Underwriting an extended stay hotel using length-of-stay metrics can better inform bottom-line projections, according to Jeremy Gilston, Manager of Real Estate Revenue Strategy. With that in mind, we’ll explore a recent case study that sheds light on how Kalibri Labs' more granular data set led an investor to more accurately assess an extended stay transaction.
A mid-sized hotel investment firm was looking to acquire an upscale full-service property in a prominent Midwest Suburb that converted a year prior from a DoubleTree by Hilton to an upscale extended stay property. The converted hotel had not realized its anticipated performance growth and was underperforming in the market. In assessing this deal, leadership believed there was considerable upside opportunity by increasing average length of stay and thus mitigating some operational expense with room turnover. They needed a way to understand just how much extended stay demand was achievable in order to more accurately project top-line performance and associated expenses.
When underwriting the property based on traditional data sources at first, this investor’s initial calculations did not get them close enough to the asking price to put in a competitive offer. However, they still believed their hypothesis and sought out more granular data for their due diligence to project more accurate and refined profit potential for the property.
The investor used a Kalibri Labs Extended Stay Market Profile report powered by a database that houses more than 33,000 U.S. hotels and transaction level data from over seven billion bookings. The insights contained in this report, which benchmarked the subject property against a selected comp set and the greater market by length-of-stay buckets, allowed the company to underwrite this property in a new way. With this data, they could more accurately project extended stay occupancy by length-of-stay penetration and link this to specific line-item expenses and Housekeeping Key Performance Indicators (KPIs) such as Full Time Equivalents (FTEs) and Minutes per Occupied Room (MPOR).
This investor struggled with a way to justify their analysis until they could confirm the long term stay volume in the market, stating “It was amazing to see that level of detail. Nobody else is doing this – the fact that [Kalibri Labs is] able to provide Extended Stay data for the market and for the competitors is unique and allowed us to put together a realistic and competitive offer.”
The data in the report supported the investor’s upside hypothesis to the tune of +$400k in Net Operating Income, allowing them to confidently increase their offer. Because of this data, the company put forth a competitive bid that was far better informed than the original take and put them in finalist contention for the property.