The 2024 Stanford GSB Search Fund Study tracked 681 search funds formed in the United States and Canada since 1984 and found an aggregate pre-tax internal rate of return of 35.1% and a return on investment of 4.5x. Those are the outputs. The financial model is how you build a deal that produces them.
Most searchers confuse two separate things: the operating model and the financial model. One shows you how the business makes money. The other shows you how the deal makes money. They connect, but they are not the same. Getting them confused kills your credibility with investors and kills your ability to price a deal correctly.
This is the framework every searcher needs before they make an offer.
Two models. One decision.
The operating model focuses entirely on the business. Revenue drivers, margins, customer retention, cost structure, and working capital behavior. It answers one question: how does this company generate cash? Get this wrong and every number downstream is fiction.
The financial model takes the operating model's outputs and layers in the deal terms. Entry price, debt, seller note, equity required, projected hold period, exit multiple. Its outputs are the numbers your investors actually care about: IRR and MOIC.
IRR is the time-weighted return. It tells investors how efficiently their capital compounded over the hold period. MOIC is the absolute return. 3.0x MOIC means they tripled their money, regardless of timing. Both matter to search fund investors, and they must be read together.
A deal with a 30%+ IRR and only a 2.0x MOIC usually means the hold period was too short or the initial equity was too small. A 5.0x MOIC at 15% IRR means you held too long or over-levered at entry. Your model needs to show both moving in the right direction simultaneously.
Building the operating model first
Start with three to five years of historical financials. Revenue by line item, cost of goods sold, gross margin, operating expenses, and EBITDA. You are not copying these numbers. You are normalizing them.
Owner compensation above market rate gets added back. One-time legal expenses get added back. Personal vehicles on the company books get added back. This is the EBITDA add-back process, and it determines the number you will pay a multiple on. Every dollar of legitimate add-back that disappears from the model costs you real money at closing.
Once the historical baseline is clean, project forward five years. Build three scenarios: base case, upside, and downside. Do not construct a downside that flatters the deal. If the business loses its largest customer tomorrow, what does revenue do? Model it. Investors have seen a thousand optimistic projections. They look for the downside first. Show them you already looked.
Capital structure in a search fund acquisition
In a typical lower-middle-market search fund deal, capital comes from four sources. Each has a different claim on the business's cash flow.
Senior lenders. SBA 7(a) loans or conventional bank debt. First priority on debt service. Lowest cost of capital. Typical leverage at closing runs 4-5x EBITDA. The debt service coverage ratio (EBITDA divided by annual debt service) must stay above 1.25x in your base case projections or the lender will not close.
Seller note. Usually 10-20% of purchase price. Second lien behind senior debt. A seller note signals the seller's confidence that the business can service the debt. It also compresses the equity required from outside investors.
Search fund investors. Preferred equity, typically with a 6-8% preferred return that accrues before common equity participates in profits. These investors funded your search, underwrote your due diligence, and now hold preferred shares. They receive their preferred return before you see a dollar of carry.
The searcher-operator. Common equity and options. Last in line for distributions, but highest upside if the deal performs. The operator's equity is typically in the 25-30% range at closing, with vesting tied to tenure as CEO.
This is the waterfall. Your financial model must show how cash moves through each layer: debt service first, preferred return second, then common equity. Returns to each party get calculated after the layer above is satisfied. Most searchers build the returns table before they build the waterfall. That is backward. The waterfall creates the returns.
What investors need to see from the returns model
According to the Search Fund Market financial modeling guide, traditional search fund investors target 25-35% net IRR and 3.0-5.0x MOIC over a five-to-seven year hold period. Your base case should reach the low end of those ranges. Your downside case must preserve capital — 1.0x MOIC minimum, meaning investors recover what they put in.
These are not soft targets. They are benchmarks investors use to compare your deal against every other search fund deal they have seen. If your base case shows 22% IRR, the conversation becomes very difficult.
The 3x3 returns matrix
Before you present to investors, build a 3x3 matrix. Three revenue scenarios on one axis: base, upside, downside. Three exit multiples on the other: at your entry multiple, 0.5x higher, and 0.5x lower. Nine outcomes. This brackets the range of what is plausible.
Present IRR and MOIC for each cell. Investors read this matrix in 30 seconds. If the bottom-left corner (downside revenue, lower exit multiple) shows 0.7x MOIC, expect hard questions about capital preservation. The model itself is flagging a problem with your deal structure.
This matrix enforces intellectual honesty. A deal that looks compelling under one revenue assumption can look fragile under another. Better to find that out in Excel before you sign a letter of intent than after you have spent 90 days in diligence.
The exit multiple assumption deserves particular attention. Paying 5.5x EBITDA at entry and assuming a 6.5x exit is not analysis. It is optimism dressed as math. Build your base case with a flat multiple: exit at what you paid. Multiple expansion is upside. It is not the plan.
Entry valuation: the biggest lever
The entry multiple is the most powerful variable in the financial model. Paying 5.0x EBITDA versus 6.0x on a $1M EBITDA business is a $1M difference in purchase price. That million either comes out of additional equity, longer debt paydown, or reduced returns. There is no version where it disappears.
Most lower-middle-market businesses transact at 3.5-6.0x EBITDA, with the range driven by sector, margin quality, customer concentration, and growth rate. Search funds compete today in a market with more buyers than five years ago. Disciplined entry pricing is not optional. Overpaying on entry is the most frequent modeling failure, and it gets rationalized away before closing.
Build a sensitivity table showing returns at 0.5x and 1.0x increments above and below your target entry multiple. If the deal only works at 5.0x and breaks at 5.5x, you need that information before the negotiation, not during it.
Where searchers get the model wrong
Four failure points appear in most flawed models.
Seller note service ignored. A seller note at 6% requires cash service each year. If Year 1 EBITDA barely covers senior debt service, you have a problem. The model needs to show combined coverage: senior debt plus seller note, both staying above 1.0x in every scenario including downside.
Working capital blind spot. When you buy a business with $300K in accounts receivable, you are also inheriting $300K in liabilities unless you negotiate a working capital peg. Get the peg wrong and you fund the gap out of your own equity at closing. The working capital peg mechanics belong in the model before you make an offer, not after.
Linear revenue assumptions. Small business revenue is not linear. A single contract renewal, a key salesperson departure, or a seasonal swing can move a year by 15-20%. Build monthly projections for Year 1 and Year 2. Annual projections in Year 1 hide the cash flow crunch that kills new operators.
Deferred capital expenditure. The prior owner ran the business to sell it. Equipment maintenance, IT systems, and facility upgrades often get deferred in the two years before sale. Build explicit capex assumptions for Years 1-3. Your free cash flow is net of what the business actually requires, not gross EBITDA.
What the Stanford data tells experienced operators
The 35.1% aggregate IRR across 681 search funds includes funds that never acquired a business, funds still operating, and funds that exited. For exited search funds specifically, the 2024 study found an IRR of 42.9%. That number is real. It is also the product of hundreds of investor return models that held up under diligence: models that captured the waterfall correctly and showed a credible path to 25%+ IRR in the base case.
The model is the first proof you understand the deal. Investors have met searchers who could not explain their own waterfall. They do not fund those searchers.
Build the model before you need it. A searcher who has run three acquisitions through the financial model before making an offer, without the pressure of a deadline, has sharper judgment on price, structure, and risk than one building it at 11pm before an investor meeting.
The financial model is not a guarantee. It is a structured test of your assumptions. Run it until it breaks. Find the variable that kills the deal. Then determine whether you can control that variable as the operator. If you can, buy the business. If you cannot, move on.
Most bad acquisitions were not bad businesses. They were bad models for the price that was paid.
Frequently Asked Questions
What is the difference between an operating model and a financial model in a search fund deal?
The operating model focuses on the business itself: revenue drivers, margins, customer retention, cost structure, and working capital. The financial model takes those outputs and layers in deal terms such as entry price, debt, seller note, equity required, and projected hold period. One shows how the business makes money. The other shows how the deal makes money.
What return targets do search fund investors use to evaluate a deal?
Traditional search fund investors target 25 to 35% net IRR and 3.0 to 5.0x return on investment over a five to seven year hold period. The base case should reach the low end of those ranges. The downside case must preserve capital at a minimum of 1.0x, meaning investors recover what they put in.
What is the waterfall, and why does it matter for returns?
The waterfall is the priority order in which cash flows to each capital provider at exit: senior debt first, then preferred return to investors, then investor capital recovery, then common equity including the operator's carry. Most searchers build the returns table before they build the waterfall, which is backward. The waterfall creates the returns, and modeling it wrong produces projections that do not hold up with investors.
What are the most common financial modeling mistakes search fund operators make?
Four failure points appear in most flawed models: ignoring seller note debt service in coverage calculations, missing the working capital peg mechanics before making an offer, using linear annual revenue assumptions that hide first-year cash flow problems, and understating capital expenditure requirements that the prior owner deferred before sale. Each one can make free cash flow projections materially wrong.
