Data analytics is a broad term but can be explained by four different types of analytics, Descriptive, Diagnostic, Predictive and Prescriptive. The first two techniques, Descriptive and Diagnostic analysis are currently being used in CRE, however, the exponential growth in computing power will only grow and be more important. Descriptive analytics refers to the use of past data on markets and properties including occupancy, vacancy, rents, loan to value ratios, debt service coverage ratios, equity returns, discount rates, etc. Descriptive analytics provides data as to how your CRE assets and markets have performed in the past and this is data commonly available and used in the industry.

The second common analytical technique used in CRE today is Diagnostic analytics and this looks backward in time to determine why various positive or negative things happened to a CRE asset. It could be changes in the market from new property competition or positive leasing trends that help a highly vacant building achieve full occupancy. Diagnostic analytics is used to find various historical patterns that affect a property or market. Many Silicon Valley start-up firms are using big data analysis as a Diagnostic tool to find patterns in real estate values and market changes.

The third and newer analytical technique is Predictive analysis. This is analysis that seeks to look forward and predict future events, based on past data. This type of analytics is in its infancy, but with the further growth of computing power and artificial intelligence, should be commonplace in the CRE industry in 7-10 years. Predictive analysis may allow a leasing broker to input a public tenant's financial documents and predict at some probability level that the tenant will renew or expand its lease. A rudimentary form of Predictive analysis is already in use on dating sites, that match people by their past input data or Netflix that suggests shows to watch based on your prior viewing habits. Predictive analysis will be a very powerful tool to not only predict potential future events and reduce the risk of CRE investment and ownership.

The fourth and newest analytical technique and the most influential is Prescriptive analysis. Prescriptive analysis is in its infancy and won't be common for a least 15 years. It will be able to use data gathered by Predictive analytics (see above) and tell you what you should do or the best course of action to take, given a real estate transaction. For example, if an investor is looking at buying only one of several potential office buildings in different markets, this technique will provide advice on the best property to buy in terms of return, value creation, rent growth, occupancy, etc. The decision criteria will be extracted from the reams of data provided by the other three analytical techniques and analyzed by the Prescriptive analytics process.

Today, the accounting structure of most CRE firms is haphazard with different systems at the property, portfolio and asset management level. Some firms have top accounting software packages like Yardi and AppFolio for their property level data but use an Excel spreadsheet for the portfolio level data and the calculation of returns. Also, most of the acquisition and financing analysis and proformas are in Excel or Argus and not integrated into the overall accounting system. In the next 10-15 years, all of the above analytical techniques will be integrated into one accounting/finance system, which will be great for the CRE industry and make it more efficient and less costly. It will allow real estate practitioners to make better decisions and plans and increase profits in a CRE portfolio.