“ARGUS Tracks Change, Like a Clock Watches Time” will begin a series outlining how I have utilized ARGUS DCF while financial modeling complex scenarios found in commercial real estate assets. Perhaps this post, or a scenario found in future posts to this series, will bring value to situations encountered that you will find beneficial and can be shared among your clients and colleagues.
Financial modeling property management fees, related to a commercial real estate asset, are often presented as a fixed flat rate per month, per quarter, per year or as an ongoing percentage calculation of gross rental revenues. But what if property management fees begins as a flat fixed rate then changes to a percentage calculation? Tracking changing events that trigger those cost fluctuations can be challenging to model; both timely and accurately.
As an example the following criteria found in a recent scenario was part of a large retail investment property being considered for client’s acquisition. The property had some vacancy and aggressive leasing efforts to achieve 100% occupancy and it was aggressive and ongoing. Argus tracks change like this scenario easily.
The existing property management agreement servicing the property offered a flat monthly fee rate until reaching a pre-determined gross rent revenue threshold. Once the threshold was met, the fees were adjusted to a very specific percentage rate growing to future values as a result of aggressive leasing efforts increasing those revenue thresholds.
Conversely; should the revenues decrease due to tenants exiting the property, causing gross rental revenues to fall below the pre-determined threshold, the fees would then revert back to the lower flat fixed rate. Fluctuations such as these have an ever changing and direct impact on income streams and net operating income values.
Building a financial model, in ARGUS, to track specific changes in these revenue thresholds enabled timely forecasting future market leasing assumptions, of the remaining vacancy, so that future costs may be better understood as revenues increased and decreased.
Using ARGUS for this financial modeling assignment enhanced my ability to accurately and precisely forecast yearly, and per month, increases and decreases in leasing activity and tenant turnover and how those changes would impact future assumptions, cash flow and investment values.
Have you ever encountered a scenario similar to this in which Argus tracks change? Please comment, ask questions and share your experience.
Wishing You Great Success!
Brent W. Sears CCIM SIOR
Image Courtesy of “Reading Time” by winnond FreeDigitalPhotos.net