For our next installment of Data Dialogues, our Chief Marketing Officer Erin Crapser talked to Brad Dillman, Chief Economist at Cortland, about two metrics that are essential to commercial real estate forecasting: rent growth and submarket scoring.
Erin Crapser: What kinds of insights or metrics have you seen teams at Cortland really embrace and be excited about?
Brad Dillman: Above all, it’s been two metrics: The first, of course, is rent growth. This really came out of a different macro-cyclical interpretation that we had than what third-party data providers had. Back in 2019, as we approached the coronavirus pandemic, we started to think about what the recovery from the pandemic would look like. There was a need to test all these different go-forward assumptions in order to quantify a go-forward view. So within that context, obviously rent growth is a critical estimate when it comes down to underwriting models and actually looking at a specific investment. And so, for that, it’s been the one, single metric that’s used out of the 50 or 60 different metrics that we actually characterize and forecast. That’s consistently the most used.
Another one, then, becomes an amalgamation of all those which are submarket scoring models. So, when we think about our own ability to say, OK, how do we think about markets? And rather than have this be OK, who went and visited Phoenix yesterday and is all excited about that market, it turns into something that is a very ordered process. This is something that’s not perfect, but it is nonetheless objective and consistent. It’s a way of allowing us to provide some type of objectivity about how we think about markets. It’s not necessarily the whole story. We have our operational side. We have all this other thinking that we need to really think about before we’d move into some other market or pursue a different sub-market type of strategy. But the point is this serves as one very objective measure that can help form guardrails around how we think about markets.
So, these different kinds of scores are done at the sub-market level, they’re done at the MSA level, they’re done related to our open-ended fund, they’re done related to value-add strategies, they’re done related to development. They allow us to look at all these different sub-markets and markets according to these strategies. And, of course, that’s very important as we watch these different opportunities from a geographical perspective come into play at one point in time and move out of play and we can always focus on that top part of the distribution.
And then, of course, it’s worth underscoring that all of this is done with our own projections, with our own view about where we think the overall economy is going, where we think multifamily is going and how we can design models that will reflect our internal analytics as well as our internal operation data on a go-forward basis.
What is the value of creating your own submarket scoring system?
BD: It helps triage deals, too, if you think about it. Because if you’ve got all your submarkets, let’s say, ranked according to some metric, or maybe they’re just graded like a triple A or triple B submarket or whatever symbolism one wants to use. The point is you can very easily triage things and say OK, this is really not fitting the box according to our research. Now, that doesn’t mean you don’t do it. It just means you’ve got a tougher hill to climb. So people can take that metric and go No, I’m going to abandon that or Yes, I’m going to continue to pursue this one.
The area where this really becomes important is (well, it’s important at the individual investment level and as we’re growing our concentration in different markets) but as we think about just overall business planning. What new market are we going to enter? What market that we’re currently in do we want to expand in? And the research models are going to inform that. That becomes critical if we think about how the business itself is going to grow, where we need to end up hiring people, what other resources we might need because of the kind of scale we’re projecting we should be aiming to achieve in a specific geography.
EC: You were just talking about a very high level as well a market-by-market, deal-by-deal level. We talk so much about resource allocation and capital allocation, but for a lot of our clients it’s really about time allocation. Where are you as a firm as well as you as an individual going to spend your time? And you need, as you said, ways to triage, ways to prioritize. And that’s an area where I think it’s important to have a robust set of data inputs as well as a team to analyze them in the right way.
BD: Yeah, I would definitely agree with you. And not only that. Once you have a data system built out you can into a lot of automated processes. So, we’re starting to do more and more underwriting at our corporate headquarters location as opposed to out in the field. Just because so much information is in data now it can be done by people who are far more technical and can do a lot more fancy things in Excel and other software than what people who are close to the real estate can do. Obviously there are still boots on the ground as people are still visiting every asset and walking units.
But once you do have a system of data flowing you can really start to automate a lot of the processes. And I don’t want to say automation in the sense of eliminating people. They’re just re-tasked to do other things because it’s no longer necessary to have an analyst sit there and query something on CoStar, pull out a data point, punch it into Excel manually, make a mistake while doing so. You don’t need to do that anymore because everything can live within your own system. Data moves a lot faster than people.
