By Mark Christenson
President, International/CTO

Recently we heard from an operator that their average rent per site was lower than that of one of their competitor’s. We consider measuring and analyzing network rents to be one of our specialties, and we were curious how they determined this laudable accomplishment. They said that they looked at an annual report from their competitor and simply divided the amount listed for rent by the estimated number of sites in the competitor’s network.

Although that would provide a ballpark figure, we suggested that a bit more analysis is required to understand whether or not their rent is higher or lower.

The reason we suggested that more work needs to be done is because although their analysis did provide a generalized estimate of a particular expense item, the one or two line items used from that annual report do not necessarily provide a level of accuracy against which a comparison should be made. For example, although simply dividing the number of sites into the total rent does give an average rent per site, it does not consider how that total rent is being calculated. Apart from lease contract-mandated rent itself, there may be other items that can significantly skew the numbers enough that it is not an apples-to-apples comparison. In other words, is the rent line item only showing the actual rent being paid to a landlord, or are other factors included or even netted against it? At least one operator in the world nets colocation revenue for shared sites against the network rent, significantly decreasing the apparent rent. Analysis such as this could lead to a lost opportunity to reduce the actual rents being paid to landlords, or create a false sense of security if this metric is only compared against other operators and those other operators are not calculating rent the same way.

Another example that could significantly impact the validity of the comparison is that some operators have significant “owned tower” portfolios thus lowering the average rent since those sites will have zero rent, or perhaps a minimal ground rent that is much less than the rent associated with a tower site or rooftop. (Although there is a depreciation expense from the capital expenditure, it will likely show up elsewhere in a financial report).

These two examples alone can provide either a false sense of high performance (“our average rents are 10% lower than the competition—great!”) or a false sense of low performance (“darn, our average rents are 15% higher”).

To compound the potential lack of accuracy, we contend that the correct comparison metric should not even be the rent being paid by a competitor. Instead, an operator should compare what its rent could be if it managed this critical real estate asset like it manages the other segments of its real estate portfolio (office space and retail space). In other words, rent should be compared against what the rent would be from another landlord in the same area. We have found that, on a per-square-foot or per-square-meter basis, operators pay rents 60-100% higher than space in the same geographic areas—and this has held true for years, regardless of whether we are looking at rural areas in the United States or city centers in Europe or anywhere else.

The wireless industry has always had its own, isolated view of network real estate costs. The result of which is that operators around the world have overpaid for rents since the first networks were deployed over 30 years ago. But, in order to calculate the size of the opportunity and how it can be addressed, it is important to consistently calculate the rent and compare it consistently as well.