Brandon Taubman is the CIO and Co-Founder of Stablewood Properties, a real estate investment firm that couples data analytics and subject matter experts to identify or uncover novel opportunities in the market. The firm is built on a solid technology and data foundation, reminiscent of Taubman’s 15-year career as a data scientist and financial engineer. Prior to Stablewood, Brandon Taubman served as Associate General Manager for the Houston Astros where he contributed to the team’s rebuilding efforts using data analytics to revolutionize scouting and player development. His career started on Wall Street where he worked for firms including Ernst & Young and Barclays valuating derivatives conducting risk assessments.
How did you get started in this business?
I have always had a strong connection with data science throughout my career which has enabled me to apply that knowledge across industries. I started out in Wall Street investment firms as an analyst following the completion of my education at Cornell University.
How does your company make money?
- Stablewood uses analytics to figure out which available-for-sale assets are mispriced (too low) compared to intrinsic value; i.e. value investing
- Stablewood uses analytics to determine where values (rent, prices) will rise in the future so that we can acquire assets in those geographies before waves of institutional capital poor in
- Our technology platform allows us to automatically and instantaneously underwrite thousands of deals to find the more investible ones.
How does your company go about acquiring new customers?
- Our customers are our investors; the people that provide us with capital to invest in assets that we hold; as well as the people buying assets from us when we sell
- The key to acquiring new customers in private equity real estate is having a reputation and track record of success – which our CEO Glenn Lowenstein offers on the back of 35 years of stellar investment
- The other key part of acquiring customers is by giving them a better way to invest. Our platform offers a range of investor relations tools which are best-in-class and create a great user experience
How did you work your way up in this business?
Up until 2013, I worked as Assistant Vice President for Barclays, still on Wall Street and happy to be applying my knowledge to complex situations. On the side, I had created a fantasy baseball data analysis system that caught the eye of a few key figures in Major League Baseball. That led to an opportunity to provide data analytics and leadership for the Houston Astros (while I put away my fantasy baseball pursuits).
What made you want to work in this industry?
After working with the Astros for several years, I turned to the field of private equity real estate. I think there is a very big untapped opportunity in this field because there is so little aggregated public data. Contrast that with the decades of statistics we had to work with in the MLB. With Stablewood, we’re working to establish those data precedents and use them as a distinguishing factor against the competition to find novel ways for our clients to invest. I find that challenge riveting and exciting.
What is it that you feel makes you good at your job?
Seeing the results that are coming from our efforts to combine data science and subject matter expert input. Real estate is an industry where you can’t overlook the value of on-the-ground, expert input. But in my experience, data can work hand in hand with those findings to help direct more sound decision making. In my day to day, I work to identify and validate data sets that can give us a real edge when it comes to investment. And when those insights are confirmed or validated by our SMEs, that feels amazing.
What are the perks of working in this type of business?
We have a lot of flexibility as far as how far we want to take technologies especially in the realm of commercial real estate. Very little has been done in the past to apply data science to these investment decisions. Being able to be a forerunner in this space with Stablewood is exciting and we’re just scratching the surface of what we think we’ll be able to achieve as we continue to build out our proprietary systems.
What are the disadvantages of working in this field?
Again, the lack of data. It was almost jarring for me when I started out to realize just how little information has been in the industry. So many transactions happen behind closed doors. But our team is convinced that this disadvantage can be a differentiator for us as we work to find undervalued investment opportunities that data, or lack thereof, previously overlooked.
What’s the most rewarding part of your work?
Growing out our approach where data and experts meet together to direct business decisions has always been rewarding for me, regardless of the industry. For example, when I was with the Houston Astros, it was great to see your data presented to the players along with the buy-in of the coaches and have that player be willing to try a change in their swing or their pitching delivery. These small changes, spurred by data, can have a great impact on outcomes. Getting that buy-in and watching the data come to life through the changes it recommends is incredibly rewarding.
Where is your industry headed? What excites you about the future of this line of work?
Real estate has been in the stone ages when it comes to technology and data analytics, and it’s been that way for far too long. It’s only inevitable that firms like ours will continue to be founded and work to leverage trends and data in new ways.
What advice do you give people who want to get into your field of work?
Be your best marketer. One of the mistakes I made when I was starting out was letting the data do all of the talking for me. While that makes total sense as a data scientist, it can leave your ideas or concepts falling flat to others who don’t have the same background as you. These are the people you want to have carry out your ideas, so take the time to market them sufficiently: explain the cause and effect of the change, the areas for improvement, and how they individually stand to benefit wherever possible. This will help you bring your data-driven ideas to life for successfully.
Are you willing to be a mentor? If so, how should someone contact you?
Yes, I am willing to be a mentor. Please contact me via LinkedIn.