FDD Item 19 Analysis and the Connection to Franchise Potential

Serious franchise buyers should understand that the FDD Item 19 analysis is one of the most important steps they can take before investing in a franchise. Item 19 is the only place in the FDD where a franchisor can choose to present financial performance representations, sales, revenue, and sometimes costs or profit. When it’s robust, it can help you model the business with real numbers.

But Item 19 is also a controlled disclosure. It’s often vague by design, sliced into quartiles, filtered to exclude newer locations, or anchored to company stores that don’t mirror what a typical franchisee experiences. That’s why it is important to do a detailed FDD Item 19 analysis before investing.

FDD Item 19 Analysis: What to Look for

Item 19 is not a forecast; it’s a curated snapshot. Your job is to figure out what the snapshot doesn’t show by doing a detailed analysis and then asking the right questions to franchisors.

What Metrics You’ll Usually See In Item 19

Most Item 19 sections are built around the safest metric a franchisor can disclose: gross sales. Sometimes you’ll also see transactions, average ticket, or a few cost categories. More rarely, you’ll see profit metrics.

Here’s how to interpret the big ones without getting tricked by the format.

Gross Sales / Gross Revenue

This is the figure most buyers focus on first, and the one that’s easiest to misunderstand. It tells you how much cash moves through the business, but says nothing about what you get to keep.

Why it shows up: It’s simple, verifiable, and sounds impressive.

Useful for: Understanding total demand, seasonality, and how much customers spend in a given model.

Limitations: Doesn’t reflect profitability, margin structure, or operational complexity.

Watch out: Many buyers mentally convert revenue into earnings without modeling actual expenses. Always treat revenue as the starting line.

Averages vs. Medians

It’s easy to gloss over how performance is presented, but the format matters. Averages can distort your understanding, especially in systems with a wide range of outcomes.

Why it shows up: Averages make results look stronger and easier to interpret at a glance.

Useful for: General ballpark sizing if the dataset is uniform and includes all operators.

Limitations: A few strong performers can lift the average well above what most franchisees actually earn.

Watch out: When only mean averages are presented, assume they skew higher than what a typical operator might see. Medians and ranges offer a more grounded picture.

Quartiles and Percentiles

This format can seem like a more honest snapshot of the system. But without context, it’s hard to tell what’s driving the spread. You need to dig deeper to understand the difference between top and bottom performers.

Why it shows up: Quartiles help you benchmark where you’re likely to land. If you can realistically operate like a first- or second-quartile owner in your market, you can use those ranges as a more grounded planning baseline.

Useful for: Seeing how outcomes vary across a system.

Limitations: Doesn’t explain the root causes of performance differences, such as operator skill, market type, staffing, or location quality.

Watch out: A weak bottom quartile might signal a fragile model, slow ramp, or lack of operational support. If the spread is wide, your next step is validation, not assumption.

The Biggest Item 19 “Gotchas” Buyers Miss

Here’s where FDD Item 19 analysis stops being “reading tables” and becomes actual diligence. These patterns appear frequently, and none of them are automatically disqualifying. But each one should trigger more profound questions.

1) Filters That Exclude Newer or “Non-Comparable” Units

You will often see language like: “includes only locations open at least X months or years.” That’s common, and not automatically suspicious—most brands exclude units open less than 12 months because early results are volatile and would predictably pull down systemwide averages.

But it can also remove the phase you most need to understand. The ramp is where the business is messiest, and that is where most first-time owners feel the pressure.

• Why it matters: If you are buying your first location, your cash flow risk is usually concentrated in years one and two. Excluding newer units can make the system look steadier than your early reality likely is.
• What to do: Write down the inclusion rule. Then ask franchisees what year one looked like in plain terms, including sales ramp, staffing challenges, early mistakes, marketing spend, and working capital burn.

2) Company Stores Used as the “Gold Standard”

Company stores can be legitimate examples, but they are not always comparable to franchised units. Corporations often have better sites, stronger managers, more marketing resources, and tighter operational control from day one.

• Why it matters: If corporate units anchor the benchmark, you may be modeling a level of execution and support that is difficult to replicate as a franchisee. That gap can show up fast in labor costs, local marketing results, ramp time, and the simple fact that franchisees also carry royalties and required brand fund fees that company-owned stores don’t.
• What to do: Separate franchisee performance from company performance whenever possible. If you cannot, treat company store numbers as a high-end reference and validate harder with franchisees in markets like yours.

3) Quartiles Without Context

Quartiles look transparent because they show the top, middle, and bottom performers. The problem is that quartiles rarely explain what causes the spread, and the spread is the real story.

• Why it matters: Wide variance usually means the model is sensitive to execution, market selection, labor availability, or site quality. Some strong brands still have variance, so the goal is to understand which factors drive it and which ones you can control.
• What to do: Ask franchisees what variables move the needle most in their market. Listen for repeatable drivers, then compare those drivers to your local conditions and your own operating plan.

4) Revenue That Reads Like Earnings

If a disclosure says “$1.1M average sales,” buyers often think “this is a million dollar business.” It might be, but it can also be a high-revenue, low-margin grind where the owner works hard for a thin take-home.

• Why it matters: Revenue is what comes in. Your success depends on what remains after labor, rent, fees, marketing, and product costs are paid. Without a cost context, big sales numbers can create false confidence.
• What to do: Model expenses to the best of your ability, subtract them from revenue to see what’s left, then stress-test by lowering sales and raising labor and marketing to confirm the economics still hold.

How To Turn Item 19 Into A Real Model

​This is the bridge between reading and decision-making. A good FDD Item 19 analysis ends with a conservative pro forma you’d be willing to bet your savings on.

Step 1: Identify the Data Source

Before you open a spreadsheet, get clear on what you are looking at.

• Is this franchisee-only performance?
• Is it company-only performance?
• Is it blended?

Blended data can still be helpful, but it needs a heavier dose of skepticism. Company stores often have advantages you will not have on day one, and blended reporting makes it harder to tell what a typical franchisee sees.

Step 2: Write Down the Inclusion Rules

Item 19 almost always has filters. Those filters matter as much as the numbers.

Capture these details in your notes:

• Minimum time in operation required to be included.
• Geography limits, if any.
• How many units were excluded and why.
• Total sample size.

Filtering doesn’t automatically make the data wrong. In some cases, it can improve comparability by focusing on stabilized units. But it can also make it easier to miss weaker units, newer units, and the messy realities of the ramp stage. When the sample size is small, results can swing more dramatically, especially if one or two locations are unusually strong or unusually weak.

Step 3: Pick Your Baseline Scenario

You are trying to model the outcome you can reasonably plan around, not the story you hope is true.

A practical approach:

• Use the median if it is provided.
• If the disclosure shows quartiles, use the second quartile, or the lower half, as your baseline until validation shows you should expect better.
• If you only get averages, lower them by a conservative amount, often 10 to 20 percent, until the franchisee validation calls support the headline number.

You can still study the top quartile. Just do not let it become the foundation of your decision.

Step 4: Build a Conservative “Reality Pro Forma”

Keep it simple, but cover the line items that actually decide whether this business pays you or drains you. Your first draft does not need to be perfect. It needs to be honest.

At a minimum, include:

• Royalties and required brand fund contributions.
• COGS and labor, using assumptions that match the model (direct labor may be part of COGS), plus realistic waste, shrinkage, and overtime.
• Rent based on your target corridor, not national averages.
• Insurance, utilities, software, repairs, maintenance.
• Local marketing beyond the minimums, especially in the first year.

Two tips that save people from fantasy math:

• ​Treat owner time as a cost, even if you do not cut yourself a paycheck early.
• ​Assume working capital is part of the startup cost, not something you can “figure out later.”

Step 5: Stress Test it Before Believing It

Once your baseline model looks plausible, test it the way real life tests it. Pick one change at a time, then stack them.

• Sales down 15 percent: This is the “traffic was softer than expected” scenario. It happens because of seasonality, local competition, a slower buildout, or marketing that takes longer to click.
• Labor up 3 percent: This is the “wages in your area are higher than the spreadsheet assumed” scenario. It can also show up as overtime, turnover, and training time.
• Marketing up 1 to 2 percent: This is the “minimum required marketing is not enough to hit the numbers” scenario. Early on, many owners spend more locally just to get the flywheel moving.
• Ramp time extended by six months: This is the “break-even takes longer” scenario. It is common when hiring is slow, the location is decent but not perfect, or the owner is learning the ropes.

Now look at what happens to the two things that decide whether you sleep at night: cash flow and cash reserves.

• Do you still cover operating expenses without skipping bills?
• Do you still cover debt payments if you are financing the buildout or equipment?
• Does your working capital last through the slower ramp, or does it run out right before the business stabilizes?
• If you had to hire one more person than planned, would the model still hold?

If that stress test shows your projected profit quickly turning into a loss, that is valuable information. It does not always mean the franchise is a bad idea. It means the model is sensitive, and sensitive models require one of three things: more working capital, tighter cost control, or more substantial proof from franchisees in markets like yours that the higher numbers are realistic.

Stress Test Example:

Here’s an example of a conservative downside case you can run during FDD Item 19 analysis. Assume Item 19 shows a typical unit at $900,000 in annual gross sales. Stress test it like this:

What you are checking: Under this downside case, do you still cover rent, payroll, royalties, required brand fund fees, and any loan payments without burning through working capital? If cash runs tight, the fix is usually more runway, tighter assumptions, or stronger validation from franchisees in markets like yours.

Franchisee Validation: Where Item 19 Becomes Real

Item 19 usually is not enough by itself. The most useful reality check tends to come from franchisees, especially operators in markets that match yours as closely as possible.

When you validate, skip the broad “does this look right?” question. Ask questions that force real detail:

• “What did your ramp look like months 1 to 12?”
• “Where did you overspend early?”
• “What does labor look like in this market?”
• “How much do you actually spend on local marketing to keep demand steady?”
• “If you could redo one thing before opening, what would it be?”

Then listen for patterns, not one-off stories. The closer the franchisee’s market is to yours, rent, wages, competition, and demographics, the more weight their answers should carry. This is where “take Item 19 with a grain of salt” becomes a real diligence practice.

How Franchise.com Helps With Smarter Item 19 Due Diligence

Franchise.com helps aspiring franchisees with FDD Item 19 analysis by:

• Turning Item 19 into planning assumptions that hold up under conservative modeling.
• Comparing disclosures across brands so one polished table does not sway the whole decision.
• Narrowing options based on fit, including capital, timeline, and involvement level, so you pick a model that works in real operating conditions.

If you want help vetting your short list, Franchise.com can help you move from “this looks promising” to “this makes sense.”

Start your franchise journey today.