Brandon is a data scientist and financial engineer with 15 years of experience in investment banking, sports analytics, and real estate. Before joining Stablewood, he charted and led the analytics effort for the Houston Astros, where he progressed to Assistant General Manager and oversaw the research and development and scouting departments.
Brandon began his career valuing complex credit and equity derivatives for Wall Street firms, including Ernst & Young and Barclays Capital. Brandon holds a Bachelor of Science from Cornell University.
1. What is Stablewood Properties all about?
Stablewood Properties is about real estate investment done differently. We couple subject matter experts and insights from the market with data analytics to better target investments and remove inefficiencies from the overall process. We’re a firm founded by a team of real estate experts and data scientists, so the blend is conducive to different perspectives. And in an industry that is, quite frankly, laggard when it comes to using data analytics in decision making, we’re seeing opportunities to find undervalued or overlooked properties in private equity real estate. We’re also able to adapt to market changes more effectively by relying on data outcomes tied to other predictors.
2. How do you separate yourself from your competitors?
That use of data analytics and our willingness to combine subject matter expert guidance with what the numbers say helps us stand out. There are fewer data points to work within private equity real estate than other industries. But what we quickly realized is that we can build out the research and hard data to drive our decision-making and get ahead of the competition. We do this with proprietary systems and applications, bringing together some of the best minds in the business.
3. What was your first business idea and what did you do with it?
I’m not sure if it counts as a business, per se, but my first independent effort working with data analytics had to do with fantasy sports. I have always been a big baseball fan and an avid fantasy sports player. After college, I realized that I could apply my data analytics background to create a system that would allow me to use statistics to make the best decisions for my teams and improve my outcomes. This became such a successful wagering system that my use of data analytics to make decisions for player performance caught the eye of people in Major League Baseball.
I eventually left my roles on Wall Street, where I specialized in investment banking and equity derivatives, and joined the Houston Astros. So you could say that my first independent business idea in fantasy sports helped pave the way for a career change.
4. What are your plans for the future, how do you plan to grow this company?
We’re working on growing Stablewood’s technology stack with proprietary systems that can help us aggregate and work with the data lacking in our industry. There’s a severe lack of data quality among private equity real estate. So many transactions are done behind closed doors. But while the barriers to building accurate and reliable systems are high, they’re not impossible. We truly believe that we can use this to get a head start and outpace the competition.
5. What is your favorite quote?
Opportunity is where luck meets preparation.
There’s always an unknown, unpredictable element to the work we do, the choices we make, the paths we ultimately go down. But doing your due diligence and taking the time to prepare can augment and exponentially improve your outcomes once luck does strike. I was fortunate, for example, to come across the right connections that led me to work with Major League Baseball. But I was also prepared with the background, skill set, and mindset to succeed. It helped me make my mark on a team that ultimately won the World Championship for the first time in 2017. That was pretty exciting.
6. Can you recommend one book, one podcast, and one online course for entrepreneurs?
Superforecasting: The Art of Science and Prediction does a great job explaining the limitations of data analytics and the importance of using data along with the experience of experts in the field to make the best decisions you can no matter what discipline you are working in.
Data modeling is important, but so is real-life experience and input from people who are seeing the trends, and learning feedback on how things are really performing.
7. What are the top three mistakes you made starting your business, and what did you learn from them?
I was incredibly (if not overly) competitive when I started out. I think that having a bit of balance between fostering a competitive spirit and focusing on what others can bring to the table is something I have learned over the years.
I was also highly reliant on data, as is understandable considering my background in statistics and economics. But the people aspect of the business, that importance of the subject matter expert, and the human side of things when evaluating what the data tells you is just as critical. With Stablewood, we have factored those ideas into the fabric of how we run our business, with teams dedicated to the data and the intangibles, so that we leave no stone unturned.
Another mistake I have made is not committing the time and effort to market my ideas adequately to get buy-in from the people that matter. For example, we had a ton of data to work with at the Astros, but getting the players to follow the signs the data was showing and adjust their game was another matter. There were a few instances where I didn’t do my job to market the potential benefits of our ideas or tactics to the players. The result was missed opportunity for the team as a whole.
8. Tell us a little bit about your marketing process, what has been the most successful form of marketing for you?
Marketing needs to be about education just as much as it feels like selling. People need to understand the benefits and be compelled by relatable facts or information to take action. This happens a lot in product marketing, where you’re trying to get people to take action and move down the funnel, to purchase a particular product. But marketing is critical for internal decision-making and pitching, too.
Marketing myself and my ideas was something that I had to work on as a skill so that others could see the benefits and areas for improvement. My marketing process has become focused on educating on the value and benefits, not just the process or outcomes, that are required.
9. If you only had $1000 dollars to start a new business, knowing everything you know now, how would you spend it?
I would look to invest in something novel and future-focused, like vertical farming. The data shows that there are too many inefficiencies in land-based farming. There are so many opportunities for expansion and cultivation, with more responsible water and resource use on top of it all, when it comes to vertical farming.
It’s an area I’ve read quite a lot about, and I think we’ll see a real transformation over the next few decades as climate change and other resource expenditures force agriculture to reinvent itself. And vertical farms are already popping up and demonstrating returns.
10. What’s a productivity tip you swear by?
Always take notes.
Don’t rely on your memory to bring back ideas, conversations, or input from yourself or others. I am an obsessive note-taker and use a number of tools and techniques for this. But no matter how or where I jot something down, I always make it a practice at the end of a meeting, conversation, or day to stop and review everything that I have collected.
This is a great way to recap what I have experienced, ideas that have come up, and, most importantly, identify action items for myself or my team. This process makes me more productive personally and helps me be a better contributor to others looking to me for direction or guidance.
11. What are the top three online tools and resources you’re currently using to grow your company?
They aren’t solely an online tool, but we’re using things like Python and R to create the tools we need internally to get ahead with our data analytics. Python is a programming language that allows us to manipulate our data more with more agility and apply machine learning principles.
We rely on R more than Python because it is specifically designed for statistics, which we are turning to as we develop our internal systems and create our own understanding of the private equity real estate market.
Excel spreadsheets may still have their place, but they’re quickly being outpaced by technology systems that are dedicated to more robust analysis.
12. How can readers get in touch with you?
Full Story: https://billionsuccess.com/brandon-taubman/