The operator sees a capital transaction. The buyer sees a 20-year credit decision. Here's how we think about it.
When an operator calls a sale-leaseback buyer, they're typically thinking about capital: how much can they unlock, what does the rent look like, how fast can they close. Those are the right questions from where they sit.
From where I sit, the evaluation is different. I'm not underwriting a real estate transaction. I'm underwriting a 20-year credit decision — a judgment about whether this business will be able to sustain a fixed rent obligation for two decades, across economic cycles, competitive shifts, and operational challenges that neither the operator nor I can predict on day one.
Understanding how a buyer thinks about that decision makes the conversation more productive for both sides.
The credit stack: what we're actually reading
A sale-leaseback underwriting analysis starts with what I'd call the credit stack — the layered set of factors that determine whether this operator, in this business, at this location, can sustain rent for 20 years.
Layer 1: Business model durability
Before I look at a single number, I want to understand whether the underlying business model is durable. This isn't a judgment about the operator — it's a judgment about the category, the brand, and the format.
A multi-unit QSR operator in a system with 30 years of franchise history, strong unit economics, and expanding franchisee ranks is a different credit story than an operator in a system with recent leadership turnover, declining unit count, and active franchisee litigation. Same coverage ratio, different business model durability.
I've spent more than a decade in net lease underwriting across more than $6 billion in transactions. The deals that have created problems — both in my prior work and in the broader market — are disproportionately concentrated in categories where the business model faced structural pressure that wasn't visible in year-one unit economics.
Layer 2: Unit-level EBITDA and coverage
This is the number I spend the most time on: the rent coverage ratio. EBITDA at the unit level, divided by the proposed annual rent. Our default floor is 2x. Below that, the rent obligation becomes a fragile one — dependent on the business performing at or near its current level with no room for error.
What I'm looking for in the coverage analysis:
- Is the EBITDA number clean? Are there owner add-backs that inflate it? Are there below-market owner salaries that need to be adjusted?
- What's the three-year trend? A business at 2.3x coverage today that ran 2.8x three years ago is different from one that ran 1.9x three years ago.
- What does the seasonality look like? A business whose EBITDA is heavily weighted to Q4 has a different risk profile than one with consistent monthly performance.
Layer 3: Lease structure fit
The coverage ratio has to be evaluated against the proposed lease structure. A 6.5% cap rate on a $3M property produces $195,000 in annual rent. Does the business produce $390,000 in unit-level EBITDA (2x coverage) or $292,500 (1.5x coverage, the QSR floor)?
If the coverage doesn't work at market pricing, I can adjust: lower the purchase price (which raises the implied yield on our investment), structure a shorter primary term, or require additional credit support. But coverage that doesn't close without significant structural adjustment is a sign that the deal doesn't fit the operator's current situation.
Layer 4: Real estate as secondary collateral
The real estate is important — it's what we own — but it's secondary to the credit analysis, not primary. A building that appraises at a 20% premium to the purchase price provides a comfortable margin. A building that appraises at 5% below the purchase price isn't a deal-killer if the operator credit is strong.
What matters more than the appraised value is the real estate's fungibility: if this tenant vacates in year 10, what does the re-leasing or disposition look like? A well-located QSR pad on a hard corner in a growing market is easier to re-lease or sell than a highly specialized facility in a secondary market with limited alternative-use demand.
Layer 5: Operator financial transparency
This one doesn't appear on a spreadsheet, but it shapes every part of the analysis that does.
An operator who provides complete, organized financial statements, explains variance periods clearly, and answers questions with specificity is telling me something important: they understand their own business. That's not a soft assessment — it's a signal about whether the business will be managed well over the next 20 years.
The operators who struggle to produce three years of unit-level P&Ls, or who can't explain a year when EBITDA dropped 18%, create uncertainty that has to be priced. Sometimes it's priced in the cap rate. Sometimes the uncertainty is large enough that we pass.
How the analysis produces a number
When the credit stack checks out, the analysis produces two outputs: the purchase price and the rent structure.
Purchase price = NOI / cap rate
Where NOI (net operating income) in a sale-leaseback context is the proposed annual rent, and the cap rate is the return we require given the credit analysis. For an operator with strong coverage, durable business model, and quality real estate, our cap rate is lower — meaning we pay more for the same rent dollar. For an operator with thinner coverage or more credit uncertainty, our cap rate is higher.
The cap rate is the underwriting output, not an input. It reflects the totality of the credit analysis.
Rent = required NOI for deal to work
The rent has to be sustainable for the operator — above floor, with reasonable cushion — and sufficient to produce an acceptable return on our purchase price. When the coverage math works cleanly, this closes itself. When it doesn't, we have a conversation about which variable to adjust: purchase price, rent, term structure, or credit support.
What makes underwriting move fast
The deals that close in 30 days are the ones where the operator package is complete on day one. Three years of unit-level P&L. Clean tax returns. Property addresses and building age. A clear explanation of any outlier periods.
The deals that take 60 days are the ones where documents arrive piecemeal, questions go unanswered for days, or the financial picture at the individual unit level requires significant reconstruction from summary-level data.
From a buyer's perspective, a prepared operator is a better credit signal than an unprepared one. Not because the documents themselves convey creditworthiness — but because an operator who can produce their financial picture quickly and clearly is an operator who knows their business. That's the operator you want as a tenant for 20 years.
What we're not trying to do
I'll close with this, because it shapes how I approach every underwriting conversation: we're not trying to find reasons to say no. Every deal we pass on is a deal we spent time analyzing. Our time has a cost. Passing on a deal is a cost for us, not a victory.
What we're trying to do is determine, as quickly and accurately as possible, whether this is a 20-year relationship we can build confidently. The operators who help us do that — with organized documentation, honest self-assessment, and clear answers to hard questions — make the process better for both sides.
The ones who make it harder — with missing documents, optimistic numbers that don't reconcile to tax returns, or resistance to explaining variance periods — are telling us something about how the relationship would look over time. That's information we act on.
Want to understand how your business looks from the underwriting side before you're formally in a process? That's a 20-minute conversation that's useful whether or not we proceed. We can tell you what we'd look at, how the coverage math looks on your numbers, and what, if anything, would need to change.