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Things You Need to Know about Real Estate & Big Data Integration

Read first then watch the video, please! For a few years now, I have been hearing all this talk about “Big Data” and have had little or no understanding of what Big Data is, until now. I thought I would explain my understanding of Big Data to supplement my interview with Neel Naicker, which is included with this post. First, let’s talk a little about what data is in the context of commercial real estate.


  • By itself and without context, it has little or no value. If I said, the building used 2,000 watts of power per day, without any other information or experience operating buildings, this bit of data would have little or no use to you. However, if you were able to compare this data to power used in other buildings of a similar type, construction and geography, you may have some use for the data.  Other examples of data that may have value to CRE professionals include, lease rates, energy consumption, average amount of hours worked per square foot by employees, average sick days taken by employees of tenants, and revenue per square foot, to name but a few. To make the example more personal, assume that I started a diet and I told you that I consumed 2,000 calories? What would that mean to you? But what if I told you that I consumed 2,000 calories at one sitting by eating an entire box of Oreo cookies? What if I said it the calories were from lean meat or vegetables consumed over a four day period?  Would any of the additional information have any meaning to you if you wanted to know how I was doing on my diet?




  • Collection of data has been going on over time immemorial. Cavemen had painted on walls telling stories of how they killed their food
    Image from Wikipedia

    Image from Wikipedia

    with spears and arrows. The ancient Egyptians wrote hieroglyphics on stone and later with papyrus and animal skin telling of the great conquests of their pharaohs. Pen & quills were used to keep financial records in paper ledger books in the 18th century and I used a paper tear-off system to keep track of my billable time as an attorney in the late 1970s. Now, most of us are familiar with Excel spreadsheets. For the most part, all of this data has been collected on disparate and non-integrated systems with little opportunity to look at everything from a holistic perspective. Holistic has been defined as

  • “characterized by comprehension of the parts of something as intimately interconnected and explicable only by reference to the whole.”

  • Big Data, from the perspective of commercial real estate is not just one or two pieces of data, such as the gross revenue of a building over an annual basis or rent per square foot.  It is the accumulation of hundreds of thousands of pieces of data, if not tens of millions of pieces of data relating to a building or portfolio of buildings.  It could also  include information about buildings within a city, region or country.  It includes little bits of information broken down to it’s least common denominator or the largest, grossest numbers. It is anything that might be relevant to a building operator, owner, tenant or community, including information that relates to the health or productivity of people utilizing the building or people in the surrounding neighborhood. The trend is for countries, states, municipalities to require building owners, operators and tenants to keep track of certain minimal data points including energy consumption.


  • Over the years, businesses have been collecting data. However, we have only been scratching the surface.  Now, more than a Googolplex of Data is available for analysis.  But what will we do with all of that data? The collection of data is still meaningless unless and until we do something with it to make it meaningful and actionable.  This is the third element significant element of Big Big DataData.  The mashing and parsing of all of this data that we are collecting in such a way so that we can analyze it for our own best use.  How can I make the building most efficient?  Can I tell and provide evidence to prospective tenants that employees who work in my building are 10% more productive than employees in other buildings because of the health and safety systems or lighting? How much might that be worth to a tenant over the life of a lease?


  • Software already exists that allows the user to rearrange information in ways deemed most useful for their purposes. The anticipated consequence of rearranging information is the ability to see the data and the significance of the data in ways not previously imagined.  The purpose of looking at information from different perspectives is to guide you to your best decisions, much like an accountant or lawyer might. How many times have you said to yourself; “gosh, I never thought of it that way”? Now with Big Data, and the software to make the data relevant, we have the ability to recognize opportunities that we have never recognized previously, like the microscope was to the discovery of bacteria and the creation of penicillin.


  • The most impressive part of the Big Data puzzle today is how software developers are focusing on simplicity and intuitiveness. Users need to be able to access information without needing a degree in computer science and with the least amount of training.  It should come almost as second nature.
  • I imagine that, in the not too distant future, data will be delivered to us without the need of pre-programing.  Algorithms will be written to allow the software to, in essence, think on its own and suggest ways that we should want to view the data rather than the way we think we want to see the information.

Hal: “Howard, I want you to look at this.  I think it is important.”

Howard: “Hal, leave me alone, I’m thinking”.

Hal: “Howard, I am serious.  You haven’t looked at this data this way before.  I think it’s a good idea, really”.

Howard: “Ok.  Your right Hal.  This is a good idea.  Now why didn’t I think of this?”

Hal: “Because I’m smarter than you”.

Howard: “Thanks Hal, you can shut down now. I’ll take it from here (and let everyone know how brilliant I am)”.

The video that is included in this post is from my interview with Neel Naicker, CEO of AMP Technologies. I already understood that AMP was about organizing data on a building and portfolio basis in such a way that owners, managers and could slice and dice the data to better understand how to get the maximum performance out of their properties and portfolios. Neel gives a more in depth look at how AMP obtains Big Data and makes it available to its users. Neel explains that we are still not fully automated and that there is still the need for the human touch in accessing the information, particularly as it relates to “legacy” data (that information that exists on paper or Excel Spreadsheets and other older forms of media). We also discuss “integration” of the data that he collects into various systems, such as a CRM or leasing systems, “all in a way that is very intuitive…….” and gives the organization better visibility into its data

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