for your commercial real estate portfolio. From all accounts, most industries are only acting on a small amount of the opportunity available, but commercial real estate asset management is far behind the pack. Investors who use separate accounting and property management systems face the biggest uphill battle. They must address first, the time-consuming task of combining their data to see the current status of their portfolio, but unfortunately, these same investors are highly limited on what they can do for systematic analytical predictions for the future.




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Leveraging Analytics in Commercial Real Estate

In summary, the use of analytics in your commercial real estate investments presents a great opportunity to have a competitive edge among your peers. Using historical data in combination with analytics can quickly help you spot previously hidden pitfalls within your business. Further, having a clear understanding of these pitfalls can help you predict different scenarios and future trends. Not to mention, analytics can also help you make data-backed decisions faster and reduce risk.

The commercial real estate market is a fast moving one where time could be the difference between winning or losing big. There have been many disruptive technologies through the past century, and analytics in the commercial real estate industry is starting to make waves. The question is will you surf the new wave or drown in it? The future is bright, and Stratafolio is here to help make the future a bit brighter. 

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Jeri

Find out why companies average $9 in returns for every $1 spent on analytics.
 
 
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Jeri Frank

Co-founder and CEO of STRATAFOLIO, real estate investor, cyclist, cat lover.
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Summary
How Can I Leverage Predictive Analytics in Commercial Real Estate?
Article Name
How Can I Leverage Predictive Analytics in Commercial Real Estate?
Description
Commercial real estate data analytics is ripe for disruption. Descriptive analytics have long been used but predictive analytics is the future
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Publisher Name
STRATAFOLIO
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