For many investors, their real estate financial modeling may have worked well throughout the historic bull run of the 2010s. But then COVID-19 hit in March 2020, putting everything at risk.
As Mike Tyson once said, “Everybody has a plan until they get punched in the mouth.”
For too many investment firms, when the Coronavirus delivered that punch, their financial models became useless in the blink of an eye.
- Developers had to put construction on hold
- Fix-and-flippers had to account for slower sales
Multifamily investors had to factor in delayed rent payments
Industrial property investors had to consider that their tenants could go bankrupt
- Commercial and retail property investors had to prepare for a sharp decline in foot traffic
No wonder Bank of America called the second quarter of 2020 the toughest ever for landlords.
COVID-19 should serve as motivation to improve real estate financial modeling. After all, if our models don’t prepare us for all the punches we could take, how useful are they really?
Ultimately, what you need is multi-year real estate financial modeling that prepares you for any scenario. This way, you know what route to take when something as unprecedented as Coronavirus arrives.
In this guide, we’ll discuss the goal of real estate financial modeling, as well as why traditional models leave you unprepared for all the challenges you could encounter. We’ll then show you how to plan around an uncertain future with intelligent financial modeling software.
The goal of real estate financial modeling
“To buy or not to buy!” That is the question.
Debt and equity investors use real estate financial modeling to analyze whether or not to invest in a property. To create the model, analysts calculate and show potential returns and risks.
For decision-makers, such as the CFO at the investment firm and board of directors, the model helps answer key high-level questions.
For example, a real estate investment company may use real estate financial modeling to answer the following:
- If we acquire a multifamily property for $30 million and hold it for four years, could we earn a 13% annualized return on the investment?
- If we construct a new office tower by spending $50 million, then find tenants and later sell the asset, could we achieve a 20% annualized return?
- If we buy an apartment complex for $10 million, spend $5 million renovating it, and then find tenants, could we sell the complex upon stabilization at a 15% profit?
Good real estate financial modeling should answer such high-level questions, giving you a range of returns. After examining the model, leadership should have a clear vision of whether to invest and what they need to do to realize profit goals.
How does real estate financial modeling work?
Real estate financial modeling involves all the commonly used metrics, such as loan to value (LTV), loan to cost (LTC), net operating income (NOI), cap rate, the amortization period, and internal rate of return (IRR).
Modeling also involves an analysis of the type of property and asset class, the market, and the overall value (did you buy at a discount?).
Here’s how analysts go about building the real estate financial model:
Establish transaction assumptions.This could include property acquisition price, renovation costs, and exit price.
Project the time period. For development projects, the construction period is a key part of the modeling.
Build operating assumptions. This could be high level (such as gross rental income) or granular (such as concessions for individual tenants).
Create the pro forma—a sort of combined income and cash flow statement. This will include key metrics such as net operating income and cash flow to equity, as well as debt repayments.
Calculate the returns. The model should include cash flow projections throughout all phases of the investment.
Run different scenarios. For example, the model may calculate how net operating income changes if an economic downturn leads to a lower occupancy rate.
Pass the model off to decision-makers. The leaders make a decision based on their own criteria and their model’s various projections for different scenarios.
Why traditional real estate financial models come up short
Take a look at a real estate financial model for a hotel investment.
As you can see, this financial model for a hotel investment does what you need to see key metrics, such as the levered IRR and unlevered IRR. It includes general assumptions, such as:
- General assumptions about the forecast period, transaction costs, etc
- 1% inflation and 1% annual growth in room prices
- An occupancy rate of 60% and an average daily rate of $150 (ADR)
- Depreciation periods for the building, cars, equipment, etc
- Operating costs from staff, utilities, maintenance, etc
You may even notice that this real estate financial model allows for scenario analysis. You can see how the IRR changes as the occupancy rate and ADR change, or if the purchase price and holding period change. You can also analyze how fluctuations in the cost of sales and valuation multiples affect returns.
That should be enough for you to make high-level investment decisions, right?
But if something as unexpected as COVID-19 hits, you won’t be prepared.
This sort of real estate financial model is static. The analyst runs the numbers on the hotel deal and then hands it to a CFO, who takes it to the board. By then, the situation has almost certainly changed. For instance, perhaps interest rates went up, and debt will be more expensive.
The spreadsheet relies too much on manual input. You could incorporate different assumptions and run different scenarios, but you’ll have to build more versions of the model. This wastes resources and leaves you playing catch up.
The model is vulnerable to mistakes. 90% of spreadsheets contain mistakes, mainly because they’re overly complex and require constant refining to ensure data aligns across the model’s spreadsheets.
The model is two-dimensional. It can’t test unlimited assumptions and scenarios at once. You can change inputs to see how it would impact returns, but you enable multiple scenarios to co-exist at once.
While traditional real estate financial modeling is thorough, its static, manual, and mistake-prone nature mean investment firms aren’t getting what they need.
In other words, a spreadsheet isn’t built to be a financial model. Real estate firms require a multi-dimensional, dynamic model that prepares them to adapt to any industry shift or economic condition.
An agile, intelligent modeling approach
Remember the goal of real estate financial modeling. You want to answer high-level questions, like:
- Should we buy this multifamily property?
- Will buying this land and building an industrial warehouse be profitable?
- What sort of investment strategy should we employ (buy-and-sell, fix-and-flip, fix-and-rent, etc.)?
- Can we achieve our desired ROI in bad market conditions?
As we’ve mentioned above, traditional real estate financial models may give you solid projections going into an investment, but they leave you unable to adapt and re-strategize in real time.
The best real estate financial models enable you to answer tomorrow’s questions today. They put a plan in place for whatever tomorrow brings and give you the tools to take successful action.
Now, you may be asking: What sort of real estate financial model could offer that?
Well, think of all that you can do with a tool like Photoshop. If you add in a landscape, you can see what it looks like if a storm came. And you have the tools at your disposal to either give yourself shelter from the storm or stop the storm altogether.
Even better, as you add new elements into that landscape, you can still maintain the integrity of the image. You can go back and examine different environments.
Wouldn’t it be helpful if your real estate financial model could do that?
In short, your financial models for real estate investments should be a sandbox with Photoshop-style layering capabilities. They should also be out-of-the-box solutions that don't involve wasting time on manual builds.
With this sort of model, you could test multiple scenarios at once, envision every possible future reality, and plan accordingly. And no matter what the future brings, you’ll know what strategy to utilize and how to execute with success.
Synario: the financial modeling solution that takes you further
We saw the shortcomings of traditional financial models in real estate. So, we created something better: Synario.
Synario is an out-of-box financial modeling solution that allows for real-time analysis and changes. It’s also quite powerful, with multi-dimensional layering capabilities like Photoshop. The tools make running multiple scenarios at once as easy as clicking a button and sliding a toggle bar.
With an intelligent, agile modeling solution, real estate firms can get out of building static financial modeling frameworks, which waste time and have shortcomings anyway. And they can focus more on the more important decisions, like figuring out which property will deliver the best ROI. They can also better mitigate risks by accounting for all scenarios and potential challenges, such as a pandemic.
Thanks to Synario’s powerful visuals, CFOs can also provide more clear recommendations to stakeholders. This way, everyone gets on the same page, and all team members understand what’s needed to succeed with a real estate investment.
Are you ready to build better financial models for your real estate firm?