It’s time to talk about square foot per capita again. I have run into more and more issues with that metric and think it is time to permanently interrupt the myth that still pervades our industry. That myth is:
You can get a clear picture of supply/demand in a trade area by looking at what the square feet of existing storage supply is per person.
That just isn’t the case anymore, if it ever was true. No other industry uses this metric as the most important one to calculate demand for a product that I am aware of. If there is, let me know. In my real estate practice, I have run many gap analysis reports for different retail users, and square foot per capita has never come up once as a measurement for demand.
There are just too many variables today that have an impact on storage demand that this simple metric doesn’t account for. Here are some:
1. Competing Facilities. Even if this metric was gospel, how it is used today can be misleading. We look at a trade area and use drive time or a 3-to-5-mile radius. Any facility within the area is considered square footage in that trade area. This can be misleading for two reasons:
a. Not all facilities are the same. One might be very old with no office, no security, and on gravel, while another might be a shiny new facility with all the bells and whistles. The older facility will most likely draw a much smaller portion of the trade area population as potential customers.
b. Each existing facility has its own trade area. If your trade area is a 5-mile radius, and Facility B is 4.9 miles away, Facility B’s trade area will, in all reality, be overlapping your trade area only 20% or so.
2. Population Demographics. The square foot per capita doesn’t take into account any of a particular trade area’s demographic data. For example:
a. If your median income is $65,000 or more in most trade areas, the average person in that area will gravitate toward nicer storage products. Half of the existing storage in that trade area may not be much of a factor in reality.
b. The myth metric doesn’t take into account population growth for an area, education level for an area (higher-educated people tend to keep their storage longer and can handle economic downturns better).
c. The myth metric doesn’t take into account the density of the population. The more dense the population, the less square foot per capita is relevant, especially in a growing area.
3. Quality of the Trade Area. The myth metric doesn’t account for the quality of an area. Not only is median income important to us, but the quality of retail in the area. That usually tells us that it is an economically healthy trade area. Are there a lot of grocery-anchored centers? Are there power centers? Are there national retail chains? Has the school tax increased recently? These and more indicate a trade area that is healthy and can sustain storage during any cycle we may find ourselves in.
4. Visibility. I have found visibility has a major impact on lease-up and the value of each lease signed at a given facility. The myth metric in no way takes this into account. There could be 30% or more facilities in a trade area that have no, or very limited, visibility, and they count just as much as a shiny new project on a major road. This just isn’t the case in reality.
5. Discounts. Square foot per capita doesn’t account for the number of REITs or sophisticated players in the trade area. It doesn’t account for discounting going on, or the lack of discounting that may be occurring.
One of the most important things subscription services offer, in my opinion, is live scraping of competitor websites in a trade area. I have seen countless trade areas that are “overbuilt” with more than 9 or 10 square feet per capita, but there is no discounting occurring (or very little) by people who use dynamic pricing. This usually indicates strong demand in that area regardless of what the square foot per capita is.
Or conversely, there may be low square foot per capita, but offering rates are extremely low. I have seen rates 50% or more lower than what we underwrote being offered.
For these reasons, and probably a few more I haven’t mentioned, it is time to shed light on the ongoing myth in this industry. I would love to see someone smarter than me design an algorithm that would be an effective way to calculate a supply/demand metric that gives more quality information as to the actual demand for storage.
I think it is time to terminate the myth metric our industry uses, or at least give it a back seat.
