Thinking in Detail About Vacancy

One of things we commonly see across many of the multifamily owners and operators we work with is an oversimplification of metrics.

Oftentimes this is in service of setting up a North Star for a period of time, whether it’s a month, a quarter, or a year.

I want to focus on vacancy rate specifically, because this is where the problem feels most obvious, and the area where we have the most experience to back our reasoning.

Setting up a single “vacancy rate” metric with a goal - maybe “keep vacancy loss below 6% of GPR for the year” - sounds good on paper, but leaves little guidance for your teams to actually make good on that goal.

In other words, if I’m an operations director at XYZ residential and am told that keeping vacancy loss below 6% is our annual goal, I have a totally blank expression on, because that number tells me almost nothing about what’s actually going on, and how it needs to be improved.

Yet time and time again, when we ask operators what their goals are and tell them to elaborate, they stay at that broad, north star level.

So let’s change that, and dive into a first principles investigation of vacancy loss and what’s actually going on.

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What is Vacancy Loss?

Simple enough question, right? It’s the loss in rental income as a result of units going vacant for any period of time.

What’s interesting though, is that there are actually two very different factors influencing that number.

1. How often are units going vacant in that period of time?
2. How many days are those vacant units sitting on the market once they become vacant?

Intuitively, the factors that influence one might not influence two, and vice versa. How often units go vacant (in a year) depends on your average lease length, the lease renewal rate, and the rate of early terminations (whether voluntary or involuntary).

Meanwhile, how many days the average vacant unit sits for is more or less made up of two factors: (1) how competitive the listing is at the time of vacancy against the market as a whole, and (2) how good (or bad) your team is at getting a vacant unit turned, listed, and a new resident moved in.

If we had to create a simple formula for vacancy loss, we might calculate it as:

Vacancy Loss = Number of Units X Frequency of Vacancies X Severity of Vacancies

OR

Vacancy Loss = Number of Units X (12 / Lease length X (1 - Lease Renewal Rate) + Early Termination Rate) X (Days on Market X Average Rent)

Put into practice, the vacancy loss for an example apartment ABC might look like:

100 units X (12 / 13 months X (1 - 60% renewal rate) + 5% early termination rate) X (50 days on market X $1,500)

WHICH EQUALS:

$103,372 in vacancy loss

OR

5.74% vacancy loss as a percentage of GPR ($1,800,000 in this example)

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A Few Observations

Taking a look at this breakdown of vacancy loss, we can make a few simple observations:

1. Many of these factors are completely out of your control as an owner, even more so as an operator.
2. Some of these factors have a natural floor or ceiling; e.g. there are residents that will not renew their lease no matter how many discounts or concessions you give them, because they are moving, end of story.
3. Some factors that are very consequential to vacancy loss aren’t being reported consistently at all, like average days on market.

These observations lead to some pretty interesting takeaways that may not be immediately obvious.

For example, say that one of our regional managers found a way to reduce time on market by 5 days on average, by cutting an observable gap in time to re-list. What impact would that make on overall building vacancy loss?

Whatever the answer you had in your head, how did it compare to the actual number of 0.63% (or around $10,000)?

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Putting This Into Action

Obviously, these numbers are just examples, and should be treated like examples.

But what the numbers reveal is fascinating—how many important tactical changes have been abandoned that sounded trivial, when the impact was actually significant? How many decisions that felt important were actually completely trivial based on the math?

At the end of the day, this framework is only one way of thinking, and is certainly not the end-all-be-all of modeling vacancy loss for buildings.

But if you’re still giving your teams goals built around improvements to north star metrics that weren’t based on a bottoms-up analysis of the fundamentals—maybe this is a sign to change things for 2025.