Today on Boomer Living we have a returning guest, Joe Anfuso, CFO of MG Properties Group, responsible for directing the financial management of company operations. He’s also an adjunct professor at the University of San Diego, teaching classes in Commercial Real Estate Finance and Investment. We’re excited to catch up and talk about how Big Data and AI data science are being put to use in real estate today, and how his company coped during this last year through the COVID-19 pandemic, and much more…[00:00] Pre-intro dialogue
[02:56] How have you been since the last time that we talked around a year ago?
[04:43] What makes MG Properties group stand out from other similar companies in terms of technology use? Do you think MG is leveraging the technology more?
[06:38] How does MG Properties use predictive analytics to measure things like delinquency rates?
[11:15] How accurate are the types of estimations? How much can one trust them without scrutiny?
[12:30] How can big data be used to develop more accurate property valuations?
[13:48] You mentioned predictive analytics. Are you using forecasting and predictive analytics to forecast market trends?
[15:56] Before data science and AI, five years ago, what was the mode of operation at MG Properties?
[17:07] What sorts of trends are you predicting in the post-pandemic world for multifamily?
[18:19] To what extent is MG Properties using Big Data to predict consumer behavior in the real estate market?
[20:04] How do you make sure that you understand the latest and greatest technology and are able to leverage this knowledge, for the company?
[22:28] Are there limitations of AI, Big Data, and predictive analytics in the real estate space?
[23:56] How can you balance relying on these technologies while also looking at them critically to make sure that we’re not putting blind faith in them?
[25:41] What has the pandemic taught you about leadership?
[28:14] Do you have anything else that you would like to add?
Joe Anfuso is a 2015 addition to MG Properties Group, responsible for directing the financial and fiscal management of company Operations, including budgeting, treasury, tax, accounting, information technology, risk management, and insurance. Prior to joining MG, Joe was the CFO and Director of Development with ColRich, a diversified privately held Real Estate company, specializing in Apartment investment, ownership, construction and management (9,400 units), land development, and home building in the Western U.S. Joe’s real estate experience also includes being the COO/CFO of Florsheim Homes, a Northern California based homebuilder/developer, with operations in CA and NV, from 2006 – 2011. Joe was also the CFO for Shea Homes San Diego from 2001-2006 and worked for the international firm Deloitte & Touche. Joe earned his BBA in Accounting and MBA from the University of San Diego. Joe is a Certified Public Accountant, in addition to possessing a California Real Estate Brokers and General Contractors License. Joe is the chairman of the Residential Real Estate Committee for Burnham-Moores Center for Real Estate. Recognized as an industry expert, Joe has been a frequent contributor on CNBC television, discussing the housing and real estate markets.
You can listen to Joe’s first appearance on the show (season1, episode3) here: Lessons Learned From Real Estate Operator And Educator Joe Anfuso
I would just think that if in this business, if you think you’re going to be able to compete without making the investments in technology, I just, you know, I think you’re being shortsighted. I, cause I can tell you our success, especially over the last year, wasn’t just what we did 12 months ago. I really believe this spans back to our commitments, five and six years ago of, making transitions in taking on the technology, We’re automated accounts payable processing, right? Automatic check writing and ACH processing, automatic onboarding of vendors. All of those things that we have just been doing little by little. Automatic tenant payments, virtual tours, all those things that you, we made investments in along the way, all paid off. And that wouldn’t have been the case, and I know other organizations where that wasn’t the case. People were scrambling to, they’re shutting offices down and then trying to figure out how to get a tour, how to get somebody in to look it up a vacant unit and all that. And I think I can honestly say that it wasn’t just one thing. It was just having that strategy over a long time. Having a commitment to making sure that you were up on your technology, that we were able to be successful.
How are you?
Good. Just a, got out of a Tuesday meeting. We have a normal Tuesday COVID meeting for what’s going on with the company.
Well, Hey, thank you so much for taking the time out of your busy day to have this conversation. So thank you. All right. Okay. Today on Boomer Living, I have a returning guest, Joe Anfuso. I originally spoke with Joe last year, so I’m excited to join him in conversation, once again. Joe is the CFO of MG Properties Group. He’s responsible for directing the financial management of the company’s operations. He’s also an adjunct professor at the university of San Diego, teaching classes in commercial real estate, finance and investment. So, I’m excited to catch up and talk about how big data and AI data science are being put into use in real estate today. So, Joe, thank you. And welcome back.
Ah, it’s my pleasure Hanh.
So, how have you been since the last time that we talk around a year ago?
Obviously we’ve had to deal with everybody else, the whole COVID pandemic. It’s been quite a learning experience, and I think technology really showed, what can be done in times of crisis. I think for our part, especially in the corporate office and at the properties, it was normally thought there were a lot of positions that just needed to be in the office every day to get their job done. For example, let’s say the accounting staff, and because of the technological investments we’ve made over the last four or five years, meaning, going into the cloud computing, doing the automatic payable, processing, things, no more check writing, all those things that we’ve made investments in over the last four or five years. When the pandemic hit, we went from everybody coming into the office five days a week, thought that’s all, that’s the way your job had to be to every accountant was gone. And then still being able to produce our financial statements in a timely manner. Being able to do our quarterly distributions to our investors in a timely manner, being able to give our information that’s needed for our institutional investors in a timely manner. Things that we’re probably going to happen for five or more years from now, we’re accelerated and everything got done. And not too much change from the standpoint of, productivity, and people working remotely. So, I think that was the, really the big thing that was learned, for us and for me over the last 12-months.
Wow, and thank God for technology, to allow us to keep staying on top. Just everything that you describe and same here. I think what has driven me to be more social, even though during a shutdown time is through technology and the learnings that I’ve gone through and hopefully share and inspire others was all due to technology. That’s a great point. Now, what makes MG Properties group stand out from other similar companies in term of technology use? Do you think you folks are leveraging , um, the, the technology a lot more?
Yeah, I think, I first, I’d like to say I benefit from this in that I’m afforded the opportunity to spend a good deal of my time on the technology side of the company and the strategic planning and the execution of strategy with regard to technology. So, I’m very fortunate. I know everybody’s different from a CFO standpoint and different operational levels. Mine has just been one where I’ve been able to spend a lot of time on technology. So, for the last six years, we’ve done a number of major implementations that have really changed the course of the company, from, to move on, to compete with, large REITs to large, players. We’re at about 20, almost 22,000 units. We’re in five States. We have about s. 74 properties, about 615 employees. So we’re large private owner operator of multifamily properties and as such, our investors we’ve got about 1400 investors. They’re relying upon us to enhance value, to manage those properties as best we can. And the only way we’re going to be able to do that and compete in our marketplaces is using technology. I do get a chance to do that. We’ve gone from everything from investment management, programs to our latest and biggest implementation, most recently. It was business intelligence, Big Data warehousing. I am being able to provide that throughout the company, and utilize and capitalize on being able to, have data. It, not only on our company, but also in our marketplaces, so we can do comparative analysis. We can do predictive analytics and all the way through. We can talk about new even prescriptive analytics when you have that data at your fingertips.
Great. Great. Yeah. So, how does MG Properties use predictive analytics to measure things like delinquency rates?
Sure. W what we do is, through business intelligence, we have the data and set up, but the program calls it. So, we actually use Yardi’s, Business Intelligence Program. We have the ability to put together data tables, they like to call widgets and provide dashboards. So that, for instance, when we first took on the project we had, in order to get the biggest bang for the buck, we had to determine what we were going to do, what we could put data on, that we can disseminate throughout the company. And we had, we had broke it down to, there was 11 reports that were being done on a weekly, quarterly basis. So, for instance, and I’m sure this is no different than what a lot of people go through, a property manager and that property manager inputs some, something into an Excel spreadsheet. That goes to the regional manager and then that regional manager, inputs that as something into a regional spreadsheet, then send that up to the senior manager and they put together from all the different regions. And then finally, it gets to executive management and somewhere along the lines, somebody missed zero. Had a fat finger mistake, and there’s also, you run the risk of some bad data. And we were able to go ahead and through business intelligence, be able to put all of those reports in data tables and be able to disseminate the information consistently throughout the organizations. And what I mean is, if it’s delinquency or vacancy or whatever the case may be, now the property manager is looking at a dashboard, which is specific to that property. The regional managers, looking at those same data, but in a regional level and can drill down. The senior manager or the executive manager can do the same thing, can look at it from a regional level, and, or a global level, and then drill down to see where there, there may be some questions. And so, everybody, I like to say is reading off the same sheet of music. And so, when everybody’s talking in management meetings, whether that’s at the property level or senior manager level, everybody now has the same data that they’re looking at. And I think it’s just makes everybody much more consistent on their reporting. It’s better reporting. There’s you know, the you’re relying on the data that’s in there, not with a bunch of different hands, touching it through the course of, putting it on copying and pasting and putting stuff in different Excel spreadsheets, and thereby giving everybody assurance as to that we’re looking at good data. And then the next, the next part of your question is, okay, so we have now our data, but now, when you’re working with a company like Yardi, that has about 15 million units on their platform. Now you can look at it and say, “Okay, what are we doing in comparative to our markets? And are we executing on our strategy for that property? And are we being competitive with other players in our markets?” And then I think that’s where you get into the predictive part of the, the data in that, let’s just say, for instance, your data’s telling you, you’ve got a couple of things. You’ve got some vacancy that’s coming up in the next 60 days. You also have marketing data that tells you where you’re getting your biggest bang for your buck, with regard to marketing spent. So now, from a predictive standpoint, you can go, we need, we have three apartments that we need to rent in the next 60 days. We also know from the data that it costs us, let’s say $300 per unit to be able to rent that from a marketing standpoint. That relates to, we know also know from that, that we need to have eight people to come look, or view the property to get that one lease. So, let’s, so you, now, you’re going, okay, “We need 24 prospects to come in. We know it’s going to cost us so much now 60 days beforehand, if we know that Zillow or apartments.com or wherever, the successes for that per property is in getting leads, we can automatically make that spend, way in advance, knowing that’s going to get the leads and provides us the numbers that we’re eventually going to get, be successful in signing leases for, to fill those vacancies well in advance of the date and keep our occupancy up and keep our net income up and keep our NOI up and so forth.” That’s, I think was a long-winded answer, but I just wanted to walk through how you get to the point to where that data becomes predictive for you.
Absolutely. I mean, you want your prospective tenants in the queue and have it filled ASAP and very minimal to no downtime as possible. So, that’s great. Now, how accurate are the types of estimations? I mean how much can one trust them without scrutiny?
I think a lot of it right at the end of the day is you still have to verify the, you have to rely on your managers, your regional managers to make sure that at the very beginning, the data is put in there soundly. But the good news is when you have that kind of data, you can pick up, you can pick up on the mistakes much quicker, because you can do some quick analysis as to know, if somebody, their lease is a three-year lease, let’s say right? Now, in some old days, when that was just paper being filed, you may not know that there’s, that’s happening, but in when you’re looking at data and all of a sudden, you’ve, you’re your occupancy and the people or the, tenants are coming in, something looks funny. You can just know right away, this one, you have all six month leases and one year leases, but you will have one here at three years and you can pick up on those kinds of mistakes instantaneously, rather than having them just not be discovered for a period of time. And that kind of data is screwing up your data table, Just because it’s not being caught. And now it’s just much easier to catch when those things happen.
Okay, so now, how can big data be used to develop more accurate property valuations?
I think it’s, it’s if you’re talking about how you can make it more valuable from the standpoint of being an owner operator? I think that, the big data is, there’s only so much juice to be squeezed out these days. And so, those that can enhance NOI and can write, create value. And that’s, you’re only going to be able to do that in the most part now through being operationally efficient. And I just don’t know any other way to be more operationally efficient going forward without technology. And so, from every different platform, like we were just talking about from a marketing spend, right? You can isolate, instead of just taking a shotgun approach to getting people in the door, getting leads in the door. Now you can actually put a, just a finite pinpoint as to what you need to do to be able to get those leads in the door without spending gross amounts of money, hoping that it’s going to get people and get leads in and for your property. I think it’s those types of operations, that from a, using that technology that will allow you to get, improve your NOI and create the value that you’re trying to on a property by property basis.
Now, you mentioned predictive analytics. So, are you using forecasting and predictive analytics to forecast market trends?
And the answer is yes, especially in the, we use big data for acquisition side. And so, from the acquisition standpoint you’ve gotta be building models that help you determine whether or not you want to be or pay the price for a property. So, think about now we have big data that we can get, not only our own properties, let’s say we’re buying something in outside the Seattle area where we own property. We have our properties. We can now look at big data on for what we’re spending on let’s say plumbing. What we’re spending for CapEx. What we’re spending for rehab. All those things. And then we can look at what the market’s paying for it because we have the big data on the marketplace. And now, we can see, maybe how come our competitors are spending less on plumbing expense than we are. And we can start to determine, okay, we need to be correcting our adjustment, our expenses to be more of what the market’s doing, because maybe it’s something we’re doing in house and when we spend more time doing things. But it, what it does is it allows our acquisitions team to go through there and go, “Look, if we can enhance our expenses, or not enhance, but if we can improve upon our expenses, we can enhance what we are able to pay for a property and be much more competitive in the bidding process.” We can predict that based on these parameters and with the data that we have over the life of the ownership. If this is a seven to 10 year hold, we have the data that tells us what the average rental increases would be. What the average increases for your other income. What the, what it looks like with regard to expenses. And so, now, our acquisition team can be much more competitive in the marketplace when they’re going out there and feel much more confident for not only us, but for our investors saying, “We’ve analyzed this, the data tells us this is what we’re doing and we can be profitable and get a great return with this data that we’re now analyzing and incorporating into our pro forma’s.”
So, let’s say before data science and AI, let’s say five years ago, what was the mode of operation?
Yeah. It was a lot of time and effort into research, right? You could use other people’s market data. You spend a lot more money using other, you know, trying to find out other market research. You used a lot of your foot soldiers, I’ll say. The people on the ground. Going out doing market studies, walking around, trying to find out what the what was going on in the marketplace, concessions, All those surveys. You could buy the data and you can, and if you didn’t trust that data from outside sources, then you went out and you did it on your own. And so, a lot of it was just, and I’d say a lot more gut feel went into the proforma as to this is what the, our experience has been. This is what we think it is. And so, what I think big data does is it allows you to validate your assumptions, right? I might feel this is it, but if the data doesn’t support it, your feeling might have been good for that year, but it’s not going to be good for the next seven years. And I think that’s where the, really the big differences is it’s validation of assumptions and information that now you can make informed decisions on.
What sorts of trends are you predicting in the post pandemic world for multifamily?
We kind of think that overall, that, especially on the West, because we’re primarily a west coast player, that the demographics just, I can’t see how they, you’re not going to continue to be in our favor. I think, and it probably that runs across most of the country as well. You look at, especially in the West, right? You probably have a better chance of being drafted to be the point guard for the Lakers than you do, to be able to build something in Los Angeles or San Diego County, or anywhere in California. If you’re owning and rehabbing multifamily properties, you’re just going to be by virtue of demographics by population. You’re going to be in a good position going forward because people need a place to live. And, as long as there’s household formation, as long as the economy continues to create some jobs, the economic engine continues to move forward. Over time. I just think that the, the big prediction for multifamily is that it will still be a desirable way for people to live, and need housing. And I just see that as continuing over the coming weeks, months, years, and decades.
Now, to what extent is MG Properties using Big Data to predict consumer behavior in the real estate market?
It’s well, I think a couple of different ways, right? It’s that the type of property, the meaning, what you can see from your data, what people are attracted to. Is it a gym? Is it a dog parks? Is it all those things that you, especially when you have a big portfolio like ours and you have, you can research other people’s portfolios or other markets. You can go in and start to determine what people’s trends are and what they’re really looking for. Let’s say, a, tennis courts were big 20 years ago, right? Every, every place had a tennis court and now those things are being converted into sports courts. It’s not just exclusive for tennis it’s, or they’re, they’re putting you’re just building a bigger gym out on what used to be a tennis court. So, because people would rather have exercise equipment or a yoga studio or know, a coffee shop. Anything like that, that where people are much more attractive. Having Wi-Fi being able to sit down like at a Starbucks and we’d go through all of that. And that’s personalities use big data to see what the changes are. And then when you either own or you go to buy, you start to make sure that’s what you’re incorporating into your buy decision. If the CapEx spend is, we need to have a lounge, a wifi lounge with coffee machines. That’s what you’re going to put your CapEx in for. It’s not going to be to resurface the tennis court. Does that, hopefully that makes sense.
So now, with the technology changing at the speed of light, and it’s hard to stay on top of all the advancements. So, how do you make sure that you understand the latest and greatest technology and are able to leverage this knowledge, for the company?
Yeah. And that’s a great question. And again, I’m fortunate in this regard. We take really a two-pronged approach at making sure that we’re up to date on technology. The first is, as a company we made a commitment to invest in a venture fund, which is specific, almost specific to multi-family housing. So, we’re a limited partner. We’ve made the investment. I’m one of the LPs that sits on the meetings and so forth. And we get the opportunity by virtue of being in the fund that we are being exposed early on to startup companies and newer companies that are trying to build a better mouse trap for multifamily housing. Whether that’s payment processing or whatever the case may be, smart home technology, all those things. We get an opportunity not only to hear from the, the venture fund, but also the companies themselves, when they’re making pitches. So, we can then leverage that. Part of being in this kind of fund is the ability to sample the wares and be able to, roll some stuff out on a limited basis at let’s say a region or an area and see if it works, right? Does that new thermostat, key lock, smart home technology work and will people pay for it? And so, it gives us the ability to get that new technology and be part of it. And so, that’s one area that we, as a company, try to ensure that we’re getting, staying on the cutting edge and seeing new technology that comes out. The next piece is really from an internal standpoint, is we make it a commitment as a company to make sure that we’re always evaluating technology and looking. We have an innovation committee made up of, I oversee, that’s usually made up of for obvious reasons, the younger cohort of the company, and, getting information from the younger cohort as to, they’re being, they’re more technologically savvy, what they see as a benefit to the company. And then from there we can do more research and then do, a, they’ll actually do presentations to the senior management group to show what they believe are the trends that are coming up, and what technology is out there that might satisfy that trend.
Now, are there limitations of AI, Big Data, and predictive analytics in the real estate space? So, are there limitations, you think?
I think it’s the old saying analysis paralysis. You have to watch out what you’re doing with big data. In our case, like I said earlier, we were looking at a way to get the biggest bang for the buck. And for us, it was looking at what the reporting was going on and how can we emulate that quickly and get a benefit from it? I think, you can think it, overthink it too much and try to solve every problem, every issue by what big data has. And, I think it, when you start to complicate it in that regard, you’re just going to be spinning your wheels as to trying to find out what it’s the data is telling you. And maybe trying to, at the end, you’re looking for, what’s the old saying goes “You’re you’re looking for a solution that has no problem.”, or something. You’ve got you’ve just trying, you’re just over analyzing everything too much and losing focus on the strategy of your business. It is, I think that’s what you have to be disciplined, to know what you want with the data and get it measured, put out the right reporting and focus on those items, those key performance indicators that are your business, that works for your business and use it to do that. You can experiment along the way, but don’t lose the focus and keep moving forward, and use the data to your advantage.
That’s very great advice. So, how can you balance relying on these technologies while also looking at them critically to make sure that we’re not putting blind faith in them, kind of aligns with what you just said?
I think part of this is having a strategic plan, and then being able to use the technology to make sure that you’re following that plan. And so, this way you stay focused with regard to what it is, what is the data has and what the data is trying to do for you. So, I know, in, in our case, we have the major key performance indicators. We have a strategy in place for our regions and for our properties, right? There’s property budgets and so forth. And so, the data should be supporting what you’re trying to do strategically for that property. If it’s a, it’s a value add play, and you’re trying to get to a point to where you need a certain return on your Capex investment and a certain increase in, rents because of that, the data can help you support that and looking into the future and say, “Okay, is, are we measuring up to what we thought, what the strategy was for this property? Are we filing, falling behind on our strategy or are we ahead of our strategy and why?” And so, I think it’s, it’s that type of information that can help you. Make sure that you’re sticking with the strategy and that you’re measuring your strategy. And so, that means you have to have a strategy and not just think that big data is going to give you a strategy.
Makes sense. Very good. Yeah. I, that’s what I had in mind is you use it. Um, You gotta know what your objectives are and what data you’re trying to gather. So, it’s a combination of data with your gut feel, right? You can’t overanalyze perhaps looking for a problem that doesn’t exist. So, it’s a combination of both. All right. So, I’m going to, I’m going to talk a little bit about leadership during the midst of the pandemic. Now, what has the pandemic taught you about leadership?
I think it is, what it’s taught me is you have to show the team, that you can overcome, whatever problem is dealt. And your team’s going to look up to you because nobody knows what a pandemic is. Truth be told, I never thought about it being involved when there’s a pandemic. And how, the team reacts to your ability to solve issues. And I think I was probably luckier than most, because, like I said, I’ve been spending a lot of time on the technology side. I knew from the standpoint of technology that, we had made the migration to Office 365. We had everything for us, is in the cloud. We no longer are working off in-house networks to support. Our network is up in the cloud. We use third party apps, like, a, Yardi. So, that’s in the cloud. I was confident and showed that confidence, to the team that we were going to be successful in working remotely and making all of our deadlines and producing reports for our investors and producing returns and distributions for our investors, because I was confident that we have the infrastructure in place to be able to do that. And, because of that, I think the team really understood. We immediately, we had laptops in everybody’s hands. We had communication. I made sure all the communication was working. We, everybody was able to login outside the office. Everybody had their security protocols in place. All those things gave everybody the confidence that, “Oh, I can log on from home. I can log on to my Yardi accounting software, GL package and get everything done. Everything else I’m looking at, I can get from emails and so forth. And, we did not, in a year we have not missed a deadline, during the whole time. And I think, once the team starts to realize that you’ve got the confidence in them and you have the confidence in the system, then it just became the normal part of operations. And I think that’s probably my biggest takeaway is, you, if luck favors the prepared and in our case, you, we thought we were very well-prepared. And it, it gave the teams confidence in the leadership.
Very good. Boy, in a time where you would imagine that the pandemic would uncover so many weaknesses, kinks in the system. But, you and your team, your company turned it into all the positives using technology. So, that’s great. That’s great. Do you have anything else that you would like to add?
I would just think that if in this business, if you think you’re going to be able to compete without making the investments in technology, I just, you know, I think you’re being shortsighted. I, cause I can tell you our success, especially over the last year, wasn’t just what we did 12 months ago. I really believe this spans back to our commitments, five and six years ago of, making transitions in taking on the technology, We’re automated accounts payable processing, right? Automatic check writing and ACH processing, automatic onboarding of vendors. All of those things that we have just been doing little by little. Automatic tenant payments virtual tours, all those things that, you, we made investments in along the way, all paid off. And that wouldn’t have been the case, and I know other organizations where that wasn’t the case. People were scrambling to, they’re shutting offices down and then trying to figure out how to get a tour, how to get somebody in to look it up a vacant unit and all that. And I think. I can honestly say that it wasn’t just one thing. It was just having that strategy over a long time. Having a commitment to making sure that you were up on your technology, that we were able to be successful.
Great. I mean, that’s, that’s awesome. I concur with everything that you’re saying and, wow. What a blessing to not only, stay afloat, but on top and ahead, for your investors, for your tenants. And it’s all, a lot of it is attributed to technology. So, that’s great. That’s great.
And I would say to your young folks out there, like I tell the students, I, if you’ve got, even if you’re older, you have kids and so forth that are in the business or you, or want to be in the business. Look, I think the younger generation is on the precipice of a real estate boom for technology. And, the younger cohort, the kids that I’m teaching that are coming out of school, they’re well-prepared, right, to work in the data analytics field, to, even in real estate. They’re working business intelligence. They’re working, any of the big data fields where the market is going. It’s not somebody like me, who’s been in, for 35 years. It’s going to be somebody that comes out that grew up with a cell phone in their hand and understands, how to work technology. That’s, they are going to be the beneficiaries, of the future. And I really mean that. I think, the young people and especially in the real estate industry with all the investment that’s going into new technology and everything we talked about from smart home technology to payment technology, to you name it. They are going to benefit and they will help organizations as they come out.
I agree. So, basically, undergraduate, students studying computer science, data analytics, data science, and so forth. So, there is a bright future for all of you.
I agree, especially, you see those degrees out there now, that are real estate degrees combined with finance degrees, combined with, some kind of data degree and digital media. And any of those things where you are just cognizant of, digitized information and Big Data information in your industry. I just think you’re going to be a benefit to anybody that you, you go to work for.
I agree. Well, thank you. Thank you so much. I enjoyed this conversation and I’m so glad that, we had this opportunity for you to come back and enjoy me again. So, thank you.
It was my pleasure and hopefully we can do it again and love staying in contact.
Okay Take care.
Take care. Bye-bye.