The private equity exit market in 2025 was supposed to be the year of the great uncorking. Record dry powder. Pent-up demand from three years of constrained deal flow. The conditions were there.
It did not happen the way anyone expected.
GF Data’s annualized 2025 deal volume forecasts showed a 24%+ decline from 2024, the lowest level since 2017. Close rates dropped across the industry. The average time from LOI to close stretched. More deals fell apart in diligence than at any point in the last five years.
And yet. Some companies sold quickly, at premium multiples, with competitive processes that closed in 60 days. Goldman Sachs projects $3.9 trillion in global M&A volume, and the ACG Middle Market Growth Outlook for 2026 confirms strong buyer appetite. The money is there. The willingness to deploy is there. What has changed is selectivity.
The defining dynamic of this market is quality bifurcation. “A” assets trade fast at premium prices. Everything else trades slowly, trades poorly, or does not trade at all.
What quality bifurcation actually means
In a normal market, deal quality exists on a spectrum. Great companies get great multiples. Average companies get average multiples. Below-average companies get below-average multiples, but they still trade.
In a bifurcated market, the spectrum collapses into two categories. The top tier still trades at premium. Everything else falls into a second tier where buyers have leverage, processes stall, and deals die in diligence.
The gap between the two tiers is not gradual. It is a cliff. A company that scores 8 out of 10 on a buyer’s evaluation might trade at 10x to 12x with multiple bidders. A company that scores 6 out of 10 might struggle to get a single firm LOI at 7x. The difference between an 8 and a 6 is not 25% less value. It is the difference between a competitive process and a distressed timeline.
This is why the aggregate statistics are misleading. Looking at average multiples and average deal flow misses the story. The averages are being dragged down by the second tier. The top tier is doing fine.
What makes an “A” asset in this market
I have studied the deals that closed successfully and the ones that stalled or collapsed in the last 18 months. Five characteristics separate the A-assets from the rest.
1. Clean metrics that withstand diligence
A-assets can answer any financial or operational question within 48 hours. Revenue reconciles. Customer metrics are consistent. EBITDA adjustments are documented and defensible. The QoE process confirms what management presented, rather than contradicting it.
This is table stakes, but the number of companies that fail it is staggering. When a buyer’s diligence team finds discrepancies in the first week, the entire process shifts from validation to investigation. Trust erodes. Timelines extend. The investment committee gets cautious.
A mid-market services company I observed went through diligence last year with a 3.2% revenue reconciliation gap. Not fraud. Just sloppy record-keeping between the CRM and the GL. That gap added three weeks to diligence, triggered additional QoE procedures, and contributed to a half-turn reduction in the final multiple. On $10M of EBITDA, that was $5M left on the table.
2. A defensible growth story backed by data
Every company claims strong growth. A-assets prove it with segmented data that shows where growth comes from and why it is sustainable.
This means revenue broken out by new customer acquisition versus existing customer expansion. Cohort analysis showing retention by vintage. Pipeline data showing forward visibility. Geographic or vertical diversification that reduces concentration risk.
The companies that struggle are the ones presenting 15% top-line growth without being able to explain whether that growth is driven by pricing, volume, new logos, expansion, or a single large contract. Buyers discount what they cannot decompose.
3. Fast answers to diligence questions
Speed in diligence is a signal. When the management team responds to data requests in hours rather than weeks, it tells the buyer three things. The team is organized. The data infrastructure is mature. The company can be operated by the next owner without a six-month onboarding process.
The reverse is equally powerful. Slow answers signal manual processes, key person dependencies, and a data environment that will need investment post-close. Every week of delay in diligence increases the probability of deal fatigue, market changes, or competitive moves that weaken the seller’s position.
In the current market, I have seen buyers walk away from deals where diligence took longer than 60 days. Not because they found a fatal issue, but because the slow process eroded their confidence in the management team’s operational capability.
4. Documented processes that reduce key person risk
Buyers are acquiring a business, not a team of individuals. When critical processes live in one person’s head, the buyer sees risk. What happens if the controller leaves? What happens if the VP of Sales takes their relationships to a competitor?
A-assets have documented the processes that matter. Not every SOP for every task. But the financial close process, the customer onboarding workflow, the data reconciliation procedures, the board reporting methodology. These are written down, assigned to roles rather than people, and tested with backup personnel.
This documentation takes real effort to create. It is tedious work that nobody wants to do when the business is running well. But when the buyer’s diligence team asks “what is your bus factor on the monthly close?” the answer matters. “We have documented procedures and two people trained on every critical task” is a fundamentally different answer from “our controller handles it.”
5. A management team that can articulate the plan
The final separator is presentation. A-assets are run by management teams that can clearly explain where the business is going, what the risks are, and what they would do with more capital.
This is not about polished slides. It is about clarity of thought. The CEO can explain the competitive landscape in specific terms. The CFO can walk through the financial model without reading from notes. The operating team can describe the capacity for growth and the investments needed to capture it.
Buyers are buying a future. The management team’s ability to articulate that future, backed by data, is what turns a good company into a premium asset.
Why data readiness is the swing factor
Of those five characteristics, notice how many depend on data. Clean metrics require data infrastructure. The growth story requires segmented data. Fast diligence answers require organized data. Documented processes require data workflows.
Data readiness is increasingly the factor that separates an A-asset from a B-asset. Not because data is glamorous. Because data is the substrate on which everything else depends. A company with great products and terrible data presents poorly in diligence. A company with good products and excellent data presents like a premium asset.
The market is pricing this in. Buyers have been burned by acquisitions where the data turned out to be worse than presented. They are now testing data quality earlier in the process, often before the LOI. Companies that fail early data screening do not make it to the formal diligence phase.
This is a structural shift, not a cyclical one. As PE holds longer and creates more value through operations rather than financial engineering, the operational infrastructure of a company matters more. Data is the backbone of that infrastructure.
What B-assets look like in the current market
The second tier is defined by friction. Not necessarily bad businesses. But businesses that create friction for the buyer at every stage.
Revenue that requires explanation. Not wrong, but complicated. Multiple revenue recognition methodologies across business units. Historical data that does not bridge cleanly due to a system migration. Customer metrics that look different depending on which system you pull from.
A diligence process that drags. Requests that take two weeks instead of two days. Supporting documentation that is scattered across shared drives, spreadsheets, and email attachments. A finance team that is overwhelmed by the diligence workload on top of their normal responsibilities.
Concentration risk without a mitigation story. Top 5 customers representing 40% of revenue is not automatically disqualifying. But top 5 customers at 40% without a clear diversification plan and pipeline data to support it is a problem buyers cannot solve with modeling.
A management team that cannot quantify the opportunity. “There is a big market out there” is not a growth story. “We have identified 1,200 target accounts in three verticals where our win rate is 30% and average deal size is $150K” is a growth story.
Any one of these characteristics might not kill a deal in a strong market. In a bifurcated market, they push you from the A tier to the B tier. And in the B tier, the experience is fundamentally different.
The math on moving from B to A
The cost of being a B-asset is not theoretical. Take a $75M revenue company with $15M adjusted EBITDA.
As an A-asset, you might trade at 9x to 10x in a competitive process. Enterprise value: $135M to $150M.
As a B-asset, you might receive a single term sheet at 7x to 7.5x, with the buyer extracting concessions on earnouts, escrows, and reps and warranties. Enterprise value: $105M to $112.5M.
The gap is $23M to $45M.
The cost of moving from B to A is almost entirely about preparation. Fix the data issues: $75K to $200K in internal time and external help. Document the processes: $25K to $50K in effort. Build the growth story with supporting data: $50K to $100K in analytics work.
Total investment: $150K to $350K. Return: $23M to $45M in preserved or gained enterprise value. This is not a close call.
What to do about it
If your exit is 12 or more months away, you have time. Run a full reverse due diligence on your own data. Fix the reconciliation issues, document the processes, build the segmented analytics. See Reverse Due Diligence: Audit Your Own Data Before Buyers Do for a structured approach to the self-audit.
If your exit is six to twelve months away, prioritize ruthlessly. Revenue reconciliation, customer metrics, and EBITDA adjustment documentation are the three highest-impact areas. See How Long Does It Take to Fix Data Before Diligence? for realistic timelines.
If your exit is imminent, focus on presentation. You may not have time to fix root causes, but you can prepare honest, well-documented responses for every issue a buyer will find. The difference between “we did not know about this” and “we identified this six months ago, the impact is $X, and here is our plan” is the difference between a repriced deal and a managed conversation.
The bifurcation is real. The market rewards preparation and punishes improvisation. The companies that treat data readiness as an exit investment, rather than an afterthought, are the ones trading at premium.
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