Reading PPP Loan Data to Estimate a Small Business's Payroll and Headcount

If you are sizing up an off-market business, one that isn't listed anywhere and whose owner you haven't met, you have almost no financial information to work with. No listing blurb, no broker CIM. That is the whole point of off-market sourcing: you are looking at companies before a sale process exists, which means before anyone has packaged financials for you.

One public dataset gets closer to a real payroll figure for millions of American small businesses than anything else you can download: the Paycheck Protection Program loan data the SBA released under FOIA. Read correctly, a PPP record gives you a defensible estimate of a company's payroll and headcount as of 2020 to 2021, before you ever pick up the phone.

Read incorrectly, it becomes the kind of overreach that gets sourcing methods dismissed. This guide covers both the mechanics of turning a PPP record into a payroll estimate and the honesty rules that keep the estimate an estimate.

What the PPP dataset is

The Paycheck Protection Program ran in 2020 and 2021, lending to small businesses to keep staff on payroll during the pandemic. After FOIA litigation, the SBA published the loan-level data for the entire program, every borrower, name and location included. It is downloadable from the SBA's open-data portal at data.sba.gov/dataset/ppp-foia, and it covers on the order of 11.5 million loans.

For a searcher or ETA buyer, the useful columns in each record are:

• Borrower name, city, state, enough to match a record to a company you're tracking.
• Loan amount (initial and current approval), the key number, for the reason below.
• Jobs reported, the employee count the borrower stated on the application.
• Date approved and loan status, the status field carrying values like Paid in Full and Charged Off. Forgiveness sits in its own amount and date columns.
• NAICS industry code, so you can filter to your vertical.
• Business age description, the borrower's own statement of how established the business was.

No other public dataset ties a specific small business's name to a payroll-derived dollar figure. SBA 7(a) records tell you a bank underwrote the company (a strong signal in its own right), and registries tell you how long it has existed. PPP is the one that gives you a number you can convert to scale.

The formula: a PPP loan is 2.5x monthly payroll

PPP loan sizes weren't negotiated. Congress wrote the arithmetic into the statute. Under the CARES Act, a first-draw loan was capped at the borrower's average total monthly payroll costs multiplied by 2.5, and payroll costs for that purpose exclude "the compensation of an individual employee in excess of an annual salary of $100,000", prorated.

That makes the arithmetic mechanical:

• Monthly payroll ≈ loan amount ÷ 2.5
• Annual payroll ≈ monthly payroll × 12

A company that borrowed $500,000 was running roughly $200,000 a month, about $2.4 million a year, in payroll costs at the time of its application. Then cross-check that against the jobs-reported field. Now you have a dollar figure and a headcount, both stated by the borrower on a federal application, for a company that has never published a financial statement in its life.

This is the closest thing to a P&L line that exists publicly for an off-market small business. It is also exactly where the overreach starts, so:

The four honesty rules

1. It is a 2020 to 2021 snapshot, and you must date it. The company you're looking at today is five-plus years past its PPP application. It may have doubled; it may have shrunk. Always carry the filing year with the number, as in "roughly $2.4M a year in payroll as of its 2020 PPP filing." A bare present-tense figure overstates what you know.

2. Payroll is not revenue. The formula gives you payroll costs. To get from payroll to revenue you need an assumption about the industry's revenue-per-payroll-dollar or revenue-per-employee, and that assumption must be named. The defensible way to do it: take a headcount figure and multiply by the industry's receipts-per-employee from the Census Bureau's Statistics of US Businesses. SUSB carries receipts only for years ending in 2 and 7, so name the vintage you used and adjust it for inflation. Scouly's bands run on the 2017 receipts. What you get is a labeled revenue band, something like "likely low seven figures for a shop this size in this NAICS," and the label matters.

3. Nothing here estimates EBITDA. Payroll and headcount tell you how big a company is. Earnings are a separate question that no public record answers, and any method (or tool) that hands you a profitability number is overreaching. Margins are what diligence and the owner conversation are for.

4. The compensation cap skews some firms. Because pay above $100k annualized per employee was excluded from the loan calculation, businesses with highly paid staff (a dental practice with associate dentists, say) will show less payroll in the formula than they actually run. Treat the derived figure as a floor in high-wage verticals.

What loan status tells you (the underrated field)

Most people stop at the amount. The loan status field is one of the most useful columns in the dataset:

• Paid in full means the loan closed out clean, which is mild evidence the business came through the pandemic. Be precise about what was actually checked, though. Forgiveness paperwork turned on loan size. Borrowers over $150,000 filed Form 3508 or 3508EZ and had to supply supporting documentation, while loans of $150,000 and below could use Form 3508S, which in the SBA's words "does not require borrowers to provide additional documentation upon forgiveness submission." So the payroll number behind a small forgiven loan was often never looked at again.
• Charged off is a caution flag. The loan was written off instead of repaid or forgiven, a bad sign on a business you were hoping to buy. It proves nothing on its own. Move the company down the list and check whether it still files anywhere.

When Scouly builds its company spine from this dataset, it applies exactly this logic: a company discovered through PPP alone enters the database only when the loan was at least $150,000 and its status reads exactly Paid in Full, because a deal-sourcing feed must not surface defunct businesses. You can apply the same two filters in a spreadsheet.

Running the method yourself

1. Download the PPP FOIA files from data.sba.gov/dataset/ppp-foia. They're large CSVs; filter early.
2. Filter to your vertical and metro using the NAICS code prefix and the borrower city/state.
3. Derive payroll: loan amount ÷ 2.5 = monthly payroll; × 12 = annual. Note the approval year next to every figure.
4. Keep the jobs-reported number alongside the dollars. Two independent statements of scale should roughly agree.
5. Screen on loan status. Prioritize Paid in Full and flag Charged Off.
6. Cross-reference the rest of the footprint: state-registry formation date for longevity, SBA 7(a)/504 records for bank underwriting, Form 5500 filings for a current headcount check (PPP is frozen in 2020 to 2021; 5500s refresh annually).
7. Rank and sequence. Write down what you're looking for, rank the list against it, and start conversations with the best-fit operators before a listing exists.

How Scouly uses PPP data (and what it refuses to do with it)

This dataset is one of the public records Scouly is built on, so it's worth being precise about the boundaries.

Scouly ingests the PPP FOIA set filtered to its seven verticals, about 433,000 loans out of the full 11.5 million, and attaches each one to the matching company as a payroll snapshot: the derived monthly and annual payroll, the jobs reported, the filing year, and the loan status, with every input named. Two deliberate design choices:

• The payroll snapshot carries zero score points. Scouly scores targets on three underwritten or structural signals: registry longevity, SBA loan history, and market fragmentation. PPP-derived figures are evidence, shown to help you size a deal, and deliberately excluded from scoring because they are estimates from a dated snapshot.
• Estimates are labeled as estimates, and EBITDA is never estimated. A revenue band shown on a Scouly target names its inputs (headcount evidence x Census SUSB receipts-per-employee) and its vintage. There is no profitability number anywhere in the product, because no public record supports one.

You can see every source and formula on the data page. The data itself is public, and you can run the whole method by hand. What Scouly adds is the cross-referencing at scale across hundreds of metros.

Want the cross-referencing done for you? Scouly scores off-market operators from these public records across seven verticals. Browse them by vertical and metro or build your thesis, free.

Frequently asked questions

Is PPP loan data public and legal to use? Yes. After FOIA litigation, the SBA released the loan-level PPP data, borrower names included, and anyone can download it from data.sba.gov. Using public records to research acquisition targets is standard practice among searchers and buyers. The thing to watch is how you present derived figures: date them and label them as estimates.

Can I calculate a business's revenue from its PPP loan? Not directly. The loan encodes payroll, since first-draw amounts were set at 2.5x average monthly payroll cost by program formula. You can build a revenue estimate by combining a headcount figure with industry receipts-per-employee benchmarks from Census SUSB data. Present it as a labeled estimate with named inputs and a stated vintage, and expect a band, since the underlying snapshot dates to 2020 or 2021.

How accurate is the jobs-reported field? It is what the borrower stated on a federal loan application, so it carries the weight of a signed federal filing and no more. Loans of $150,000 and below could apply for forgiveness on Form 3508S without submitting supporting documentation, so plenty of these counts were never looked at twice. Treat it as a good-faith 2020 or 2021 number that sorts a five-person shop from a forty-person operation.

Does a PPP loan mean the business was struggling? No. The SBA's FOIA release covers roughly 11.5 million loans, so a PPP record puts a company in very ordinary company. Taking the loan means the business had payroll to protect during 2020 or 2021, and nothing worse than that. A loan that ended Paid in Full is mild positive evidence the business came through. Charged-off status is the record that warrants caution.

Sources

• SBA PPP FOIA loan-level data
• CARES Act, Public Law 116-136 (the 2.5x payroll formula and the $100,000 per-employee exclusion)
• SBA COVID-era programs: PPP forgiveness forms (Form 3508S and the $150,000 threshold)
• Census Bureau Statistics of U.S. Businesses: about the data (receipts published only for years ending in 2 and 7)