The past three years of public-market strength have made private equity an easy target. Returns from a small group of mega-cap stocks have driven public indexes sharply higher, giving investors both stronger short-term performance and full liquidity. That combination has widened the gap with private markets and renewed debate about PE’s value proposition.
Long-term investors might wonder why they should stay committed to an asset class that has lagged public markets and offers less flexibility in reallocating capital. The question is not without merit. Measured on a money-weighted basis, PE has only modestly outperformed broad public benchmarks over the past five and ten years.
PE marks also tend to move more slowly than public valuations, especially on the downside. That lag can make the asset class look artificially stable during market reversals, as seen in 2021 and 2022. In economic terms, true volatility likely sits between the smoother reported marks and the sharper swings of listed equities.
Yet, despite the skepticism, the case for PE remains strong, and may even be getting stronger. What’s changing is how value is identified, measured, and shared. This article explains why the playbook for institutional investors and managers is due for an update.
Why PE Still Merits a Central Role in Portfolio Construction
Private equity remains structurally advantaged. It continues to capture growth, deploy capital flexibly, and adapt across market cycles. Several forces are reinforcing that edge.
It’s getting easier to allocate to high-performing managers
Throughout the 2010s, low rates and rising multiples masked differences in operating capability. With those tailwinds gone, results now depend more squarely on how well portfolio companies are run. The value-creation toolkit has also expanded, moving beyond pricing and procurement to include a wider array of functional levers, such as digital transformation, commercial execution, and new product introduction.
As multiple expansion slows, true operating skill is showing through more clearly and tends to carry across a franchise, from deal to deal and fund to fund. That persistence is widening the divide between managers who can consistently create value and those who cannot.
As multiple expansion slows, true operating skill is showing through more clearly and tends to carry across a franchise, from deal to deal and fund to fund.
Between 2007 and 2012, managers with a top-quartile fund had only about a one-in-three chance of repeating that performance and a 60% chance of staying in the top half, making it difficult to distinguish consistent skill from luck. For vintages between 2013 and 2018, those odds rose to roughly 45% and 80%, respectively. (See Exhibit 1.) The increase suggests that genuine operating capability is now more visible, giving allocators a firmer basis for manager selection.
A practical next step for limited partners (LPs) is to build a data-driven selection capability that avoids the bottom quartile funds and favors repeatable operators. From 2003 to 2022, top-quartile PE funds outperformed bottom-quartile peers by roughly 13 percentage points in annual internal rate of return (IRR) (20.7% versus 7.5%), underscoring how much manager selection shapes performance in a diversified PE program.
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Data-enabled manager selection is finally practical
Allocators now have the tools to evaluate managers with a level of precision that was impossible even five years ago. They can analyze deal-level value bridges, tracing realized multiples on invested capital back to their drivers such as growth, margin expansion, multiple change, and deleveraging. These methods separate true operating skill from market lift. Public market equivalent (PME) and direct alpha analyses place PE cash flows on the same timeline as public indices, converting outperformance into clean measures of multiple and annualized excess return. With richer data and model-assisted screens, it’s now possible to identify strong operators and at minimum, systematically avoid the bottom quartile.
With richer data and model-assisted screens, it’s now possible to identify strong operators and at minimum, systematically avoid the bottom quartile.
A handful of factors consistently predict whether a PE firm avoids the bottom quartile. These include clear sector focus and specialization, disciplined fund growth of no more than 25% from one vintage to the next, and a healthy pace and breadth of distributions to paid-in capital rather than reliance on a few big wins. Strong performers also tend to show tighter deal dispersion with fewer tail losses and outliers, and more accurate underwriting, reflected in closer alignment between expected and realized value.
To turn these insights into process, LPs can formalize a few practical tools, such as a value-creation audit that dissects realized deals to separate operating contribution versus market lift. A performance-persistence matrix can track how managers sustain results across vintages, and a selection-uplift model can help companies estimate top-half direct alpha based on operating and process features. Overlaying these with access and pacing maps, spanning co-investments, separately managed accounts (SMAs), and re-ups helps determine how much capital to allocate to repeatable operators while maintaining diversification.
Steady PE allocation preserves diversification and returns potential
Reducing PE exposure now would effectively trade lower-multiple private businesses for higher-multiple public mega-caps. Skipping 2025 and 2026 vintages would further overweight the weaker 2021 and 2022 cohorts, eroding time diversification and creating a vintage hump that concentrates risk in the least attractive entry years.
Maintaining disciplined pacing, re-upping into proven franchises, and using co-investments or separately managed accounts to scale repeatable operators preserves program balance and improves the odds of capturing the next upcycle.
History shows that attempting to time the PE market by skipping vintages rarely works. For example, an investor who avoided the three worst vintages over the past 20 years would generate a gain of just 0.8 percentage points over one who invested steadily. (See Exhibit 2.) Considering how difficult it is to identify the “worst” vintages in advance, that lift is simply too low to justify the risk.
Contrast this performance with the lift that an investor would accrue by deploying capital in the top quartile versus the median over the past 20 years (20.7% compared with 13.7%, annually), and it becomes clear that the focus of allocators should be building long-term relationships with the best, most repeatable operators. Given that capital is relatively scarce right now, this is likely one of the best moments to go build some of those new relationships with general partners (GPs) who can identifiably generate repeat outperformance.
Our experience shows that pacing discipline is about doing enough, consistently, so that time diversification can work. That means codifying pacing bands so they do not oscillate with last quarter’s marks, anchoring underwriting on method, and using liquidity tools judiciously so optics do not prompt selling at a loss.
PE-backed firms may be positioned to capitalize on AI faster
Many smaller companies see opportunities to apply AI across their value chains to boost efficiency and profitability. The investment case is often clear on paper, but execution usually falters. Most lack the internal expertise to pinpoint where AI creates impact, the capital to fund upfront development, and the discipline to sustain change once pilots begin.
Private equity sponsors, by contrast, can approach AI adoption through a portfolio lens. They underwrite both the operating gains and the valuation lift. Every additional $10 million in earnings before EBITDA can translate into roughly $100 million to $120 million in equity value at exit. They also bring fund-level operating partners, standardized playbooks, and access to specialist advisors who can identify and scale AI use cases across multiple portfolio companies.
Capital, expertise, and operating discipline gives PE-backed firms a measurable edge over comparable small and midsize businesses.
That combination of capital, expertise, and operating discipline gives PE-backed firms a measurable edge over comparable small and midsize businesses. They cannot match the investment firepower of global technology giants, but within their segments they can move faster and more consistently. The pattern resembles earlier periods when PE sponsors institutionalized new disciplines such as structured pricing or systematic add-on M&A. Today, leading firms are taking the same approach to AI and embedding it portfolio-wide. As the early returns come in, we expect this trend will accelerate.
What Investors and Managers Should Do Now
The insights we’ve just described offer leaders a practical way to evaluate performance. The goal is the same on both sides of the table: build conviction through evidence, and stay disciplined when conditions change.
For principal investors: The task is to identify managers whose methods are consistent, transparent, and proven to work through different cycles.
- Underwrite the GP’s method, not just marks. Require deal-level value bridges that separate operating improvement (EBITDA growth, margin expansion, multiple change, and deleveraging) from market lift. Tie these to a repeatable operating playbook that travels across sectors and vintages. Compare managers to the right public benchmarks using PME and direct alpha, not pooled IRR. Include attribution by source of value, so selection focuses on operating capability, not timing.
- Use access to back repeatable operators. Re-up into managers who demonstrate operating discipline and team continuity. Use co-investments and SMAs to scale exposure to the strongest deals without crowding risk.
- Engineer liquidity without destroying value. Keep pacing on track by planning for secondaries, continuation vehicles, and net asset value finance as tools of last resort. When they are used, lay out the full cost, conflict protections, and the path for distributions to paid-in capital to avoid being forced into selling at the wrong time.
- Model risk with clarity. Adjust for the smoothing inherent in private-market marks when setting policy limits and asset-liability models. Codify pacing bands so commitment levels do not rise and fall with recent performance, and clearly separate short-term optics from underlying economics in board materials so temporary drawdowns don’t trigger reactive selling.
- Concentrate where conviction is highest. Write larger checks with fewer GPs who demonstrate repeated capability. In exchange, seek not just lower fees but higher access, including advisory seats, operating seminars, or structured insights into deal flow.
Managers now need to show, not just say, how they create value, prove that it’s repeatable, and give LPs confidence that results can endure across cycles.
For GPs: Investor expectations are rising in parallel. Managers now need to show, not just say, how they create value, prove that it’s repeatable, and give LPs confidence that results can endure across cycles.
- Sharpen areas of focus. Many PE firms have already narrowed their sector priorities. But those that push one level deeper into specific subsectors can outperform. Specialized funds deliver returns that are roughly 200 basis points higher than others. LPs increasingly favor knowing more precise exposures in portfolio construction as their risk models become more nuanced.
- Build differentiated value-creation capabilities. Identify the value-creation levers that matter most within each subsector of focus and develop real strength in those areas. Build capability directly or through recurring partnerships. Make these capabilities part of your offer to management teams so the value is visible and credible, and incorporate them into deal sourcing. Target companies that would benefit from these levers rather than limiting the work to diligence and portfolio management.
- Make value creation measurable and auditable. Standardize deal-level value bridges, publish 100-day plans with milestones, and report hit rates. Demonstrating how the playbook holds across sectors and rate environments converts narrative into evidence.
- Open the data room for real diligence. Offer cash-flow information that will allow investors to compare direct alpha with PME. For example, managers that adopt standard cash flow and performance templates and provide replicable analyses such as PME-ready cash flows, entry-year cohorts, and value-creation breakdowns report materially shorter diligence cycles because LPs can validate performance more efficiently. This matters in a market where average fund closings now take about 21 months.
- Be a true partner on access. Offer co-investment opportunities that are reliable, timely, and easy to execute, something nearly 70% of LPs now expect, according to a recent Private Equity International survey. Consistency here builds credibility and strengthens alignment, often paving the way for earlier or larger commitments in future funds. Where possible, design fee and term structures that reward longer holds rather than financial engineering alone.
- Create deeper connection with critical LPs. Help LPs upskill their teams and include them earlier in diligence. Some managers now host semiannual operating workshops or portfolio-level data reviews. Those efforts often lead to larger re-ups as LPs concentrate commitments with managers they trust. Shared insight reinforces partnership and helps both sides defend the asset class in board discussions.
Private equity’s fundamentals are still solid. The dynamics have changed, but the edge now lies in how well investors and managers use what they can measure. Data, discipline, and transparency are making performance easier to see. Those who apply that clarity with consistency will define the next phase of outperformance.
The authors thank Benjamin Entraygues, Tawfik Hammoud, Russ Kellner, Pete Czerepak, Ben Sheridan, Philipp Carlsson-Szlezak, Drew Townsend, Jenna Chodos, Andrew Caminiti, and James Loughridge for their contributions to this article.
