Quick Math Versus Detailed Math
Welcome to The Real Estate Espresso Podcast, your morning shot of what’s new in the world of real estate investing. I’m your host, Victor Menasce.
On today’s show we’re talking about how to model a project. I often hear people advocating for a simple spreadsheet to perform quick calculations. There was a point in time when I too used these simpler tools to make fast decisions. There’s a trade-off in any project where speed is absolutely a component of a quality outcome. As time has progressed, I’m less inclined to rely on quick math for anything.
The reason for not relying on quick math is that when bank leverage is involved, which it often is, the analysis becomes increasingly sensitive to small changes. And a small change can cause a project to flip from attractive to upside-down in a heartbeat. So I want to be working with a financial model that takes into account all of the required elements. Things like interest reserves or lender fees and legal fees are essential to factor into the analysis.
An inaccurate model is just that: inaccurate. And an inaccurate model holds no value. We have experience with projects where the cost for some line items have been estimated or based on hard quotes. Regardless, it didn’t matter whether the estimate or the quote was wrong. If the error is large, the subcontractor will simply walk away and refuse to complete the work until a new scope is agreed to.
We experienced a massive cost overrun, for example, on the site work at a 100 unit apartment complex that’s currently in construction. We thought we had done a good job on the geotech, but in between those test locations, we discovered organic material in the soil that was not suitable for building. That material needed to be removed, exported from the site, and replaced with more suitable material, which was then compacted in 12-inch lifts to ensure a stable substrate under the building. This alone consumed the majority of our contingency fund.
There are certain metrics that become extremely sensitive to changes. Construction cost is one of them. Capital cost is another. We often experience changes in market conditions, which can affect the capital structure. A lender might change their lending policy, requiring the borrower to introduce additional equity to the project just to satisfy the lender’s requirements.
If your financial model doesn’t take these factors into account and merely relies on so-called rules of thumb, then there’s a high likelihood that your project assumptions will be way off. Now, this doesn’t mean you need a detailed construction quote or a completed permit-ready design before you can even start the underwriting process. But you do need to have good data sets as a starting point, and a solid market study and a strong set of rental comps at your disposal.
One of the biggest mistakes I often see is underwriters assuming that rents will continue to increase consistently year after year. That can happen in markets that are rent controlled, but in markets that see larger changes between supply and demand, there are periods where rent increases can fall below inflation averages. When that happens, expenses increase but income doesn’t and profit margins get squeezed. If your project can’t cope in that situation, then you’re at high risk of having your project turn upside down.
An acute sensitivity analysis will reveal vulnerabilities in your financial model. An experienced underwriter who’s accustomed to working with institutional quality investors will quickly identify such rookie mistakes. The best way to identify these types of issues is by studying projects that are currently for sale in a distressed situation.
There are many examples to choose from. Each one of these deals would’ve been presented to investors a few years ago with a rosy picture, an investment rate of return forecast that simply didn’t pan out. So, where were the mistakes? Were the assumptions about rents, leverage, interest rates, maintenance costs or insurance and property taxes too optimistic? Usually, a project struggles when it fails on multiple metrics simultaneously, not just one.
Many underwriting software options have a very simplistic structure. For example, if your project has multiple layers of financing, most tools cannot handle that. Yet, it’s a perfectly legitimate debt structure. Many projects experience it and if your tools can’t handle those real-world situations, then the analysis is simply too academic and therefore, not useful.
This was the main reason why we developed our own underwriting software in-house. We didn’t start out wanting a software development project, it happened out of necessity. And it is one of the reasons many of our consulting clients approach us; because of the depth and accuracy of our underwriting process.
As you think about it, quick is good but detailed is better. Make the rest of your day an awesome one. Let’s go make some great things happen. We’ll talk again tomorrow.
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