This Q&A was featured in PitchBook’s Q1 2026 U.S. PE Middle Market Report. A PitchBook subscription is required to read the full report.
Despite abundant dry powder, PE dealmaking remains fiercely competitive as capital sits idle while processes grow crowded and valuations remain elevated. This leaves little room for underwriting errors, forcing buyers to abandon traditional diligence tactics in favor of precision execution.
Investment committees increasingly demand a direct link between deal models and defensible, data-backed proof points capable of withstanding diligence, lender scrutiny, and post-close performance realities.
How Are Macro Headwinds Impacting PE Funds and Portfolio Companies?
Record levels of dry powder colliding with near-historic-high aggregate deal prices have pushed entry multiples higher and intensified competition, raising the bar for underwriting rigor and performance results.
Buyers face tighter timelines, less tolerance for adjustments, and greater pressure to quantitatively demonstrate why a target clears the return hurdle. Deal teams are expected to show conviction around run-rate earnings, working-capital needs, and downside resilience, and to do so in a way that is grounded in reliable empirical evidence. That means fewer “plug” adjustments, more sensitivity-tested assumptions grounded in the target’s actual data, and a clearer articulation of the post-close value creation plan with required resources to execute.
The market is effectively forcing operational maturity sooner. While many middle-market companies have real data, their disparate systems often lack the ability to effectively access, analyze, and convert it into decision-grade insights.
As a result, sponsors often inherit a “Day 0” gap: systems may not be fit-for-purpose, key performance indicators (KPIs) may not reconcile cleanly, and the organization may not be prepared for the cadence of board reporting or lender requirements. Closing that gap becomes a value creation workstream rather than a back-office clean-up.
Why Is a “Plain Vanilla” Quality of Earnings Not Enough in Today’s Market?
Traditional quality of earnings (QoE) remains foundational. It focuses on normalizing earnings before interest, taxes, depreciation and amortization (EBITDA) by assessing accounting quality, identifying non-recurring and non-cash items, and evaluating pro forma impacts from structural changes. But in a high-multiple environment, that baseline is table stakes.
Sponsors need more than a “check-the-box” adjusted EBITDA bridge that satisfies lenders and reps-and-warranty underwriting. To show that earnings streams are sustainable, deeper, data-driven evidence is needed. This data-driven QoE can also show that unit economics behave as the model assumes, and the levers in the investment thesis are measurable and executable post-close.
What Does a More Detailed, Data-driven QoE Analysis Look Like in Practice?
It expands the lens from caption-level financial statements to “transaction-level truth,” supported by automated, real-time data application, which we can think of as “QoE 2.0.” Instead of analyzing the business from the penthouse, QoE 2.0 reconstructs historical financial performance from the basement — often using large volumes of order, invoice, stock-keeping unit (SKU), customer and pricing data. That enables a deeper assessment of margins, revenue, product, geography, channel, cohort, or contract type.
Additionally, a data-driven QoE helps validate whether performance is concentrated, volatile, or sensitive to specific variables.
The result is a run-rate EBITDA view that is normalized, explainable, and supported by granular drivers tied directly to the investment thesis and operating model.
How Does QoE 2.0 Improve Underwriting and Support the Investment Thesis?
Transaction-level analytics convert narrative into evidence by surfacing subterranean trends, such as margin compression isolated to certain customers or SKUs, price-volume mix shifts, customer concentration risk, churn masked by aggregate growth, and working-capital drag tied to specific terms.
Just as importantly, these insights identify actionable value creation opportunities, such as pricing harmonization and product rationalization. Channel-mix optimization and procurement, or manufacturing yield improvements, are additional opportunities often supported by QoE 2.0.
When these findings are mapped to the model, sponsors gain tighter sensitivities, clearer KPI definitions, and more confidence that the post-close plan is measurable because the necessary data has already been identified and tested during diligence.
Why Does QoE 2.0 Increasingly Intersect With IT Diligence and Management Reporting?
The best diligence insights are only valuable if the business can reproduce and monitor them post-close. Many diligence analyses prove that the data exists, while also revealing that management does not have a repeatable reporting engine to deliver those metrics in real time.
This raises questions about the scalability of enterprise resource planning and financial systems and the consistency of data definitions. Without reliable reporting, companies may lack the data to support board cadence, covenant compliance, and eventual exit requirements.
Sponsors increasingly need confidence, pre-sign, that the systems roadmap goes beyond merely meeting compliance minimums and can fully support the value creation plan.
Why is “Value Creation Beyond Financial Engineering” Such a Critical Theme Right Now?
When entry valuations are higher and capital structures are more constrained, it becomes harder to manufacture returns through leverage and multiple expansion alone. That places more emphasis on operational alpha: revenue quality, pricing power, margin durability, working-capital discipline, and scalable infrastructure.
Pairing QoE with data analytics and systems readiness helps sponsors establish Day 0 conviction around where value can be created, what must be fixed, and how quickly the business can be professionalized to support growth and eventual exit.
Beyond Earnings, What Other Day 0 Issues Should Sponsors Pressure Test?
In many middle-market deals, earnings normalization is only part of the story. Sponsors should also assess working capital mechanics, tax exposures, audit and close-process maturity, and the broader governance and compliance stack — all of which can directly affect the exit multiple, buyer universe, and sale process timing. Diligence should identify what needs remediating during the hold so the business is exit-ready, not just close-ready.
What Should PE Stakeholders Do Differently To Realize Maximum Value?
PE stakeholders should treat diligence as the first value creation workstream, rather than a precautionary exercise. They should anchor each value driver to transaction-level data tied back to the model and board-ready KPIs. Then, stakeholders should elevate QoE beyond an adjusted EBITDA bridge to a driver-based view of earnings sustainability — pressure-testing concentration, cohort behavior, price-volume-mix, and margin durability under downside scenarios.
In parallel, they should confirm the target can operationalize insights post-close by establishing data definitions, reporting cadence, and a systems roadmap to measure execution from Day 0. Finally, PE stakeholders bake “exit readiness” into underwriting early by identifying tax, close-process, and controls upgrades required to expand the buyer universe and protect exit multiple.
Your Guide Forward
Cherry Bekaert’s Private Equity practice provides integrated advisory, audit and tax services to act as your trusted advisor across the full investment lifecycle, from first look to final exit. Contact our team to learn more about how we can support you.
