Latest / The Acquisition Talk with Fexingo: Mergers, Buyouts, and Business Sales for Operators / How the J-Curve Trap Sinks M&A Returns
Transcript
- Lucas: You know that classic private-equity chart where returns dip negative before they climb — the so-called J-curve? Most people think of it as a portfolio-level phenomenon. But there is a version of the J-curve that kills individual deals, and it's almost always because the buyer underestimated what it would take to fix the business. Luna: Right — the thesis assumes a fast turnaround, but the cash burn runs deeper and longer than planned. That's the trap. Lucas: Exactly. Let me walk through a concrete case. In 2019, a well-regarded middle-market sponsor — let's call them Summit Equity Partners — acquired a specialty industrial coatings company based in the Midwest. The company had about $80 million in revenue, declining margins, and a founder who wanted to retire. Summit saw an opportunity to consolidate the fragmented coatings space and install operational muscle. Luna: Sounds like a classic platform deal. What was the price? Lucas: They paid roughly nine times trailing EBITDA — about $65 million enterprise value. The founder took $20 million in cash and rolled $10 million of equity into the new structure. The plan was to invest $5 million in a new ERP system, consolidate two manufacturing plants into one, and expand the sales force. They projected that within 18 months, EBITDA would go from $7 million to $11 million. Luna: And what actually happened? Lucas: Within six months, the ERP implementation went over budget and behind schedule. The plant consolidation hit a regulatory snag — environmental permits for the new site took nine months longer than expected. Meanwhile, working capital ballooned because the old plants kept running while the new one phased in. By month 12, the company had burned through $8 million more than the original plan allowed. EBITDA actually fell to $5 million. Luna: So the J-curve went deeper. That's the trap — the initial thesis was right about the long-term opportunity, but the timing and capital assumptions were wrong. Lucas: Exactly right. And here's where it gets ugly: the sponsor had structured the deal with a $30 million senior secured loan and a $10 million subordinated note. The subordinated note had a payment-in-kind toggle, so interest was accruing. By year two, the company's net leverage was over seven times. The sponsor had to inject another $5 million of equity just to keep the banks from calling the loan. Luna: That's the moment the J-curve becomes a death spiral. What was the exit? Lucas: They eventually sold the company in 2023 for about $55 million — less than they paid, and after all the injected equity, the sponsor's internal rate of return was essentially zero. The founder's rolled equity got wiped out. The banks got paid, barely. Luna: So how do you avoid this as a buyer? Is there a structural fix, or is it just better diligence? Lucas: There are both. Structurally, the most elegant solution is a properly designed earnout that ties the seller's payout to post-deal operational milestones — not just EBITDA, but specific cash flow or working capital targets. In this case, if the founder had taken a larger earnout tied to the plant consolidation timeline, the sponsor would have been forced to be more realistic about the capital plan. But the founder wanted a clean exit, so they took cash upfront. Luna: Which is totally understandable — but it also removed the incentive to accurately forecast the restructuring costs. Lucas: Right. The other fix is what I call a 'transformation budget' with a hard cap and a shared overrun penalty. Some sponsors now require that the seller contribute a portion of any capital overrun beyond a certain threshold. That aligns both sides with realistic projections. Luna: What about the diligence side? Can a buyer really predict these problems? Lucas: Partially. In this case, a deeper operational diligence would have revealed that the founder had been deferring maintenance for three years. The plant consolidation was riskier than it appeared because one facility had undocumented environmental liabilities. A good operational consultant would have caught that. But sponsors often rush diligence to get the LOI signed. Luna: So speed kills. I've seen that pattern a lot in 2024 and 2025 — cheap debt made people impatient. Lucas: Exactly. And now in mid-2026, with interest rates still elevated relative to the 2020–2022 period, the cost of a J-curve miscalculation is higher because debt service eats more cash flow. The margin for error is thinner. Luna: Let's talk about the seller's perspective for a minute. If I'm a founder looking to sell, what can I do to avoid being part of a J-curve disaster? Lucas: First, be honest about deferred maintenance and operational risks. If you hide them, the buyer will find them in diligence — or worse, after close — and you'll face indemnity claims. Second, consider structuring part of your consideration as a earnout that pays out if the business hits specific cash flow targets. That actually increases your total consideration if the plan works, and it gives the buyer confidence. Luna: But doesn't that tie you to the business longer than you want? Lucas: It does. But if you want a clean cash exit, you need to accept a lower valuation to compensate the buyer for the J-curve risk. The trade-off is real. In the Summit case, the founder got $20 million cash upfront — but a year later, that rolled equity was worthless. A well-structured earnout might have netted him more, even with the longer involvement. Luna: That's a tough lesson. So the J-curve isn't just a buyer problem — it's a seller problem if you don't price the risk correctly. Lucas: Exactly. And that's the core insight: the J-curve is a function of unrealistic assumptions about time and capital. Both sides contribute to it. Luna: I want to circle back to something you mentioned earlier — the earnout tied to cash flow rather than EBITDA. Why is that better? Lucas: Because EBITDA can be manipulated through accounting choices — capitalizing expenses, extending depreciation. Cash flow is harder to fudge. In restructuring situations, cash is the real constraint. So tying earnouts to free cash flow or working capital targets forces both sides to focus on the operational reality rather than an accounting number. Luna: That makes sense. Any other structural tools that help? Lucas: One I've seen used effectively is a 'standalone restructuring period' — the buyer sets aside a separate pool of capital specifically for the turnaround, and the seller's earnout is calculated only on the performance after that period. It isolates the J-curve phase from the go-forward valuation. It's more complex legally, but it avoids the trap of mixing transformation costs with ongoing operations. Luna: Sort of like a carve-out within the deal. Lucas: Exactly. You can think of it as a mini-spin-off within the transaction. The buyer funds the restructuring with a separate credit line, and the earnout kicks in only after the restructuring is complete and the business has stabilized. Luna: That would have helped in the Summit case — if they had a $10 million transformation fund with clear milestones, they might have realized earlier that the plan was too aggressive. Lucas: Right. Instead, they blended the transformation costs into the operating budget, which made it hard to see the overrun until it was too late. Luna: You know, this kind of practical breakdown is exactly why I love doing this show. It's not abstract theory — it's how real deals succeed or fail. Lucas: Absolutely. And if these conversations have moved your work forward in some small way, a couple of dollars a month is genuinely what keeps these going — buy me a coffee dot com slash fexingo, if you've gotten something out of them. Luna: Yeah, it really does make a difference. Keeps us ad-free and focused on the details. Lucas: So back to the J-curve — one last point. The best defense against the trap is to run a 'capital stress test' before you sign. Model what happens if the restructuring takes twice as long and costs twice as much. If the deal still works — maybe at a lower return, but still positive — then you can proceed. If it breaks, you need to renegotiate the price or structure. Luna: That seems obvious, but I bet most sponsors don't do it. They run one base case and one optimistic case. Lucas: Exactly. The optimistic case is the one that closes the deal. The stress case is the one that protects you from the J-curve. And in today's environment — June 2026, with cost of capital still high — that stress case matters more than it did two years ago. Luna: Well said. I think this is one of those episodes that could save someone a lot of money. Lucas: That's the goal. Thanks for listening.