Analytics - Friend or Foe

By Dean Boyer  |  February 20, 2020

Analytics - Friend or Foe

The real estate industry is still in the early stages of adopting data analytics as an insightful strategy for managing investments, operations and finances. The objective of such adoption is to analyze a myriad of data relative to location, pricing, appraisals, industry trends, competition, vacancy and more in order to derive valuable insights. The challenge is in (A) acquiring the data and (B) developing the analytics necessary to achieve these objectives. A real estate firm’s relative success in building data analytics is the basis for the title of this article: “Analytics – Friend or Foe?”

Analytics as a friend is an easy concept to accept when the analytics in question deliver insightful, actionable results. However, analytics processes that are time-consuming and deliver little value are a foe to any firm’s objectives. In either case, the determination of analytics as friend or foe is ascertained by a firm's ability to do the following:

  • Acquire pertinent internal and external data.
  • Validate the accuracy and completeness of the data.
  • Ask questions of unknown things rather than things that are known.
  • Build analytics that are actionable.
  • Apply what is learned.

Real estate firms often have limited technology resources at their disposal, and the list above requires a certain level of information technology fluency. Therefore, it is not unreasonable to assume that when a real estate firm is considering the adoption of analytics, they are also making a build versus buy decision. However, even in cases where that determination has already been made, it is still essential that any analytic investment account for these key elements.


Data exists both inside and outside your firm; the key is to understand what data is required to deliver valuable results. For example, location analytics benefit from a whole host of external data sources that provide information about demographics, traffic flows, schools, taxes, etc., and each of these sources may or may not improve the quality of your results. Source, accessibility and cost are all contributing factors in the acquisition of data; the key determining factor in whether the data acquired is beneficial or not is why the data is being acquired.

What is the data strategy behind your data acquisition?


Not all data is collected equally! Accuracy and quality of data can have a huge impact on the resulting insights. For example: an analytic that is date-dependent, such as occupancy, can be corrupted if any part of the data is transposed or entered incorrectly. Data quality and accuracy concerns apply to both internal and external data. To correct the issues associated with internal data, real estate firms are well served by establishing a data governance committee to provide oversight and guidance in the management of data. In regards to external data, the adage “BUYER BEWARE!” is still applicable.

What is your current data governance strategy?


Introducing analytics is all about gaining insight and discovering things that were not previously known to the firm. When using analytic technology, the tendency is to ask for reports that depict information that is already known by the firm. For example: “What is the current cash flow?” is a question often asked in the development of financial analytics. Answering that question is achieved by running a set of standard reports that compare accounts receivables to account payables. A better question to ask is, “When will there be a change in the cash flow that will impact current reserves?” By altering the question to address an unknown outcome, the analytic can deliver greater value.

What questions are you trying to answer by investing in analytics?


Analytics by design are either descriptive, diagnostic, predictive or prescriptive. Descriptive analytics depict the current state of the business. Diagnostic analytics identify potential issues in the current flow of the business. Predictive analytics project potential outcomes based on past trends and current actions. Prescriptive analytics identify which future outcomes best meet the goals and objectives of the firm. Each of these types of analytics may or may not be valuable. Value-based analytics stem from the actions taken from analytics. For example, an analytic that identifies 10 rental units in a residential housing complex will be vacant this month is informative, but has little value if the residential housing complex usually has two or more vacancies. However, if the analytic were not only to identify the 10 units, but also indicate that these same units have been vacant for 50% of the life of the complex, then action can be taken in terms of pricing, renovations or some other benefit focused on making the units more desirable. If the information obtained from an analytic prompts a call to action, then the analytic has value. If no actions are forthcoming based on the information, then the value of the analytic is minimal.

What actions do you expect to result from your analytic investment?


While the concept of analyzing data and using analytics has been around for a couple of decades, the methods and techniques for analyzing data are fairly new. The “data-centric organization” is a huge paradigm shift for most firms. Back in 1960, Richard Leghorn first used the phrase “Information Age.” Since then, the term is used to delineate the Industrial Age from our current state of doing business. While the Industrial Age was known for advancements in automation and process engineering, the Information Age is still struggling with trying to understand the value of data and its impact on business. To assist in the paradigm shift from process-centric to data-centric, firms are investing in data literacy pro-grams that assist employees in understanding the power contained within data. Empowering employees to take informed actions based on analytics improves overall investment, operational and financial performance.

What is your firm doing about data literacy?


Investing in analytics can have a positive impact on your real estate business. Whether your real estate firm is involved in commercial or residential real estate or investments, real estate analytics can help you gain insights into pricing, locations, appraisals, occupancy, competition and more. The key to successfully building out analytics is to have a well-thought-out data strategy. Remember before beginning any analytic project to ask yourself these five questions:

  1. What is the data strategy behind our data acquisition?
  2. What is our current data governance strategy?
  3. What questions are we trying to answer by investing in analytics?
  4. What actions do we expect to result from our analytic investment?
  5. What is our firm doing about data literacy?

If you can answer each of these questions satisfactorily and believe that your firm understands what is required, then you will find analytics to be an outstanding friend that grows with you as your organization grows. If you are unable to answer these questions or believe that your answers are missing the mark, then it is time to step back and invest in developing a data strategy; otherwise, you may find yourself fighting your analytics and struggling to justify the investment.

About Dean Boyer

Dean Boyer

Dean Boyer is a Director in the Technology Services Group at Marks Paneth LLP. To this role, he brings more than 30 years of experience in information technology and data management, with a focus on data science and business intelligence. Mr. Boyer’s diverse background in technology and digital solutions enables him to advise both for-profit and not-for-profit organizations on how to harness data to increase operational effectiveness and improve organizational performance. His experience includes product... READ MORE +

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