A truly great rent forecast solution takes all known data from the current rent roll and applies appropriate assumptions to implement an expected value algorithm for each unit that can then aggregate up to any level of market or management hierarchy.
Here are examples of what great inputs should be:
Anyone with experience in rental housing knows that rents do not grow steadily throughout the year. There are clear high, low and shoulder seasons that must be modeled to create good forecasts.
Peak-to-Peak Rent Growth
No budget or forecast can be done without input defining how much rents are expected to grow over the period. Combined with rent seasonality, the model can then calculate market rents over the entire period of the budget or forecast.
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Renewal retention rates
The percentage of expirations that are renewed. This drives the way the expected value (EV) model* assesses how much to apply new rents and vacancy loss vs how much to apply the expected renewal rents with no vacancy loss.
Renewal Rent Capture Percentage
This assumption helps the model determine renewal rents. It’s one thing to have new rent modeled as a single number by unit type for each month; however, that doesn’t work well for renewals since renewal offers are typically based on a combination of both the market rent for a unit and the corresponding expiring rent for that resident. This can be easily expressed as a percentage of that difference or “gap.” In budgeting and forecasting, be careful to express that parameter as the percentage of the gap that will be “achieved,” not necessarily the percentage used to calculate the renewal offer. If the two are the same, then you are implying zero negotiations will happen. That may be desirable; however, it’s rarely true.
Vacant Days to Release
This informs the EV model about the vacancy loss to calculate for the portion of the model that covers a home changing tenants.
Average Lease Term
Average LT is needed as part of the new lease branch of the EV model.
Needed to appropriately calculate gross vs net rents
Bad Debt Percentage
Usually, this is based on an analysis of history with possible tweaks up or down depending on executive opinions on expected future improvement or degradation in residents’ financial solvency.
Early Termination Expectations
Another assumption is needed to refine the model. As with bad debt, it is usually based on an analysis of history with possible tweaks up or down depending on executive opinions on future changes in market conditions.
Getting rent forecasts right is a notoriously difficult challenge. However, this can be made easy for operators if “the genius is built into the system” and if the process of configuring the model is made as simple as possible. These drivers play a large role in a successful multifamily budget. We go into more detail on these tips in our Multifamily Budget Guide Ebook.
*EV Model calculates unit-level results for Rental Income. The probability of a renewal is multiplied by the cashflow for a renewal & the probability of a moveout is multiplied by the cashflow for a moveout. These 2 amounts are added together to create the rent result, as well as the metric data such as move-ins, move-outs and occupied units.