S&P Global analyzed every buyout transaction from 2015 through 2024. Addbacks averaged 29 percent of marketed EBITDA. Nearly a third of the EBITDA number used to price a deal at entry is built on adjustments (cost exclusions, anticipated synergies, forward projections) rather than what the business is actually producing.

The consequence follows with depressing regularity. Ninety-two percent of companies missed their projected EBITDA in year one after close. Eighty-four percent missed in year two. Those shortfalls caused 86 percent of companies to miss their projected leverage targets. The median net debt to EBITDA was 2.3 turns higher than projected in year one. 2.7 turns higher in year two.

Read those numbers again if you sit on a portfolio company board.

This is not a story about bad actors. It is a story about a pattern so consistent it should be the baseline assumption going into every deal.

The addback is not the problem. The pattern is.

Sponsors and management teams are not fabricating numbers. They are doing exactly what deal processes reward: presenting the business at its best plausible case. Every individual addback has a rationale. The synergies are achievable. The cost savings are real in principle. The logic holds on the page.

The problem is that a stack of individually defensible adjustments produces a valuation anchor the actual business then has to grow into. When the timeline slips — and it slips — the leverage that made sense at close becomes a constraint. The board meetings that were supposed to be about executing the value-creation plan become about explaining why EBITDA is 2.3 turns below where the model said it would be.

There is a second problem underneath that one. At close, a company's financial data lives across systems that were never designed to talk to each other. CRM holds pipeline and bookings. ERP holds cost structure and billing. Finance reconciles ARR separately. The board package gets assembled from all of them, manually, every quarter. The addbacks that looked clean in a model become genuinely difficult to track in practice because the underlying data is fragmented.

The adjustments were always optimistic. The systems make it hard to know how optimistic until it is too late to course-correct.

The exit window is longer. The scrutiny is higher.

The Morgan Stanley report adds structural context that matters here. The average holding period for buyout assets is back to approximately 7 years in 2025. Exit volumes peaked at $825 billion in 2021 and have fallen to $375 billion. Secondary buyouts now represent nearly half of all exits. Assets stuck in funds more than 10 years old have grown from $4 billion in 2005 to $350 billion in 2025.

The window between close and exit is longer. The pressure on operating performance is higher. And a secondary buyer's diligence team is at least as rigorous as any strategic acquirer's, because it is usually another PE firm that knows exactly where to look.

The EBITDA shortfall that shows up in year one does not quietly disappear. It compounds. It surfaces again under diligence at exit, at precisely the moment when the cost of finding a gap is measured in multiple compression rather than a remediation sprint.

There is also a structural shift in where returns come from. As equity contributions to deals have risen and debt has moderated, returns have become more dependent on what the business actually does through the hold. Entry multiples averaged 11.5x EV/EBITDA in 2025, up from 6.6x in 2000. Borrowing costs are 8 to 9 percent. At those numbers, financial engineering is not the story. Operations are the story.

That should rearrange the afternoon of anyone still treating the operating view as a reporting exercise.

The gap is a data problem before it is a performance problem

In year one, the revenue that was projected to grow at a certain rate is landing differently because the underlying customer cohorts are behaving differently than the model assumed. ARR that looked clean at diligence contains a segment of products being phased out that was not visible in the headline number. Cash conversion is running behind because the invoicing and collections cycle is longer than the forecast accounted for.

None of these are surprises in retrospect. They are all visible in the data if the data is connected, current, and structured to let the right people ask the right questions early enough to act on the answers.

That is what Chassi builds. Modeled from existing systems of record and delivered in days, Chassi gives CFOs and operating partners a current, integrated view of the metrics that matter through the hold period: ARR by product cohort, revenue quality by customer segment, pipeline conversion, cash flow visibility, and board-ready reporting that holds up to scrutiny. Built at the start of the hold and kept current through it.

The 92 percent miss rate is a pattern. Patterns have causes. The operating view is where those causes become visible before the board meeting where you have to explain them.

Source: Morgan Stanley Counterpoint Global Insights, "Public to Private Equity in the United States: A Long-Term Look," September 1, 2026. S&P Global addback analysis cited therein covers transactions from 2015 through 2024.

Chassi is the operating intelligence platform PE-backed companies use to move toward a successful exit. Request a Demo.