Leasing Capacity and Market Checklist Before Acquisition
A sponsor has leasing capacity when a working leasing operation exists on the closing date, the property has a specific reason to win tenants over its competitors, and local vacancy and new construction leave room for the projected absorption. A low purchase price answers a pricing question only. The leasing test asks whether vacant space becomes occupied space inside the modeled period, and the worked example below shows how much income rides on that answer.
Why a low basis answers only half the acquisition question
Leasing capacity is a main acquisition decision factor, and it sits beside the ability to buy at a low base price. The two are separate tests, and a file can pass one while failing the other.
Price benchmarks such as cost per unit against replacement cost, or a stated approach of buying below retail before adding value, measure what the buyer pays. They say nothing about whether vacant space will fill. A property bought below replacement cost with a sponsor unable to lease it still carries vacancy, and the discount does not pay the carrying costs while that vacancy persists.
The decision test is short. Take the price discount out of the file and look at the occupancy projection again. If the discount is the only support for the projection, the leasing case has not been built.
Testing tenant choice at the level of the space being filled
The core property test asks why a renter or tenant would choose this property over the comparable ones. Amenities and floorplans describe the asset. Tenant choice requires a comparison against what the same renter can rent down the street.
For multifamily, analysis starts with the physical property, its unit mix and floorplans, and its amenities, then ties each to the competing properties. The comparison has to run at the level of the unit type the projection depends on. If the plan fills one-bedroom units, a property-wide amenity list does not show that those units beat their direct competition.
Other property types follow the same mechanism with different variables, such as floor plate size or building systems for office. Every projected lease needs an identifiable reason behind it.
“Most importantly, why would a renter choose this property over the comps?”
Reading local market figures inside one boundary
Market diligence for a leasing thesis covers population growth, demographics, vacancy rates and how much construction is underway in the same asset class and area. Each answers a different question. Population growth and demographics describe demand. Vacancy describes space already available. Construction describes space about to arrive.
The figures combine only when they share a boundary. A vacancy rate for a whole metro area and a construction count for one submarket describe different inventories, and setting them side by side produces a precise number that measures nothing consistent.
Slower population growth and an aging population, together with remote work, raise the weight of local conditions in performance. A broad average then says less about one building, and the property-level comparison carries more of the case.
What the leasing operation must already have on the closing date
A leasing operation takes time and money to build, and it is expensive while idle. Both facts matter to an acquisition model. A sponsor with an existing team carries payroll that enough vacant space must absorb. A sponsor that still has to assemble a team starts the lease-up clock with nobody working it, and every month spent hiring is a month removed from the modeled period.
Oversight is the other half of capacity. Leasing meeting time goes furthest when it centers on assets needing attention, such as a vacancy that has sat too long or space leased through a third party. A named owner for each of those cases gives the projection a process behind it.
The closing-date test asks whether a staffed team with a funded budget and a clear reporting line exists when the lease-up period begins. If any piece still has to be built, the model needs a ramp period before the first lease.
“It takes time to build a machine. It’s expensive when it’s idling.”
How a lease changes value: the single-tenant case
Value follows leasing through net operating income. A cap rate is one year of net operating income divided by price, so a lease that adds income adds value at the market cap rate.
Leasing an entire office building to one tenant at $6 million a year on triple net terms lifted its cap-rate valuation to $60 million. Triple net matters here because the tenant carries the property expenses, so most of the rent reaches net operating income.
Large single-tenant leases concentrate the outcome. One signed lease moves value a great deal, and one failure to sign leaves the whole building vacant.
Worked example: equal capital, 80 percent versus 65 percent occupancy on an 80,000 square foot office building
This hypothetical compares two lease-up outcomes on the same capital. Both cases buy an 80,000 square foot building for $12,000,000, pay a 1 percent acquisition fee, and reserve a $1,000,000 leasing budget that is fully spent. Fee: $12,000,000 multiplied by 0.01 equals $120,000. Total capital: $12,000,000 plus $120,000 plus $1,000,000 equals $13,120,000 in each case.
At purchase, 40,000 square feet are occupied, so vacant space is 80,000 minus 40,000, equal to 40,000 square feet. All space rents at $20 per square foot on triple net terms, so rent equals net operating income. In-place income is 40,000 multiplied by $20, equal to $800,000. Going-in yield is $800,000 divided by $12,000,000, multiplied by 100, equal to 6.67 percent.
Base case: the leasing team signs 24,000 square feet within twelve months. Occupied space is 40,000 plus 24,000, equal to 64,000 square feet, and occupancy is 64,000 divided by 80,000, multiplied by 100, equal to 80 percent. Vacancy left is 80,000 minus 64,000, equal to 16,000 square feet. Added income is 24,000 multiplied by $20, equal to $480,000, so total income is $800,000 plus $480,000, equal to $1,280,000. Yield on total capital is $1,280,000 divided by $13,120,000, multiplied by 100, equal to 9.76 percent. Budget per leased square foot is $1,000,000 divided by 24,000, equal to $41.67.
Stressed case: the same team over the same twelve months signs 12,000 square feet on the same $1,000,000 budget. Occupied space is 40,000 plus 12,000, equal to 52,000 square feet, and occupancy is 52,000 divided by 80,000, multiplied by 100, equal to 65 percent. Vacancy left is 80,000 minus 52,000, equal to 28,000 square feet. Added income is 12,000 multiplied by $20, equal to $240,000, so total income is $800,000 plus $240,000, equal to $1,040,000. Yield on total capital is $1,040,000 divided by $13,120,000, multiplied by 100, equal to 7.93 percent. Budget per leased square foot is $1,000,000 divided by 12,000, equal to $83.33.
The income gap between the cases is $1,280,000 minus $1,040,000, equal to $240,000 a year. Price and fees match, and so do the budget and the period, so leasing output alone explains the difference. The base case fills 24,000 divided by 40,000, multiplied by 100, equal to 60 percent of the vacancy, and the stressed case fills 12,000 divided by 40,000, multiplied by 100, equal to 30 percent.
The income figures are annualized run rates at the end of the period. Lease start dates, free rent and collection timing would reduce cash received during the period, and the example leaves them out.
Mistakes that hide the leasing question
Treating a below-replacement-cost price as proof of leasing demand confuses two measures. Price per unit against replacement cost compares what was paid with what building would cost. Absorption depends on tenant demand and on the operator, and the benchmark contains neither.
Funding a leasing budget and assuming a result equates spending with output. The example holds the budget at $1,000,000 in both cases, yet cost per leased square foot doubles from $41.67 to $83.33 when output halves. A budget measures capacity to spend, and the model needs a stated basis for the square footage the spend is expected to produce.
Mixing boundaries in market statistics produces false precision. A vacancy rate measured over one set of buildings cannot be paired with a construction figure from a different submarket or asset class without an explanation of how the two inventories relate.
Describing amenities without a comparison leaves tenant choice unexplained. The question is why a renter picks this property over the comparable ones, and a feature list answers a different question.
Reading annualized income as cash collected overstates the period. Occupied space at the end multiplied by rent gives a run rate. Cash received depends on when leases started and on any free rent, so first-year income falls short of the run rate figure.
Leasing capacity questions for the acquisition file
Which specific spaces carry the occupancy assumption? The answer ties the projection to actual vacant suites or unit types and to no property-wide percentage.
Why would a tenant choose those spaces over the nearest competing ones? The explanation compares the same unit type or suite size with the alternatives open to the same renter.
What boundary defines the vacancy figure? Geography and asset class fix what the number measures.
How much competing construction sits in the same asset class and area? New supply in the same boundary competes for the same tenants as the subject space.
How do population growth and demographics connect to the intended occupants? Broad demand trends matter to the property only where they match the tenants it targets.
Which leasing resources exist on the closing date and which still have to be built? A team that must be assembled adds time to the lease-up process.
Who owns long-standing vacancy and any space leased through a third party? Named responsibility shows where the pipeline gets attention.
What happens to income and yield when the same budget produces half the leased space? A like-for-like stress on output shows the dollar cost of a lease-up shortfall.