Using “Money Ball” Strategies In Commercial Real Estate With Brandon Taubman | S3SP4
In this fourth special episode of Season 3 of the A.CRE Audio Series, Sam, Spencer, and Michael discuss baseball analytics and real estate analytics with special guest, Brandon Taubman, Chief Information Officer at Stablewood Properties. Brandon is a data scientist and financial engineer with 15 years of experience in investment banking, sports analytics, and real estate.
Prior to 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.
Brandon’s experience in baseball and on Wall Street brings a unique and innovative perspective to commercial real estate. Watch, listen, or read this fascinating episode as the A.CRE team discusses Brandon’s background and how analyzing baseball players has informed his methodology for analyzing commercial real estate investments.
Using “Money Ball” Strategies in Commercial Real Estate with Brandon Taubman
Watch or listen below as we discuss baseball analytics and commercial real estate analytics with Brandon Taubman, Chief Information Officer at Stablewood Properties.
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Resources from this Episode
- Tools for Real Estate Analytics
- Learn more about Brandon Taubman
- Build Your Own Real Estate Financial Models
Episode Transcript
Announcer (00:01):
Welcome to the Adventures in CRE Audio Series, join Michael Belasco and Spencer Burton, as they pull back the curtain on everything commercial real estate, and introduce you to some of the top minds in the industry. If you want to take your skills to the next level and be part of a growing community of CRE professionals across the world, this is for you.
Sam Carlson (00:25):
All right, welcome back. We are season three, season three as you know was all about deal making, deal doing. And we’ve had a little bit of a lull. We had Thanksgiving break, we’re back now and we’re meeting here today with, I don’t know, is this way most excited guest of the entire season, it probably is. And for good reason, we’re here with Brandon Taubman. And before we jump into the intro of who Brandon is, I have an affinity and a love for the game of baseball.
Sam Carlson (00:57):
I coached it for several years, my oldest is… I don’t know if we’re going to make it to the pros, Brandon, but we’re trying our hardest to get at least to college and maybe pay for some tuition. But at any rate we’ve got Brandon Taubman, he’s got a fantastic background. He is bringing some skills that you might not think are within the scope or the realm of commercial real estate. But we’re going to share with you a really cool discussion and chat today with Brandon Taubman. And maybe before we get a hello from Brandon, if I could just turn a little bit of time over to Spencer, just to give me a bio so the listeners have a good idea of who Brandon is.
Spencer Burton (01:40):
Yeah. Thanks, Sam. Brandon, it’s really good to see you. Now for the listeners, for the viewers, Brandon actually is also my partner in a real estate investment firm at Stablewood. And so this is a double pleasure for me to bring Brandon into the A.CRE world. He and I are in the trenches of commercial real estate investing every day, so that’s exciting.
Spencer Burton (02:01):
Now in terms of Brandon, he’s an investor with 15 years of professional experience across various sectors, investment banking, derivative evaluation, daily fantasy sports, which we’ll get to, professional sports and most recently commercial real estate. He started his career at Ernst & Young, what, 2007, Brandon? And then moved to Barclay’s Investment Bank. Now continuously with his career in finance, he engineered a successful system to wager in daily fantasy sports. And that led to ironically a professional career in baseball economics.
Spencer Burton (02:37):
Started with the Houston Astros in early 2013 and was pivotal part in the architecture and rebuilding of the Houston Astros from what? 2013 through 2019. And so Brandon joined Stablewood in early 2020 and it’s this really interesting shift from evaluating and valuing baseball players to evaluating and valuing real estate. And we’re going to talk a lot about that. Now one final connection, Brandon and I have we’re both graduates as is Michael of Cornell University. He currently lives in Southern California with his wife and two kids. So Brandon, great to have you on, nice to see you again today for a second or third time of the day.
Brandon Taubman (03:19):
Thanks for having me on, I feel like with a generous introduction like that, anything I can say about myself at this point would be de minimis, but I’ll do my best to represent myself here and thank you guys for having me on.
Spencer Burton (03:32):
Yeah, absolutely. So to this topic of evaluating baseball players and how that relates to evaluating real estate, give us your mindset. As you were making that transition from professional baseball analytics to professional real estate analytics, what did you think about real estate as you were starting that transition and what were the major difference or similarities that you saw at the onset?
Brandon Taubman (04:03):
Yeah. Great question. So if you think about it, my career in terms of the industries I’ve been in quite fragmented. Investment banking to baseball, to real estate, but the common thread between the three is that you’re ultimately looking at assets that have some projectable value into forward you years. And so that’s the easiest to understand, in finance where you’re looking at cash flow and discounting back to present value.
Brandon Taubman (04:26):
In baseball though, players have projections of the sort of value that they’ll produce on field. The stats community often called the sabermetric community in baseball. They will look at a catchall metric called WAR, wins above replacement for baseball players. So basically asking the question, how many wins does this player contribute to my team or how many wins will he contribute to my team in the future?
Brandon Taubman (04:49):
And we can actually assign a dollar value to that win production, and we can assign a cost of capital to the team. And so where you get pretty quickly is a proforma for a given baseball player that looks not so dissimilar from how you evaluate a derivative or a piece of real estate.
Spencer Burton (05:05):
Now that’s fascinating. So there’s some projection about the value. In real estate it’ll be cash flow, the value that, that player will produce in the coming years, how do you assign risk volatility? So in real estate, you’ve got investment-grade cash flows and you have some pretty good certainty that those cash flows are going to exist. And then you have other… Let’s find, self-storage is an example, much more volatile cash flows, actually senior housing, even more so because there’s a greater expense load.
Spencer Burton (05:38):
What about volatility with baseball players? Are there certain players that there’s more certainty around the cash flow, the performance in the future, is there generally more kind of a steady-state there?
Brandon Taubman (05:50):
Absolutely. Yeah, there is. So let me stick with the finance baseball real estate framework for explaining this.
Spencer Burton (05:56):
Sure.
Brandon Taubman (05:57):
So in finance, the volatility of any given asset, at least in the liquid markets is implied by the market, right? So you actually don’t need to go study what volatility was, historic volatility the market will tell you based on how they’re wagering in the marketplace. In baseball, it’s not quite as efficient, but it’s pretty efficient because what you have is thousands of baseball players over the course of time that have been perfectly tracked in terms of their performance or ups and downs.
Brandon Taubman (06:24):
And it becomes really easy to understand the risk of a given player on a profiling basis. And so it’s used in example, a left-handed reliever, who maybe gets 50 innings pitched a year is going to have a way lower ceiling than a position player that has 700 plate appearance and is impacting the game in a lot of different ways.
Brandon Taubman (06:44):
And so the way to understand risk in baseball is to build projection models based on what has happened in the past and pretty clearly and quickly, you can get to an understanding of the different risk in athletes. And that connects or correlates with the way that we look at real estate investments, where we have opportunistic and value add and core and core-plus and so on. It’s least specific in real estate, I think. In real estate, we’re talking about like broader generalizations of the risk profiles, but we’re often not getting down to the level of standard deviations of risk.
Brandon Taubman (07:19):
I mean, we’re trying to, it’s stable and you know that’s Spencer, but I would say to put a bow on this, the understanding of risk around investments is most sincere and best understood in finance and probably least understood in real estate and baseball is probably in the middle.
Michael Belasco (07:36):
So I wanted to tack on a little bit here. So we’re talking about individual assets so to speak, whether it’s public equities, whether it’s a baseball player, whether it’s real estate and we’ve all seen Moneyball, we all know that… If you know the story of Brandon Taubman, he’s of that lineage, and maybe even took it to the next level a little bit.
Michael Belasco (07:58):
So if you’re looking at players individually and you’re valuing them, there’s this aggregation of players that turns into a portfolio of players to which you put on the team. And you’re not necessarily going after the player that performs at the highest level on all metrics, because you have caps, you have all kinds of things. So give us a little input maybe into the similarities between whether you’re putting together a real estate portfolio or a baseball portfolio of players and are there any similarities you could draw there?
Brandon Taubman (08:28):
Yeah, really, really good question. So portfolio theory works a little bit differently, depending on what industry we’re talking about. Like in the equity space, there’s not really a cap on the amount of transaction that you can do, and the market is like really liquid. So the math will basically tell you what the most optimal portfolio is. In baseball, it’s a little bit different ’cause you have all these roster constraints and you can’t have a given player play more than one position and not every player can play every position. In fact, they’re often usually like relegated or restricted to a couple positions that they could play well.
Brandon Taubman (09:07):
So there’s a lot more thought or a curation that goes into like putting together a good baseball team. The closer you are to the major league level, the more specific you need to be about how you put together a roster. Typically pitching staffs are 12 or 13 players, you don’t want more than one first basement on your team, because that causes a little bit more friction with your roster and so on and so forth.
Brandon Taubman (09:31):
But the lower level you get, the closer you get to the amateur draft or the international market where you have like 5, 6, 7 years to develop players, the less you really care about those sorts of restrictions, like what position does a player want? And really what you want to do is just get the best players that you can.
Brandon Taubman (09:50):
The rate of attrition is so high for minor league players, something in the order of 90%. So you’re just focused on the best players. It doesn’t really matter if you get 10 shortstops and you’re playing those shortstops out of position, because really you’re just looking for like some golden nugget, some skill that can ride that wave of attrition all the way from the Dominican summer league to the major league level. So definitely depends about what sort of portfolio you’re talking about major or minor league.
Michael Belasco (10:14):
Yeah. So it’s almost like you develop your eternal market almost like you don’t really care. You’re just bringing in all the players and then you start to curate that and you get to select. So I under… I’m just peeking into this really for the first time, how major league teams then cultivate their in-house private markets of players that they can then start to analyze.
Brandon Taubman (10:34):
A major league team will rarely have ever have two really good shortstops on the cusp of a major league promotion. And they have to figure out like how to position those players on their team. Most teams have none and they’re spending a hundred million in the free-agent market to have the suitable shortstop. But it’s nice to not be like prescriptive on portfolio assemblage, if you will, as a scouting director or international director where you’re just trying to find some talent.
Sam Carlson (11:00):
So I want to jump in here just for a minute. We’re 10 minutes into the interviewer or… And Spencer and Michael and Brandon, you guys know each other. And so we jumped into the weeds really quick. And I’m wondering for my own benefit, I don’t know if the listeners feel this way, but for my own benefit, I’m wondering, I know I love the game of baseball. I love the strategy. I’ll sit down and watch the game of baseball and I’ll have siblings or people or friends that are like, “This is boring. I don’t get this, I don’t see what’s happening.”
Sam Carlson (11:30):
And I’m like, “There’s so much strategy here, you don’t know what’s going on,” but I want to just go back a little bit and we don’t have to spend a of time on this, but I want to put like a little bit of a backdrop on what because what you’re really talking about is a high-level tactical skill that you are applying to something that will make a lot of money and… So you have some awesome skills, but I need a framework, did you love baseball first? Did you say, “Hey, I really love math and I’m going to go into finance.” And then baseball was.
Sam Carlson (12:03):
How did this happen? And I have a piggyback question to that. Let’s start there. I have a piggyback question if it works then it works, but start with me, where did this love and fascination for, I don’t even know what we’re calling this. Where did that start?
Brandon Taubman (12:22):
I think with my mom and dad and maybe with my grandpa who took my dad to Shea stadium, when it first opened many years ago, my dad became a great fan. And so just like you Sam, when I grew up, like my dad coached my little league team and took me to ball games. And I think I grew into a love for baseball and my professional career took me in a different direction. I was much like a lot of the listeners of this podcast, interested in building a career for myself in corporate finance. And that’s exactly the direction that I went in out of school with Ernst & Young and then Barclays.
Brandon Taubman (12:56):
And those were really good experiences, I worked with really smart people. I learned a lot about the way the world works, but I became somewhat disenchanted because I had seen some problematic things in my time in finance, I saw the subprime mortgage crisis and the global financial crisis when I first graduated in 2007. And my position at Ernst & Young was to value or evaluate these derivatives, that investment banks and insurance companies held that were at the core of the crisis itself.
Brandon Taubman (13:23):
Moved on to Barclays again, like very thankful for my experiences there, but gained some insights that made me feel like, you know what there’s more to experience outside of corporate America and that sort of interest or intrigue that I had about maybe going to work for a professional sports team, coincided with the birth of this new wagering platform, gambling market, if you will, which was daily fantasy sports.
Brandon Taubman (13:51):
Now daily fantasy sports is a daily contest, it starts in end in the same day where you create a roster of players and those players have some cost and some projected value or some projected production. And you can play against big pools of people, you could play head to head and so on and so forth.
Brandon Taubman (14:09):
And so in its infancy, daily fantasy sports was very inefficient. There were a lot of let’s say sports fans or enthusiasts that didn’t really have a systematic or a quantitative approach to playing and I did. And so I built a projection system and an optimizer in Excel using Solver. You guys can see the Spencer Burton Solver tutorial online at A.CRE If you like. But I used the same tool and basically picked the optimal roster each day. I played in scale, I won a whole bunch and I sort of like marketed that.
Sam Carlson (14:44):
I’m smiling ear to ear right now. I’ll put myself on mute, but I’m like hearing this story. And I’m like, “This is like the coolest thing ever.” Guy comes from finance, working on formulas and all this stuff, takes it starts… So make sure you include in your story, how much money you were making. I’m just kidding, but sorry to interrupt you, but if you’re just listening, all three of us, that are listening, we’re all smiling just being like, “This is incredible.” So, Brandon, I didn’t mean to interrupt you. Sorry.
Brandon Taubman (15:16):
Appreciate. Unfortunately, I didn’t make as much money as I wish I did or could have, I guess because I forwent that opportunity for something in baseball and obviously there’s a conflict of interest. So as soon as I got hired by the Astros I stopped my daily fantasy activities.
Sam Carlson (15:33):
Did they find you because of that?
Brandon Taubman (15:37):
Yeah, the story there is, I was interested in learning what the impact of weather was on the run environment. Basically, I wanted to know like how much weather impacts how many runs are scored in the given game, turns out the impact is pretty significant. But in any case, I put together some research, I imported data from Bloomberg. My Bloomberg terminal at Barclays had access to weather data. And I built this model that basically tried to predict what the change in expected run environment or run outcome would be given wind, wind direction, precipitation, et cetera.
Brandon Taubman (16:11):
And I shared it an individual at the Cardinals who I just had reached out to. And I was like, have you guys looked at anything like this? How do you guys handle this, et cetera, and started a conversation with this guy who eventually recommended that I applied for a job at the Houston Astros that had just opened. He had some friends there as well.
Brandon Taubman (16:29):
And so I would say it was serendipitous, or I don’t want to call it accidental, but I was primarily interested in making money from daily and that sort of naturally or organically grew into an opportunity with a major league team. And then by the way, when I saw the opportunity with the Astros at the time, the team was winning 50 games a year, it had no TV deal in place, which is how clubs get like half of their revenue to go spend on players.
Brandon Taubman (16:55):
And we had the worst farm system in baseball, 30th rank of 30 teams according to all the third parties that are really good at understanding the quality of your farm system. So my friends and family were like, “What are you doing? You’re going to move to Houston, Texas a place you’ve… A state you never stepped into in your entire life for a baseball team that looks absolutely atrocious right now. You’re going to make like 30% of the amount of money that you’re making now, and ask your girlfriend…” Who’s now my wife, “… to move across the country with you.” And I was like, “Yes.” That’s exactly what I’m going to do.
Brandon Taubman (17:24):
But I got to say the people that were starting the organization, the baseball operations effort, they were a really impressive group that had, had a tremendous amount of success at the Cardinals building up their draft process. And so I had some confidence that things were going to work out well and that I would have a great team around me to work with and hopefully prosper.
Spencer Burton (17:47):
Let me ask you. 2013 to 2019, you had some great success at the Astros I’ll toot your horn for you, but what changed in the way that baseball players were analyzed from 2013 to 2019, both at the Astros? And it sounds like there were some significant changes at the Astros, but across the major league in general, what changed over those six years?
Brandon Taubman (18:12):
Yeah, really good question. So I’m going to take it back a little bit farther, right? Because a lot of people have this Moneyball revolution as their reference point for baseball analytics and that was the early 2000s. So Billy Beane and Paul DePodesta played by Brad Pitt and Jonah Hill in the… I’m forgetting the author’s name.
Brandon Taubman (18:30):
But in any case, so what they decided to do is like, let’s look at how players have performed historically and see if we can understand what that means about how they will perform in the future. It’s a basic, basic premise and they had data at their fingertips to do that. The next sort of phase in baseball analytics came at the St. Louis Cardinals where Jeff Luhnow, Sig Mejdal, these group of guys decided like, “Hey, what if we took the same sort of approach in the amateur draft market? So high school and college kids, JUCO kids. And let’s see if we could produce a draft model that will lead to outsized returns in the draft and that worked brilliantly.
Brandon Taubman (19:04):
And so the Cardinals had like all of the success with homegrown talent in the late 2000s that was predicated on how they were drafting and their analytical approach there. So at the Astros, management embraced those concepts, like let’s use data to draft well and to evaluate players well, but the big unlock, the big opportunity at the Astros was we stopped looking at data, past data as a way of projecting the future.
Brandon Taubman (19:34):
And what we said is like, what happens if we actually empower our players and our coaches with data. So instead of like management using it to make personnel decisions, let’s actually share this information with our players so that we can help them be the best versions of themselves.
Brandon Taubman (19:48):
And that was the analytical revolution of the Astros, and we really like unlocked pitching. If you look at our resume in terms of how we’ve drafted and developed pitching, who we’ve signed and how they’ve performed compared to expectations, it’s very clear, we got the most out of our pitchers and we were able to do that because of a technology in baseball that tracks every pitch thrown and expresses those pitches thrown in spin rate, velocity, break, pitch location, and so on.
Brandon Taubman (20:12):
And using that data, you can really understand like, “Man, this pitcher over here, for example, he throws his fastball 40% of the time, that’s not a good pitch. He has a curveball, that’s one of the best pitches in baseball that he throws 5% of the time. Let’s ask him to throw his curveball some more and his fastball less.” Those sorts of tactical changes made a big difference in terms of win production.
Brandon Taubman (20:32):
And the players bought in because we were talking their language now. We weren’t saying, “Hey, you’re projected to be a three WAR player next year.” We’re saying, “This is how your fastball spins and where it’s located and here’s the data.”
Spencer Burton (20:46):
With every decision, there’s a call it a risk-adjusted return calculation. Players may perform well, real estate may perform well, but it also costs a lot. In baseball, how did you pair the cost of a player over versus the expected outcome from that player?
Brandon Taubman (21:10):
Yeah. Great question. We took a stochastic model approach, a probabilistic model, which Spencer and Michael, I see you guys laughing because you know what that means, but basically we would understand risk by simulating the returns with baseball players over the course of time. And what’s really fortunate for clubs and unfortunate for players, for major league players is that for the first six years of their service at the major league level, they’re basically on a string of successive options.
Brandon Taubman (21:38):
So each year the club gets to decide whether to retain the player or to let them go. And so the risk to the major league club of their minor league talent, end of players in their first six years is relatively small. Where the risk comes in is with deals in free agency, where players get long term multi-year deals. And we would basically simulate the risk around those free agency decisions to understand whether they were worthwhile and where that analysis pushed us is basically like always try to focus on keeping it core group of controllable, relatively cheap players.
Brandon Taubman (22:12):
And don’t try to build an organization around free agency, I mean, some clubs are able to do that successfully, like the Yankees, for example, because their expenditures are unlimited. They can do what they want, but for a team that really does care about risk. The risk of a player going bust, we would just focus on young controllable talent.
Spencer Burton (22:31):
Fascinating. I think about all these parallels to real estate and something that you and I have talked about in the past, and that is coaching via data rather than intuition. How has that changed? So you think about your traditional coach from 50 years ago and he’s got this beer belly and he’s making decisions on the fly because he’s coached 1000 games or 2000 games, how has that changed today? How much influence does data have on the actual decisions coaches are making?
Brandon Taubman (23:03):
It’s changed dramatically, but I wonder if it’s actually gone too far in some ways. And so like the two diametrically opposed viewpoints. One is like coaches are prone to making bad decisions, they’ll make the decisions that save their stomach lining and not the ones that maximize output. They’re not really good at gauging risk basically in terms of how they’re making game decisions.
Brandon Taubman (23:25):
The other one is that the coaches wise understand suppliers, sees and feels things in the dug out that people upstairs in their ivory tower in the front office can’t possibly understand. Where the industry currently is way more skewed to the former where teams are basically asking their coaches to make programmatic decisions in-game. But there’s a lot of stories, a lot of anecdotes in recent time where like maybe that’s led teams astray in their in-game decision making.
Brandon Taubman (23:52):
At the Astros, we too were skewed towards the sort of programmatic approach. I think rules of thumb are appropriate that there ought to be a dialogue between the front office and the coach where they’re explaining like what the is, and the likely outcome for various decisions that could be made throughout the game, but that you still give the coach the flexibility and the power to make decisions that he thinks is our best given what he knows of the players on any given day.
Spencer Burton (24:19):
And the parallel of real estate, if you think about it, and this is a constant tension at Stablewood where we value data, we value technology to a degree, I think more than many firms in the industry, but traditionally, this is an industry where real estate decisions are made largely on intuition. And oftentimes the analysis is meant to support the intuition and not the other way around. But it can go too far, where you rely too much on the data, you rely too much on the analysis and you need a nice, healthy pairing of the two. Michael, it’s interesting and I’ll let you chime in on this.
Spencer Burton (24:59):
Michael is a bit more of a skeptic. I’m sorry if I’m putting words in Michael’s mouth, a bit more of a skeptic around the value of data in real estate and that value compared to the intuition. Thoughts on this conundrum right now in the industry data versus intuition.
Michael Belasco (25:15):
Are you asking me that or?
Spencer Burton (25:16):
Asking Michael Belasco, yeah.
Michael Belasco (25:18):
No, I would not say that I’m a skeptic at all. I would say there is a level of skepticism that I’ve always kept. And for the listeners, I was a part of Stablewood during the launch for the first year and a half. And this would always be a point of contention because… And this is something, there’s a lot to unpack here first of all, because I’ve been thinking about… I’m going to ask Brandon the question about bridging the gap between other industries is something that we talk about a lot and how much value add that is.
Michael Belasco (25:50):
But back to your question, so I’m not skeptical of data at all. And I always told Brandon when we talked, I just want to challenge it to the point of finding where it breaks down and it’s true you get into data and you get in… There’s a lot of truth to data and there’s a lot of field of data. And I find that when you get down deep into the weeds, it ultimately comes down to the assumption that you put into a future predictor.
Michael Belasco (26:18):
And whether you’re predicting it at the top level and you’re saying 3% or you’re using all this data to get to the bottom detail to say that you’re predicting on a street-level X or Y there’s always some input that isn’t intuition, that is better informed by data. And I’ve had so many conversations with Brandon and the initial… Rent always goes up by 3%, whether it’s up or down, if you’re a long-term investor who cares. It’s always going to hit that mark.
Michael Belasco (26:43):
And we got to the point to where I value… And it’s funny because since I’ve left Stablewood, there’s a couple of things I’ve started and data, I can’t get past it. I’ve learned through Brandon to be constantly asking questions to where it’s bulletproof using whatever data’s there to support it. That is never going to be the full answer to everything, but it better informs.
Michael Belasco (27:05):
And the other thing I’ve noticed is that it’s more convincing when you’re going out. So you’re investing money and you’re raising money and data is very helpful in convincing others, sophisticated people that you know what you’re doing because you have this extra resource and this extra power. So I am not a skeptic of data, I just want to get down to the point. And my role there was to basically say, “I’m skeptical until proven otherwise,” I’m going all the way down into the details.
Spencer Burton (27:32):
It’s healthy though, by the way. I appreciate… And skepticism is probably a bit extreme. You question it and I think questioning it’s important.
Michael Belasco (27:43):
Now, I just want to add, so when Brandon came and every time Spencer you and I speak to universities, Brandon Taubman whether it’s direct or indirectly is a subject of one of my main messages. And it’s because of all this and what he’s brought into Stablewood and what he’s done, what’s to him was no brainers and to us was like revolutionary, like the things he contributed and it was because he came from an… Well, first of all, he’s brilliant so that’s the first thing, you need to have a brilliant mind. I know Brandon-
Brandon Taubman (28:10):
You’re going to do this more often guys. My ego is feeling really nice right now.
Michael Belasco (28:15):
But you crossed industries, right? So Brandon came from Wall Street, he came from baseball and he was very data-centric and he comes into real estate now and he’s bringing in things. I remember when we were on calls in the early days and he’d mention stuff, be like, “Guys, why aren’t we doing X?” And we’d all be like, “Okay, well prove it.” And then the next day he’d come up and he’d prove it. And he would… Mind’s blown it happened many times.
Michael Belasco (28:41):
And so I always tell people if you’re starting a company and you want to do real estate for an example, bring in a brilliant mind who might be interested, that’s coming from something completely different. Because if you’re trained in an industry, you’re trained to see things a certain way. And when somebody comes in from outside, that has the ability to think critically, they’re going to bring some revolutionary ideas to which Brandon Taubman has done over and over again, I’ve seen it. It which brings me to my question, Brandon, I’ve been wanting to ask you, so-
Brandon Taubman (29:10):
Wait, can I just say, I want to say something really quickly, piggybacking on your remarks there and Spencer. The best organizations have a Michael Belasco and a Brandon Taubman, I hope that doesn’t sound too conceded to say that. But my point is like there’s balance, and so all the times that Michael shot holes in whatever I was presenting was really valuable because it made the end result better.
Brandon Taubman (29:32):
I think so-so organizations have like only people like me or only people like Belasco where you have like really strong subject matter expertise in this case, real estate. And Belasco coming from Hines, me coming from data science and the worst organizations have neither. But I do think you need like checks and balances. It goes back to your question about manager and team and so on. And so yeah to any people forming companies or looking to hire in skill sets, there is true value to wisdom of the crowds where you want disparate viewpoints and to achieve balance in the end. Go ahead, Belasco.
Michael Belasco (30:04):
Yeah. So that’s a super great point. What I wanted to ask you was you’ve seen the revolution of baseball and how you pick players and you curate teams, you’ve watched it from inside. And then you come to an industry which is for all intents and purposes, sort of nascent in the data and analytics space. There’s a lot being done here, but it’s not that much, right? It’s not that much compared to what you’ve seen in baseball.
Michael Belasco (30:27):
So from the transition, when you transition from baseball to commercial real estate, and you took a peak under the hood at how people do things in real estate and to what you’ve started to do now and what you’ve been implementing over these past couple years at Stablewood, where would you say, and you’ve interacted with a lot of different capital partners, lenders, equity, you’ve interacted with tons of people.
Michael Belasco (30:47):
So you know, you’re well in the thick of the industry, more so than most. Where would you say real estate analytics data underwriting is compared to other industries you’ve been in and maybe this is a little too in the weeds, but where do you see it going or where do you see opportunities for it to improve? If you can answer, I know some of that might be proprietary for you, but to the extent you can answer that would be great.
Brandon Taubman (31:14):
Yeah. So first part is, I would say real estate is truly in the stone ages. Honestly, part of that is because in finance, you have literally millions of participants in the marketplace that make it efficient and observable. In baseball you have this pristine track record, every pitch is thrown, every bat is tracked. And that gives people like me wonderful data to work with.
Brandon Taubman (31:36):
In real estate, there’s very little data relatively speaking, and it’s highly fragmented. Even if it’s out there, it’s hard to get your hands on it. And so to answer your second part of your question. In real estate, I think the barriers to entry to do good data science are way higher because the data is worse and more incomplete and so on. But also because of that, like the benchmarks are way lower. There’s a lot of opportunity to do better than what’s out there.
Brandon Taubman (32:02):
And that’s why I basically got into the industry because I thought that there was… I wanted to be part of this right up. And I think real estate is going to change a lot over the next 10 years. Let’s say you see all these service providers with their SaaS place coming into the space and you see data vendors offering interesting data sets that can help you understand investment opportunities better. And I’m excited to be a part of applying of the emergence of new data in real estate.
Sam Carlson (32:31):
So I want to go back for… It’s kind of my job to go back every now and again. You know what I mean? I want to go back because I think… And one of the things that Spencer and I since we were kids that we love to do is just look at businesses, consider businesses, think strategically, all that stuff. And I try and find these principles to attach my reasoning through and the samurai not to get too samurai-y on you, but my Miyamoto Musashi, if you’ve ever heard that name, he was like a Grand Puba of the samurai. He said, “If you know the way broadly, you will see it in everything.”
Sam Carlson (33:09):
And one of the principles that we think about, that I use as a mechanism is think macro act micro, meaning if you see success, and if you see patterns broadly, then you can create leverage by acting in small things. And that’s my own personal principle or whatever. I don’t want to put words in your mouth, as I’m sitting here, listening to your story, listening to your tactics and how you’re doing things. I’m very curious as to you go from finance to baseball, to real estate.
Sam Carlson (33:52):
And I’m thinking, well you’ve seen the way broadly in at least in finance and then you saw it in baseball. Because of that are you able to see it in everything? And that applies obviously to what you do now in commercial real estate. That’s I guess my question.
Brandon Taubman (34:11):
Yeah, it’s good. I’m going to struggle through this answer a little bit, but I’m going to try my best here.
Sam Carlson (34:16):
I struggled through the question so it’s fair game, buddy.
Brandon Taubman (34:20):
I think the macro principle is that data combined with subject matter expertise leads to the best decisions. That’s the macro, that’s what I’ve seen throughout all industries. Now in real estate, the micro is that it’s basically all gut feel right now. So there’s a whole bunch of micro opportunities to seize and we’re doing our best to seize them at Stablewood.
Brandon Taubman (34:43):
But think about a traditional acquisitions person that is largely basing, well they’re doing underwriting for sure especially if they’re part of A.CRE Accelerator program, but they’re also visiting sites and forming an opinion subjectively with very little data on hand. And that’s not the way that is optimal probably. And at least not the way that we’re approaching it at Stablewood, where we’re trying to first apply as much data as we can to understand the investability of the property.
Brandon Taubman (35:14):
And then the subject matter expert is there to fill in the gaps. Where is the data not so sharp or not so complete, would we be foolish to rely on it and let’s have our people focus their expertise in those areas.
Spencer Burton (35:29):
Talk to us a little bit about a phrase I hear you use a lot, discount but don’t dismiss. Where did that come from and how does that relate in your view to real estate?
Brandon Taubman (35:40):
So a gentleman named Sig Mejdal who’s currently the assistant general manager of the Baltimore Orioles always used that expression and stuck with me and where it comes from is in the draft room, at least at the Astros. You had this weird dynamic where on one side of the room, you had all the nerdy front office people using their projection systems to understand how good the draft worked.
Brandon Taubman (35:59):
And then you had the scouts that were out in the field, looking at these players, following them all throughout the draft calendar year. And often there’d be a player with a projection, a projected value that would exceed his likely draft positioning. But there’s always something wrong with that sort of player, right? Tyler White is a great example, this guy coming out of his D2 program was 350 pounds, severely overweight, he could only play first base, but he hit.
Brandon Taubman (36:27):
And so the Scouts were, “This guy’s never going to be a star. Let’s not…” He can’t possibly be but six point was like, “Well, let’s discount him for the fact that he’s got a bad body and he’s slow and this and that, but let’s not outright dismiss him because he does have some attractive attributes that may pan out.” Now, Tyler White never became an all-star type player, but he did by far exceed expectations. And he was an important part of the Astros for a few years.
Brandon Taubman (36:51):
As a guy who we could just put in the lineup and would get us a hit when we needed it. So that’s where that mantra comes from and it’s just this idea that we don’t know the future well enough to outright dismiss. What we need to do is be calculated in the way that we assign premiums and discounts to a given investment opportunity, whether it’s real estate or a baseball player.
Spencer Burton (37:12):
Yeah. I love that. So we don’t have a lot more time and I want to make sure to speak to the younger members of our audience. There’s two really areas. First off you had this fascinating transition from one industry to a totally different industry, and you’ve been able to add such significant value to real estate already and I’m excited about the coming years. And what about to say a university student, undergrad grad student, they’re trying to build up their skillset so that they can add value to the industry as it changes and it adapts some of these micro opportunities that you mentioned.
Spencer Burton (37:51):
What technical skills besides real estate financial modeling, of course can they be focusing on. You’ve mentioned R… I know that’s a language… I don’t want to put words in your mouth, but are there tools like that that undergrads should really be mastering in order to excel in real estate?
Brandon Taubman (38:09):
Yeah. Okay. Be very specific about it, I think all of your listeners who have an interest in building technical skills to be more marketable and better investors should actually get into Python. I’ve gotten into R because at some point R was bigger than Python in terms of its open-source community. But the way that the world is going, it’s like Python is the language to focus on, it’s the most flexible, it’s all open source. And so to have some basic proficiencies there that you could put on your resume, that would be huge.
Brandon Taubman (38:38):
I remember when I started at Ernst & Young in 2007, the fact that I could create some VBA macros was like a big deal to managers and put me ahead of the other people that were starting my year. The modern-day excel modeling VBA skill is Python. If you have that skill set, you’ll be more attracted to hiring managers in the forthcoming years. And there’s so much that you can do in Python, machine learning, some software development, some data engineering there, but just pick up some basic skillsets. It will go a long way and put you ahead of the peer group, I think.
Spencer Burton (39:12):
Yeah. It’s great advice.
Sam Carlson (39:14):
That’s awesome. Michael, any last words from you, buddy,
Michael Belasco (39:19):
Other than that this has been an incredible episode, I’m excited for everybody to hear this. I think the big takeaway from me and this is from Brandon and that I constantly tell pretty much everybody I speak to at the university level and beyond is, look beyond where you are in the industry and look outside and you’ll be pleasantly surprised. I think that’s the way to make revolutions happen in industry. So that’s my constant go-to with Brandon. There’s so much more, but yeah, it’s been a pleasure and always love listening and talking to Brandon. So it’s been great. Thanks, Brandon.
Brandon Taubman (39:55):
Thank you. Same time and place next week, guys.
Sam Carlson (39:59):
There we go. Same time, same place.
Spencer Burton (40:00):
It’s going to be interesting no doubt.
Sam Carlson (40:03):
Yeah, that’s awesome. Brandon, you’ve been fantastic. Thanks for coming and sharing all this nerdy stuff as well as all the other really interesting insights, I kid. It’s been great for me, I love hearing your story. I think the listeners will obviously enjoy just the transition. And I think the other thing it does is it makes it so, hey you don’t have to be stuck in the mud, you are other things. You can transition, you can develop other skill sets that will give you other opportunities.
Sam Carlson (40:34):
So maybe that’s an under-tone of the interview, so thanks for coming. To the listeners, thanks for listening or if you’re watching, thanks for watching and we’ll see you on the next episode of this podcast. I will say that Brandon’s information and writeup will be on our website at adventuresincre.com and we’ll see you on the next episode.
Announcer (40:55):
Thanks for tuning into this episode of the Adventures in CRE Audio Series. For show notes and additional resources, head over to www.adventuresincre.com/audio series. Would you like to learn real estate financial modeling in a matter of weeks and do it with zero guesswork? If so the A.CRE accelerator is for you, the accelerator is a step-by-step case-based program designed to teach you exactly what you need to know and in the order you need to know it. So you can gain both the knowledge and experience to take your career to the next level, to see if the accelerator is right for you go to www.adventuresincre.com/accelerator.
