Data Driven Real Estate Podcast #4 – Builders and commercial real estate trends in 2020 with John Burns. DDRE#4

Builders and commercial real estate trends in 2020 with John Burns. DDRE#4

John Burns with John Burns Real Estate Consulting (JBREC) joins us this week. For years, the JBREC team has consulted with builders, institutional funds, built-to-rent firms, and Wall Street landlords offering in-depth market analysis and demographic trend to help businesses make better-informed investment decisions. This week, we take a deep dive into data. What matters, what doesn't, and how Covid-19 has impacted builders and what trends are emerging. Some will certainly surprise you. Residential and commercial real estate may not have the same two-year journey. Commercial investors, you're going to want to listen to this show!

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Show Topics

  • 01:00 How John Burns got into the real estate game?
  • 01:52 John Burns Real Estate Consulting and their first huge client
  • 02:48 The major client types for John Burns Real Estate Consulting
  • 06:45 Polling data vs survey data: Which is better?
  • 07:48 The one data set with a 16% margin of error that traders love
  • 09:46 The missing data we didn’t have before the Great Recession that would have been helpful
  • 10:41 Good data doesn’t come cheap! Do you even understand?
  • 11:38 Nuance in real estate marketing timing, risk assessment, and charts that matter (and don’t)
  • 16:59 The genesis of one of the best (and only) books on real estate and demographics
  • 18:11 What is Surban?
  • 19:12 Has Covid permanently destroyed one of the hottest trends in real estate over the past decade?
  • 20:39 What’s more important in real estate: location or affordability?
  • 25:44 Will divorces explode and drive up real estate demand?
  • 27:18 What is affordable housing to Millennials, the most educated generation ever?
  • 28:28 Why haven’t we seen a builder boom this cycle?
  • 31:50 Are trade wars impacting builders and building supplies?
  • 34:14 Is real estate in markets like Houston susceptible to things like the oil industry?
  • 34:57 The secret trick to track migration patterns in near real-time
  • 35:33 Many people have escaped high-tax states by migrating to states like Florida. Will that continue?
  • 37:17 What builders used to do before awesome data and research by companies like John Burns Real Estate Consulting
  • 38:36 Is there a different trend in single-family real estate versus commercial?
  • 39:13 While commercial real estate prices drop?
  • 40:59 What are builders most worried about?
  • 42:02 Are builders making any mid-build adjustments because of Covid-19 consumer trends?
  • 45:01 The real estate market in 2020 is going up?!
  • 46:16 The unusual category of unemployment that most people have checked being laid off because of the pandemic
  • 47:00 The issue small businesses are having because of the CARES Act
  • 48:18 64% of America can make more money on today’s unemployment program
  • 50:42 Will commercial foreclosures be an issue in the next few years?
  • 51:48 What types of commercial real estate will get hit hardest?
  • 52:48 Will office lease space have a vacancy issue with remote work gaining popularity?
  • 54:17 Is Amazon taking over malls?
  • 57:30 Why aren’t American homes built in factories?
  • 58:12 Are public builders getting into the build-to-rent space for single-family homes?

Show Transcript

Aaron Norris [00:00:02] Welcome to the Data Driven real estate podcast, the podcast from real estate professionals dedicated to driving business success using data. I'm Aaron Norris, vice president of Market Insights for Property Radar. And with us today, we've got Shot Tool, CEO of Property Radar and John Burns with John Burns, real estate consulting. John. Guys, I've got to do the embarrassing bio. It'll be quick and snappy, I promise. But John Burns, of course, was with John Burns real estate consulting, which helps business executives make informed housing industry investment decisions. He is co-author of Big Shifts Ahead Demographic Clarity for Businesses. One of my favorite demographic books, a book written to help make demographic trends easier to understand, quantify and anticipate. And John has a B.A. in economics from Stanford University and an MBA from UCLA and works out of Southern California right here in Irvine, California. So thank you for joining us today. Our fourth show. All right. How did you decide to get into the real estate game?

John Burns [00:01:01] Completely, accidentally. After getting my graduate degree, I went to go work for a consulting firm. I'm there. Three months. They reorganize by industry. My boss picks real estate. So in 1999, I became a real estate counsel and I went and I went to a school with a really well-known real estate program. It took no real estate class. I figured it out later, I think.

Aaron Norris [00:01:29] How long were you there and when did you went to John Burns real estate consulting start?

John Burns [00:01:35] You're gonna date me here, man. So I was there from eighty-nine to ninety-seven and I went out on my own in 2001. It's thirty-one years.

Aaron Norris [00:01:47] Wow. Well, who was your first client? What did that look like? Why did you go out on your own?

John Burns [00:01:52] First client was the Irvine Company. I should have saved the check. It was for all of $1,000 dollars.

Sean O'Toole [00:01:57] Now, that's a heck of a first client, though.

John Burns [00:02:00] I know. I started big, but very small. I just had done a lot of consulting all over real estate, commercial and residential. And I really saw the commercial guys were very, very sophisticated about managing themselves through the cycle. And, you know, it's a little easier you can build a big company with buildings that don't move when you're a home builder and investing in residential. The buildings are changing all the time. And it was a little bit more of a cowboy industry was all about buying the land. Right. It wasn't really about managing that cycle. So I saw an opportunity to take with the commercial real estate guys we're due on and bring it to residential.

Aaron Norris [00:02:41]  Yeah. And your client rosters really change then? Over the last several decades. Then so who does your clients look like now?

John Burns [00:02:49] It started with home builders and developers. Now we have a lot of building products companies. We have a lot of hedge funds. We have a lot of private equity. This whole single-family rental trend. We've been at the forefront of that. So I sleep a little better at night knowing that my eggs are a little diversified into multiple baskets.

Aaron Norris [00:03:09] Very good. Well, and I know, you know, a lot of what we're trying to focus on is a lot more of the data. I always like the hand this to Sean because this is his baby.

Sean O'Toole [00:03:20] Yeah. So before we start diving into you know, I know everybody's gonna be anxious to hear what you think is coming, but we thought we'd cover some other stuff first. You know, this is the data-driven real estate podcast. So what data? You know, I think you guys have a variety of stuff, including surveys and other things. What data is important for you and your business as you help builders and these other folks, you know, make good decisions?

John Burns [00:03:49] So there's been a huge shift over the 19 years I've been doing this. At first it was, can you go find some data? There was none. And now there's too much. So tomorrow, can you filter it down for me? So I learned back from one of my mentors out go bar way back when that it was all about jobs. I think it's about more than that now. But I still have to monitor that job growth really well, because that's an adult with an income that could buy your house or rent your property. And that data actually is very, very good data. We have the whole COVID period here where all these government programs have made things really messy. But usually that data is as excellent comes out every month. You can't get population and other data very reliably.

Sean O'Toole [00:04:39] Yeah. Is it mostly government or private industry like folks like ADP and that kind of stuff or both. Or a mix.

John Burns [00:04:45] The actually the Bureau of Labor Statistics gathers it from the State Employment Department, California Employment Development Department. They have two surveys. One is a huge sample size of all the major companies out there. That's what you normally hear quoted. They will miss trends like small startups and things. So there's another survey, that one, the unemployment well, where they call people at their house, that that picks up those trends. But it's a smaller sample size. So I usually find the right guy looking at both. And the right answer is usually somewhere between the two.

Sean O'Toole [00:05:19] Yeah. And it's one of the things I find really interesting every time I look at your reports. I'm totally immersed in public records. Right. County assessor, county recorder. But you pull in all these other things, you know, population, unemployment, inflation, economics and all of those, of course, play a really important role. What percentage of that stuff do you think? You know, you mentioned like some of the labor stuff is survey-based. You know how much of it is survey-based versus real hard data? I mean, like we have employment data getting reported in our payroll reports regularly. Why isn't that data available? Why are we looking at surveys?

John Burns [00:06:03] So ADP reports their numbers, but I think they only do 20 million workers or state somewhere around. So, you know. You know who's got all the data? Is the post office, the post office and the utility companies. And so I've been trying to get it out of them forever. And, you know, somebody sued the utility companies a long time ago for some privacy issues. So that was the answer to your question. Lawyers are the reason that we can't get one hundred percent sample size. We don't even need to take the census. If they would just ask the mailman, is there anybody in the house or not? And how many people are in there? She knows.

Sean O'Toole [00:06:43] Yeah, that's that's pretty funny and very true. So, you know, with a lot of that data being survey data. Right. The survey that most people are familiar with is polls. And obviously, the polls got the last election a little bit wrong. And there's already, you know, people questioning polls for this election. How do you feel, you know, when you're asked about survey data and your reliance on survey data about its accuracy? And I mean, you can get a statistical margin of error. But, you know, do you feel that relying on survey data puts you at a disadvantage and. What are the issues there?

John Burns [00:07:26] I try to guess that we filter data. So I try to get as much data as I can. And if there's 10 different ways of looking at something and nine of them are all coming to the same conclusion, I get some pretty good confidence in the conclusion. You're you're right. You need to be very careful about making a conclusion off of one data point. I'll pick on the Census Bureau. New home sales number, which moves the stock prices every day and every time they published, it's got something like a 16 percent margin of error. So they might say home sales were up 10 percent this month when they were actually down six. And people are trading on this kind of data. It's just it's just crazy. But if you've got seven other data points that are triangulating around that 10 percent, you have some confidence it's probably right this time.

Sean O'Toole [00:08:16] And that's probably why your clients are paying used to do that triangulation and look at those other data points rather than just rely on one thing that has a 16 percent there.

John Burns [00:08:28] That's how we spend it for less than the cost of our person. You've got 60 of us trying to figure this out for you. So that's how that works.

Sean O'Toole [00:08:35] Yeah. The public records play much of a role for you guys at all.

John Burns [00:08:40] I mean, we'll look at everything. Yeah. Yeah. We will get all the public records we can. We're very frustrated. They're not very available in Texas, for example. My chief information officer, Steve Dutra, people call the data God and you're not allowed to hire him. I know you guys are data geeks. He's just amazing. And he knows what's right and wrong by metro area of everybody's data on his cobbled the whole time he's been with me, all of us since the beginning.

Sean O'Toole [00:09:11] Yeah, no, I definitely know his name. And, you know, there really aren't very many people. And on you know, I hang my hat is one of them. So I'm a little biased here. There aren't very many people that understand both data science and all the nuances that are in the real estate data set. And, you know, I think that's a real shame. I think we made huge mistakes in the crisis. Coming up, the two thousand eight, because, you know, even the Fed didn't understand what they were looking at.

John Burns [00:09:46] You know, I look back on that as there are some data we just did flat out in half. I mean, I didn't have data on option arms. We didn't have data on what percentage of loans. We're actually documenting people's income. Now we have some of that data. So that's one of the reasons we have a lot more data now than we did 20 years ago, is when problems emerge. And you can. Solve it with data. I think that gives everyone a lot more confidence or whatever investment they're making.

Sean O'Toole [00:10:17] And there's somebody willing to pay for it. Right. So I remember, like, you know, the big core logic's and the first Americans all went back because they'd already abstracted the loans and they went back through all the loans to abstract the details on the pay option arms. And that was like a brand new hot data set that they were all competing with two thousand nine. But it didn't exist before that. You're absolutely right.

John Burns [00:10:40] Nobody would have paid to do it.

Sean O'Toole [00:10:41] So, you know, there's a ton of data still in the recorder's office that I would love to get. But it's just not financially viable for us to go abstract it. And I think a lot of people don't understand that the documents that the recorder get recorded is images. Right. It's not. It's pixels. Right. So you have to go abstract the information off of those documents. And OCR has largely failed to do that in any kind of regular or repeatable way. So it's it's an interesting it's a tough thing. One of the things you guys come up with from your data is a set of indexes. And are those is that a pretty important piece of your work? And you've got a couple that I find pretty interesting, like your housing cycle index, for example.

John Burns [00:11:38] Yeah. So the housing cycle risk index is. Something we came up with. It's kind of similar to what parents dad does. We're just sitting back and looking at the entire cycle. And when the cycle goes on for a long time, either good or bad things tend to overcorrect. So we we we did this a long time ago, maybe two thousand five. So we were calling high risk before it blew up. But, you know, when demand gets higher than it usually does, that's a sign that there's very low risk by job growth is really strong or there's more home buying than usual. But when supply rises to a very high level to meet that demand and all of a sudden supply is higher than normal. That's a high risk, too. And then you look at the affordability in that market. People used to compare affordability between each market, but that didn't matter. I mean, L.A. is always more expensive than Phoenix. But when Phoenix gets more expensive than Phoenix normally is, that's high risk, too. So we built an index going back to nineteen eighty one in every market we noticed that certain markets there were very supply-constrained, like California, were more tied to the affordability. Certain markets where you could build as much as you want whenever you want, like Texas, where more supply to supply, more tied to supply. And we came up with our weighted average that didn't call when the market would turn. But it would tell you when the risks are higher than normal or lower than normal and which way things are trending.

Sean O'Toole [00:13:15] Yeah. Yeah, no. Super useful report. Does it not only for as I remember it like. You call out a couple of different things like, you know, supply supplies and, you know, labor and other components there too within that.

John Burns [00:13:34] So there's 25 indicators we looked at, a few macro ones like consumer confidence that we talked about earlier.

Sean O'Toole [00:13:42] I wanted to ask a little bit about your intrinsic value index. This is something that's always fascinated me. You know, in fact, back in 2008, I kind of said one of the big problems was, is that we used you know, I mentioned this in our last podcast. Right. The last three morons to say I'll pay X, right, is how we determine what every piece of property in an area is worth. And, you know, especially like in the Bay Area where you got a company that goes public and you get three people who can just pay whatever, that doesn't then suddenly mean everybody in that area can pay whatever. Right? And I was just I wanted to ask a little bit about that intrinsic value index. Are you looking at kind of like what the people that currently occupy that area can kind of fundamentally afford?

John Burns [00:14:30] Yeah. So, I mean, it's the whole buy low, sell high. Warren Buffett, Ben Graham way of looking at things. So we have another index that feeds into this. So it's just our home value index, which which is basically an Abia. Right. Right. That actually, we cheat. We get a whole bunch of people's AVMs. Steve knows which ones are best in which market and we do a weighted average of other people's AVM. But that's how we do it. But then when a market gets far more expensive in relation to the local incomes than it usually does. That's where we say it's above its intrinsic value or what it overcorrects it's below its intrinsic value. The tough thing on that, and I'll pick on Denver, for example, is I believe Denver is a permanently more expensive market than it used to be. So, yeah, there's some subjectivity involved, not just, you know, trading, going back to the median of trying to figure out what the new normal is if you will. So I'm not going to say that we've got it all solved mathematically. There is some subjectivity in it, but most of our. But when you chart it. You can show something to your clients and they go, OK, I get it. And that's more than just a one guy's opinion. You know, it's got some data behind it. And usually, it usually ties pretty well to some local guy's gut feeling, which actually that's a good data point, too. I mean, smart people that are very objective when something doesn't look right to them. I listen carefully. That's good data.

Sean O'Toole [00:16:06] Good price reference. Back to Bruce Norris, Aaron's dad. Aaron, do you want to talk a little bit about demographic's? Obviously, a John's and his team's book, The Big Shifts Ahead a few years ago, I thought was just you said it was one of your favorite demographics, but it's my only demographics book.

John Burns [00:16:28] So his only too, but he did admit that.

Aaron Norris [00:16:31] OK. Totally a true story. But I had to buy it again last night because I keep on giving away my copies and I'm surprised and people are like, how do you not read this? Markets like California that are so cyclical and when ups are up it's great, when they're down, man, you want to get out of Dodge. And I'm very visual as well. So what was the genesis of Big Shifts Ahead, it's 2016. So for you, you know, almost...

John Burns [00:16:59] It needs a refresh, although some of the framework in there is helping me a lot right now. So the genesis of that was here we come out of the Great Recession and housing ain't booming. Everyone's got one millennial excuse after another. And I'm like, well, I think we can figure this out data-wise. So it started as a small research project that turned into a nine thousand hour research project with three really smart interns, all of whom work for me full time now. So that's that. That worked out really well for that reason. But I just said we can make sense of this. When we got into it, we said, let's break everything down to a decade born, because then you're comparing 10 year periods to 10 year periods. Everybody knows what year they were born and it just made it all more understandable.

Aaron Norris [00:17:52] That's putting it lightly. So, you know, Baby Boomers into the Baby Boomers, Gen X, Gen Y and then breaking it into 10-year cycles, it just seems a lot more sensical when it comes to trying to identify trends in the segment. One of my favorite words out of the book is Surban. Can you describe what that means?

John Burns [00:18:11] Yeah, we made that up. It's it's when, and I think the world is trending away from that right now, too. So it was bringing the best of urban to the suburbs. So urban, actually, due to a lot of local government investment, really got cleaned up a lot in the 90s and 2000s. Everyone knows how great York and San Francisco in other places have been recently. They were not that way 30 years ago. And then they became really cool and hip and the suburbs said, we want some of that in our city. And so they started zoning higher density, you know, not high rises, but 20 to the acre, detached housing or even attached. But you can do detached at that right next to retail. And so we called it Surban. And that that was really the hot thing until Covid hit.

Aaron Norris [00:19:12] So you I. You know what? I guess I thought Surban would be survive well. So you think that's a trend that the Surban is just too dense?

John Burns [00:19:20] No, I. Well, I think I shouldn't say you.. do is against aspects.

Sean O'Toole [00:19:25] Dense aspects?

John Burns [00:19:28] Well, I still think it will continue. One thing that surprised me, it was very different in this last cycle was that it used to be people would go to the suburbs and then the jobs would migrate to the suburbs because that's where the people were. And you kind of get sprawl that way. And this cycle, it was like everybody went downtown, including the jobs. And so I can't afford a house in this great location unless I get a really dense one. And so what has now shifted, I believe, is this whole proof that work from home works for a lot of people. We're seeing it. It's people are fleeing. It's not an urban flight as much as it is, I can now live 60 minutes away. Frankly, I can now live in another state. I've been given permission by my boss to do so. We can go back to where I grew up. It's a flight to more affordable housing. 

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