How Clean Books Took a Private Equity Offer From $51M to $97M

A private equity firm offered $51 million for 51% of a three-year-old telehealth company. Fourteen months later the final offer was $97 million for the same stake. The business didn’t change much in between. The numbers did. Here is what happened, and what every owner thinking about selling should take from it.

A great business with books nobody could trust

The company was a virtual behavioral health provider. Its clinicians worked inside six community health centers, and in its second year revenue grew from about $1.8 million to $6.6 million while gross margin climbed from 27% to 47%. On paper, that is exactly the kind of growth a private equity buyer wants to see.

The problem was the paper. Three years of history had been recorded incorrectly. Monthly statements were only partly complete. The same year’s profit changed depending on which report you opened. At the largest partner, invoice-level revenue was off from the accounting system by as much as $100,000 in a single month.

Every buyer runs a quality of earnings (QoE) review. Their accountants:

• Download every bank and credit card statement and tie it to the books.
• Convert the books from cash to accrual if they aren’t already.
• Map every figure in your financials back to the books.
• Ask for the story behind any month where revenue or expenses break from the trend.
• Confirm payroll: every employee, salary, bonus, tax filing and benefit, matched to the payroll records. This is a big job, and knowing the major payroll systems (ADP, Paychex, Gusto, Paylocity and others) makes it much faster.
• Review equity and compensation items such as employee stock ownership plans (ESOPs) and stock options.
• Normalize the results year by year to show what the business really earns.

The QoE is bottom-up diligence in accounting and finance: it starts from every transaction and works up to the totals. At the same time, the buyer’s legal team does top-down diligence, reviewing the company structure, ownership, contracts and benefit plans such as 401(k)s.

That is where we do our best work. In the industry it’s called sell-side transaction advisory: financial due diligence backed by quantitative financial analysis. The job comes down to handling huge amounts of data of every kind: pulling it straight from the seller’s vendors (billing systems, payroll providers, banks and partners), normalizing it in Excel and crunching the numbers until every figure holds up.

When they find problems like the ones above, one of two things happens: the price drops, or the deal dies. Our job was to find and fix every one of those problems before the buyer did.

Step 1: Rebuild the books from the raw data

We didn’t start with the financial statements. We started with the transactions underneath them: every patient encounter, every invoice and every payroll record across all six partners. At one partner alone that was more than 9,000 invoice lines.

From there we restructured all three prior years, converted them from cash to accrual accounting so revenue and expenses landed in the month they were earned and incurred, and normalized where we had to. When we finished, invoice-level revenue at the largest partner matched the accounting system to the dollar. That matters more than anything else in this story. Numbers rebuilt from raw transactions are the ones that survive a QoE. Numbers rebuilt from summaries usually don’t.

Step 2: Give every number one home

Instead of one giant spreadsheet, we built five models, each with a single job:

• KPI data model. Turned raw encounter and invoice data into monthly reporting for each partner: penetration, utilization, productivity and charges by visit.
• Operating cost model. Rebuilt operating costs so margins could be checked line by line.
• Employee cost model. Tracked every employee’s cost over time to validate historical payroll and staffing.
• Advanced pro forma. A 10-year forecast built from the latest year of raw transactions, using assumptions specific to healthcare and telehealth.
• Diligence request tracker. Logged every request from the buyer’s QoE firm so nothing was missed and every answer traced back to the data.

When a buyer asks where a number came from, you want one answer, not three. Separate models with clear jobs make that possible.

Step 3: Prove the forecast with actual results

Every pro forma is a set of assumptions. Buyers discount the ones they can’t verify. So we tested ours against what actually happened.

The model assumed 1.08 medication visits per patient per month. The actual was 1.16. For therapy, the model assumed 2.14 visits and the actual was 2.01. Some assumptions ran a little high, some a little low, and that honesty is exactly what made the whole forecast believable.

We also proved the unit economics. One health center that switched to the company from a national vendor earned more than twice the vendor’s three-year profit in under a year. A single data point like that, backed by real numbers, does more than any sales pitch.

Step 4: Lead the quality of earnings, don’t just survive it

The buyer hired a national healthcare valuation and transaction advisory firm to run the QoE. We worked directly with their teams and reported back to both the owner and the buyer. Because every figure traced back to source data, their questions had fast, documented answers. The buyer accepted the rebuilt numbers.

How the sale process worked

The company hired a healthcare M&A broker to run a sell-side process. Instead of a broad public sale, the broker ran a targeted auction: a short list of buyers it already knew and trusted.

• The teaser. A short, anonymous summary of the business went out to the broker’s relationships to gauge interest without naming the company.
• Indications of interest. Five firms responded with an IOI, a non-binding letter giving a price range and deal terms. Four were private equity firms and one was a family office.
• Management presentations. We met each bidder on Zoom to walk through the pro forma and its assumptions, showing how every number tied back to raw encounter data from the health center partners.
• The preemptive bid. Right after our session, one private equity firm raised its offer by $30 million. The bump reflected more than clean numbers: the buyer saw a company with a real moat and room to expand quickly across the U.S. In deal terms that is a preemptive bid: a price high enough to step ahead of the other bidders and end the auction early.
• LOI and exclusivity. The higher bid came with a letter of intent and an exclusivity period (also called a no-shop), which took the company off the market while the buyer ran confirmatory due diligence, including the QoE.

Exclusivity is where many deals lose value. Once the other bidders are gone, a buyer who finds problems in diligence will often retrade, meaning cut the price it agreed to. Because our numbers already traced back to source data, there was nothing to retrade on.

How the offer moved from $51M to $97M

• Initial offer: $51M for 51%, based on a first look at the business.
• Numbers verified: about $67M, once the rebuilt books held up in diligence.
• Assumptions walked through: $97M. One management presentation matching each pro forma assumption to actual results led to a $30 million preemptive bid.

Over 14 months, the price was never retraded, and the deal went down to the wire: it closed in the final hours before the contract’s midnight deadline. The QoE confirmed roughly $9 million of EBITDA.

Why the buyer paid up: the moat

A moat is whatever makes a business hard to copy or compete with, the way a moat protects a castle. Warren Buffett popularized the term: a company with a wide moat can keep its customers and its margins even when competitors show up.

For a small or mid-sized business, the moat matters even more than for a large one. A buyer paying a multiple of earnings is betting those earnings will last and grow after the deal closes. Without a moat, a competitor with more money can copy the model and take the profits. With one, the buyer is paying for earnings it can protect, and it will pay more for them.

Common moats in smaller companies include:

• Hard-to-win relationships and contracts that took years to build.
• Specialized know-how in a complex field, such as healthcare billing or regulation.
• Proprietary data or processes that prove results competitors can’t.
• Switching costs that make leaving painful for customers.
• A model that scales into new markets without starting over.

This company had several at once: established partnerships with six federally qualified health centers, a care model built around their workflows, and data showing the unit economics worked. Most important, the model could be repeated with health centers across the country. The buyer wasn’t just paying for today’s EBITDA. It was paying for a protected position and a fast path to national expansion, and that is a big part of why it bid $30 million more to lock the deal up.

“The valuation is in the numbers and in the leader. They go hand in hand. When you can validate every one of them, trust with the buyer about your forecast starts building instantly.”

What every seller should know before going to market

Most businesses that go up for sale never sell. According to the Exit Planning Institute, only 20% to 30% of businesses listed for sale actually close a deal. Even a signed letter of intent is no guarantee: deals die in diligence when the numbers don’t hold up, or the buyer retrades the price.

Know which number you’re being valued on. Buyers price a company on a multiple of either the top line (revenue) or the bottom line (usually adjusted EBITDA). Revenue multiples are mostly reserved for fast-growing, recurring-revenue businesses like software. Almost everyone else, including healthcare services, manufacturing, business services and logistics, is valued on EBITDA. That’s why the QoE matters so much: it decides the number the multiple is applied to.

Avoid the mistakes that cost sellers the most:

• Going to market with messy books. Buyers price risk, and unreliable financials are the biggest risk there is.
• Aggressive add-backs. EBITDA adjustments you can’t document get thrown out, and your credibility goes with them.
• Talking to only one buyer. Without competition there is little pressure on price.
• Chasing the headline price. Earnouts, rollover equity, escrow and the working capital target can change what you take home by millions.
• Letting the business slip during the sale. Missing your forecast mid-process is the fastest route to a retrade.

You don’t have to hire a broker to sell. A competitive process was the right strategy for this company. The case study covers every way to find a buyer and what working with a broker involves, and the free white paper adds typical multiples for nine industries and all ten mistakes.

Four lessons for any owner thinking about selling

1. Have an experienced third party in your corner. The owner or CEO is usually the visionary, not the finance person. You need someone who has represented sellers and speaks the same language as the buyer’s deal team.
2. Your books are the product. Unreliable financials are the biggest risk you can hand a buyer, and buyers price risk.
3. Start from transactions, not summaries. If your numbers can’t be traced to source data, assume the buyer’s accountants will find out.
4. Walk the buyer through your assumptions yourself. A forecast backed by actual results is a negotiating asset. Ours added $30 million.

If you are one to three years from a sale, the best time to fix your books is now, long before a buyer’s QoE team ever sees them.

Details are generalized to protect the confidentiality of the company, its partners and the buyer. Figures are rounded.