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 How Brandon Taubman, Data Scientist at Stablewood Properties, Uses Data to Drive Success

Brandon Taubman has been instrumental in shaping Stablewood’s innovation strategy, utilizing data science to manage properties and evaluate acquisitions for our clients. Specifically, we have created a “Prism” platform that combines a customized big data analytics engine with proprietary white-label cloud-based applications for each of our platforms. This allows us to analyze data in real-time and ensure that we stay true to our clients’ promise to deliver them “outperforming real estate returns.” Data science helped me identify our target investments. We’ve learned that successful landlords have three attributes. The first is that they have an eye for finding good deals on undervalued properties.

Data science applications in business

Brandon Taubman: While this article is focused on commercial real estate, this concept is the same for all industries and applications. We can apply data science to make informed decisions about our assets in business. And from there, we use a version of agile or test-first development to iterate on our decisions. I often see one particular application of data science in the business world in marketing and advertising. The ideal situation would be if a marketer could use data science to identify when their target market is at a low point and the time is ripe for influencing their purchasing decision to buy their product.

How did Brandon Taubman become so well-versed in data science and its applications to commercial real estate?

Taubman: My work in baseball started by analyzing scouting reports, statistical analysis and have a particular eye on the Mets team. I would take these findings to Major League Baseball teams and explain what they could do to make better decisions based on the data and information available. Their feedback has been phenomenal, and it’s something that’s become second nature. At Stablewood Properties, I realized that the same platform could be applied to real estate investment decisions.

How has data science helped the Houston Astros win a championship?

Brandon Taubman: I credit a data-driven approach to building talent. As we built the Astros, we created a science-driven organization. When you study a successful baseball team like the Astros, figuring out their strengths and weaknesses is the key. If you watch baseball, you’ll see the common denominator: baseball players all have strengths and weaknesses. But the common denominator is where you find your weaknesses or strengths. It also includes how you work on those weaknesses and strengths through teaching or training or related.

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