Data in CRE Part II

July 22 4 min read

Data and Information in CRE

­­The impact of technology on the commercial real estate (CRE) industry is a vast subject. Here we discuss the role of data and Information and how Artificial Intelligence and Machine Learning might impact the CRE world.

Can Technology Replace Brokers?

No, robots will not replace brokers, but they will definitely replace some of their tasks. Across all industries, the way we work is already changing because of Artificial Intelligence (AI) and Machine Learning (ML). In part 1 of this series AI in CRE, we considered how the CRE industry could benefit from embracing these technologies. Here, we discuss data and its importance for AI and ML in the context of building design and construction, followed by an examination of the numerous impacts on the industry. Many wonder as technology advances, if machines will take over our deals, our properties, and even our jobs.

Data is Everywhere

AI and ML run on data, and data is everywhere. But what do we garner from the vast collections of data and how do we use it to generate information? Often, data is collected without an application in mind, and then it is not or cannot be used effectively. Without analysis or application, data is useless.

How do we move past this challenge? Relevant data should be collected at appropriate sample sizes, from reliable sources. When that data is analyzed well, it can illustrate a connected world, showing patterns and trends that indicate a cause for action, to seize opportunities or mitigate risks. To go a step further, we use that data to inform programming and problem-solving applications.

Low-Quality Data Equals Reduced Reliability

We capture accurate, representative data, and then edit and update our data sets to ensure what we are working from is the most current information available. When outdated inputs are used or when data collected is not representative, the value of AI and ML, that relies on those inputs, becomes questionable.

Gathering all of the information makes decisions easier. Collecting as much information from many perspectives or reliable sources about a particular situation will give the decision-maker, in this case, the AI engine, more certainty so it can make better recommendations for us to act on. Lower quality data equals a less reliable outcome.

Applications for CRE

Data applications across the CRE industry are almost limitless. In part 1 AI in CRE, we examined property management operations. Here, we consider building design, construction, and brokerage, and the technology applications in each area.

Design and Construction: What is the IoT?

Buildings are being designed and constructed considering IoT, the Internet of Things, where smart sensors and devices are integrated over ethernet (PoE, WiFi, and 5G) to provide connectivity across the mechanical electrical, and plumbing (MEP). Technology is integrated to blend in with operations during the design stage of these “smart buildings” as they are designed and constructed.

A smart building uses sensors to monitor occupants, their movements, and density for a given space so that it can monitor and adjust the lighting and shading, the heating, and cooling. Energy efficiency can be managed with smart sensors connected devices—the sensors are constantly collecting data and providing that sensor data to its central system. ML is used to monitor and learn from different situations and then make recommendations for maximum efficiency.

For example, if the northeast corner of a building is hotter than the rest of the building in the mornings from solar gain, the ML could learn over some time to send additional cooling to that one area, without the need for manual observation or manual adjustments to controls. The cost savings to clients comes from maximizing efficiencies and minimizing costs. The benefits to property managers include time-saving on repetitive tasks and the ability to generate meaningful tracking and reports of resource usage, comfort levels, and to meet wellness targets more easily for their buildings.

Brokerage: Knowledge is Power

Early awareness of various physical or economical events impacting our clients points us to strategy options in terms of preparation, business development, and risk evaluation. How do we connect those events with data? Some options are through AI or ML. For these tools to play a meaningful role, we use them to turn data into information and information into action augmentation to inform our strategy and actions.

We might think we know everything about our clients and prospects. If we store information only in our minds or a record system only available to ourselves, opportunities can be missed. Imagine, our prospect posts on social media or has a press release announcing they are expanding into the Southwest in the next five years. Given the number of media channels and outlets, that news flash could be missed. But if we leveraged a news scanning AI tool such as a Robotic Process Automation (RPA) tool that sifts all available data and informs us that ABC company is expanding, that is a game-changer for brokerage professionals. Suppose we integrate Bloomberg information to sift all the public information about public organizations, we could analyze financials for growth or contractions and cross-reference that information to forecast future CRE needs and opportunities for our brokers to reach out from an informed position.

There are various ways that business development opportunities can be enhanced with AI, RPA, and ML. Central to all of this is collecting reliable data.

Is AI coming for your job?

A recent report by the Altus Group notes although 75% of CRE executives think automation will lead to certain job losses, 71% of those executives believe it will bring new roles revolving around greater value-add tasks to the industry.

Machines will not do everything in the future, but they will do more. If some tasks are removed from our day, or at least minimized (who doesn’t want less admin?), we can concentrate on relationship building which is of prime importance in CRE. Applying our experience and knowledge, or the creative and innovative aspects of our work are the more enjoyable part of our jobs for many of us and are key differentiators in relationships with our clients. The parts that bring about change or success, working at a higher level that adds value—that cannot be replicated by AI.

Combining the pattern recognition and programming powers of ML and AI with human intelligence could be the ideal solution. This industry, like many others, relies on relationships and trust. Even with applied technology, CRE transactions will continue to be directed by experienced individuals who can make sense of the market, use information, data, and AI to show confidence through knowledge, and guide and offer their clients the right opportunities at the right time.

Across all industries, individuals who are trusted by their clients, those who are creative problem solvers, who can evaluate options and risks, and make a sound judgment using data inputs including the use of AI and ML—those career-minded professionals will thrive.

In serving real estate requirements for the future, we must adapt to an increasingly data-driven approach. To thrive and provide clients a true advantage, we must leverage data to work at a higher level that adds value.


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Brian Medricka

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