Self Storage Investment Analysis: Multi-fund Ramping

I actually found a twitter thread talking about scaling into self storage facilities (entering a deal, exiting, using those proceeds for a new deal, etc...) but there was not a lot of nuance or detail on how you can get from A to B and what kind of deal structure was used for the joint venture. So, I built a model that has all the logic to figure this out based on assumptions for up to 6 deals. (you can use it for just 1 deal as well)

$45.00 USD

The template will be immediately available to download after purchase. This template is included in the joint venture , real estate , and industry-specific bundles (see tabs at the top).

self storage

The model output will show a final summary for the LP (investor side) as well as for the GP (sponsor side). I thought that was an important distinction because depending on if you are operating these facilities or just acting as a passive investor, the final returns and cash requirements will differ.

Diving into the usability of this template, the deal configuration starts off with assumptions about each self storage facility tranche. The following are defined for each of up to 6 deals:

  • Startup Assumptions
    • Start date for construction/acquisition (dropdown selection of months)
    • Length construction lasts if applicable
    • Revenue start month auto populates
    • Total Square Feet
    • % Rentable
    • Rentable square feet auto populates
    • Cost of Land ($ per rentable SQ. FT.)
    • Total Cost of Land auto populates
    • Construction costs (up to 10 slots for each fund can be entered)
    • Existing facility (define square feet), current Net Operating Income, cap rate.
    • Acquisition Cost and Cost per sq. ft. will auto populate
    • Reserve
    • Total Initial Investment populate per all the above
  • Operating Expense Assumptions
    • Define annual cost per square foot
    • Define sales and marketing spend as a percentage of gross revenue
    • Annual % growth of expenses
  • Revenue Assumptions
    • Total Rentable Units
    • Starting Occupancy
    • Occupancy Improvement per Month
    • Stabilized Occupancy
    • Average Revenue per Unit per Month
    • Annual % growth of revenue
  • Exit Assumptions
    • Months Held For
    • Exit Month (auto populates per the above)
    • Exit Cap Rate
    • Exit Value (auto populates)
    • Sale Price per Sq. Ft. (auto populates)
    • Seller/Other fees defined as a %
    • Net Exit Proceeds (auto populates)
    • Months until next facility launches (can be a negative month count if you are running facilities in parallel)
All of the above assumptions can be defined for each fund / deal. The resulting cash requirements will flow to a cash flow waterfall where the user defines sponsor and investor assumptions (GP / LP) for how much equity each will contribution and what the distribution rates will be at each IRR hurdle. That data then is automatically pulled back into a monthly and annual timeline so all the deals can be seen in aggregate on a monthly and annual basis. The resulting cash flow is measured for IRR and DCF Analysis for both the sponsor and investor.

Lots of visualizations were included and one of the coolest ones is a line chart that shows the cumulative effect of initial cash requirement and usage of proceeds to continually do bigger deals or deals with better terms.

By enabling all results to be denominated in terms of what it looks like for a sponsor vs. an investor, the model becomes even more useful to more users.

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