Private equity investors are asking harder questions than they were a few years ago. Knowing that a portfolio beat public markets is no longer enough. Boards, CIOs, and investment committees now want to know what produced the result and whether it can be repeated. Was the return earned through manager selection? Strategy allocation? The timing of when capital went to work? Or did the market simply do the heavy lifting?
Those questions matter more now because private markets have moved from a niche allocation to a core holding. The investor here is the allocator — a pension plan, endowment, or fund-of-funds committing across dozens of managers — and the portfolio in question is that book of fund commitments, not the operating companies held inside any single fund. Investors still pay premium fees for access, and in exchange they want a clearer picture of what that access is buying them. The difficulty is that the standard benchmarking tools were never built to answer the question.
Benchmarking tells you what happened, not why
Most private equity benchmarking still measures one fund at a time. Quartile rankings, peer-group comparisons, and pooled return data all provide context, but none of them explain how a portfolio’s decisions combined to produce its overall result.
Most measurement tools stop at the fund level and struggle to explain how a collection of decisions
added up to total portfolio performance.
That gap matters, because a portfolio full of top-quartile funds can still disappoint. Capital may have been committed unevenly across vintage years. The portfolio may have leaned into the wrong strategy at the wrong time. Allocation choices may have shut it out of the market’s strongest-performing segments. Traditional benchmarking confirms the outcome; it rarely explains the drivers behind it.
Construction adds a further wrinkle. The same underlying data can yield materially different benchmark results depending on how the benchmark is built — which raises a fair question for any investor: if the yardstick itself can move, how much weight should the answer carry?
The missing piece: portfolio-level attribution
The problem grows at the portfolio level, where results are shaped by a series of decisions that compound over time. How much capital should be committed? When should it be deployed? Which managers should receive it? How should it be spread across buyout, growth, venture, secondaries, and other strategies? Each choice moves the final number.
Yet most measurement tools stop at the fund level. They can show how an individual manager performed, but they struggle to explain how a collection of decisions added up to total portfolio performance. That limitation used to be manageable, when portfolios were simpler and consisted largely of traditional closed-end funds. Today’s portfolios — customized mandates, separately managed accounts, evergreen structures, co-investments, secondaries, and wider global exposure — carry far more flexibility and far more complexity. As portfolios have grown more sophisticated, so have the questions investors ask of them.
A different way to look at performance
Answering those questions calls for a different method. HarbourVest’s approach isolates the major decisions behind a portfolio’s return. Drawing on a transparent, investable universe, it builds thousands of simulated portfolios and changes one variable at a time — manager selection, strategy allocation, or commitment timing — to estimate how much each decision contributed to the result.
Telling a genuinely strong manager from a lucky one — or a shrewd allocation from a fortunate market — takes a record deep
enough to know how thousands of other funds fared over the same years.
In practice, the analysis is designed to show whether performance came from backing the right managers, investing in the right parts of the market, deploying capital at the right time, or some mix of the three. The framework rests on a proprietary database spanning nearly four decades and covering more than 23,000 funds, 5,000 general partners, and roughly 73,000 holdings. Rather than measure a portfolio against a single benchmark, it measures the portfolio against a broad range of realistic alternatives drawn from that same universe. The output is less a ranking than a diagnostic.
The idea will feel familiar to many investors. Private equity firms have long decomposed a company’s return into its sources of value — revenue growth, margin expansion, leverage, add-on acquisitions, and multiple change. HarbourVest applies the same logic one level up, at the portfolio. The goal is not to confirm that a portfolio performed well, but to understand what made it perform.
From Theory to Practice: Two investors, One Market
The method is easiest to follow through an example. Consider two institutional investors with access to the same universe of private equity opportunities over the same period, one earning 1.52x and the other 1.89x MOIC — multiple of invested capital, or the dollars returned for every dollar put to work. Traditional benchmarking would note that the second portfolio won and stop there. Attribution analysis starts from a shared reference point — the 1.66x a typical portfolio drawn from that same universe would have earned — and asks how each investor’s decisions moved them above or below it.
How to read the charts below
The market baseline (1.66x) is the return a typical portfolio drawn from the same universe would have earned. Each factor below shows how much one decision moved an investor above or below that baseline; the four add up to the gap between the market and the investor’s result.
(1) Manager selection — which private equity firms — the general partners, or GPs — and which of their funds the allocator commits capital to. It measures whether the specific funds chosen beat or lagged the typical fund of their type and is usually the largest single swing.
(2) Vintage timing — when capital is committed. A fund’s vintage is the year it begins investing, and returns vary by vintage; steady pacing spreads the bet across years, while concentrated pacing wagers on timing.
(3) Stage & size — where in the market capital is weighted — large versus mid- versus small-market buyout, and, more broadly, buyout versus growth versus venture.
(4) Geography — how commitments split across regions such as North America, Europe, and Asia, and whether that regional mix helped or hurt versus a typical portfolio.
Investor 1 finished modestly below the market, at 1.52x. A handful of decisions explain the 0.14x shortfall. Weaker manager selection was the largest drag, costing 0.08x; less consistent deployment across vintage years cost a further 0.04x; and a heavy tilt toward large-buyout strategies — where the portfolio underweighted the small- and mid-market segments that led during the period — cost another 0.02x. Geography was broadly neutral. The portfolio committed more to managers that went on to underperform and missed some of the market’s stronger vintages by deploying unevenly. Through a traditional lens, it simply lagged; attribution names the specific choices that put it there.
Investor 2 finished well ahead of the market, at 1.89x, and for reasons the analysis can point to. Stronger manager selection added 0.19x — by far the largest single contributor. More consistent deployment across vintage years added another 0.04x, and a tilt toward the small- and mid-market segments that led during the period added 0.01x, with geography a marginal 0.01x drag. The allocation is the mirror image of Investor 1: where the first portfolio put 96% of its capital into large buyout, Investor 2 committed only about a fifth there and the balance to mid- and small-market funds — the parts of the market that outperformed. The conclusion is not merely that Investor 2 outperformed; it is that identifiable construction decisions, not luck, did the work.
Analysis
Read side by side, the two portfolios show the same lesson from opposite directions: manager selection was the swing factor, worth nearly 0.28x of MOIC between them, while consistent timing and diversification quietly added to or subtracted from the edge.
Strip away the decimals and the story is simple. Both investors fished the same pond, yet one came back with far more. The biggest reason was people: Investor 2 was simply better at picking managers. Handed the same roster of firms out raising funds, it backed the teams that went on to deliver and steered clear of the ones that stumbled — the private-markets version of hiring the right people before the rest of the market catches on. That judgment alone explains most of the gap. Investor 2 also read the opportunity better, leaning into the small- and mid-market funds that led the period while Investor 1 crowded into large buyout, and it committed capital at a steadier pace rather than betting on a couple of vintage years. None of it was luck or a rising tide — both faced the identical market. It came down to a handful of good decisions, and the best of them was knowing which managers to trust.
The standard is changing
Investor expectations are moving. High-level performance reporting no longer satisfies many boards and investment committees; they want evidence for how a return was generated and which decisions helped or hurt. For managers and allocators alike, that means performance has to be explainable, not merely reportable.
Doing that well is harder than it looks. Telling a genuinely strong manager from a lucky one — or a shrewd allocation from a fortunate market — takes a record deep enough to know how thousands of other funds fared over the same years. It is that asset-level detail, accumulated over nearly four decades, that lets HarbourVest segment where a portfolio’s returns actually came from.
As private markets portfolios keep growing in size and complexity, attribution is likely to become a standard part of fiduciary oversight. Investors need to separate returns handed to them by market conditions from returns earned through manager selection, portfolio construction, and capital deployment. In private markets — where capital is committed and locked up for years, and where performance dispersion across managers runs far wider than in public markets — those construction choices carry real weight. Knowing whether a portfolio outperformed will always matter. Understanding why may matter more.
About the Author
Sofia Gertsberg joined HarbourVest in 2016 to lead the firm’s Quantitative Investment Science team. The team’s objectives are to utilize HarbourVest’s proprietary data set to develop quantitative tools and models to enhance fundamentally-driven investment and portfolio construction process across the firm.
Sofia joined the firm from State Street Global Advisors, where she was the global head of fixed income and money market risk leading the investment risk oversight of assets across active, smart beta, and passive strategies for fixed income, cash, and currency portfolios. Her responsibilities included leading a global team of investment risk managers and analysts, designing and implementing investment risk monitoring framework, setting internal risk limits, and conducting risk management due diligence for outside managers. Sofia was also a voting member of SSGA’s Sub-advisor Oversight and Valuation Committees. Prior to that, she was a market risk manager at State Street Global Markets. She also held a director of analytics role at Debt Exchange.
Sofia received a BS in Economics from the University of Latvia in 2000 and an MBA from Boston University in 2003. She speaks fluent Russian and Latvian.
Data and Illustration Notes
As of June 30, 2025. Source: HarbourVest proprietary data set comprised of information aggregated from multiple data sources, including HarbourVest and third-party data providers. Net of underlying management fees and carried interest. Gross of HarbourVest management fees and carried interest. Other expenses borne by investors in the HarbourVest managed funds / accounts may reduce returns. Performance in USD. For illustrative purposes only. Past performance is not a reliable indicator of future results. Not representative of any HarbourVest fund, account, or experience.
HarbourVest Partners, LLC is a registered investment adviser under the Investment Advisers Act of 1940. This material is solely for informational purposes and should not be viewed as a current or past recommendation or an offer to sell or the solicitation to buy securities or adopt any investment strategy. The opinions expressed herein represent the current, good faith views of the author(s) at the time of publication, are not definitive investment advice, and should not be relied upon as such. This material has been developed internally and/or obtained from sources believed to be reliable; however, HarbourVest does not guarantee the accuracy, adequacy or completeness of such information. There is no assurance that any events or projections will occur, and outcomes may be significantly different than the opinions shown here. This information, including any projections concerning financial market performance, is based on current market conditions, which will fluctuate and may be superseded by subsequent market events or for other reasons. The information contained herein must be kept strictly confidential and may not be reproduced or redistributed in any format without the express written approval of HarbourVest.
Nothing herein should be construed as a solicitation, offer, recommendation, representation of suitability, legal advice, tax advice, or endorsement of any security or investment and should not be relied upon by you in evaluating the merits of investing in HarbourVest funds or in any other investment decision.
Market analysis is not representative of any HarbourVest product. This presentation reflects quantitative analysis of the global private equity industry derived from HarbourVest’s proprietary Quant Database, a compilation of private equity partnership and transactional data drawn from internal and external sources. The proprietary Quant Database has been developed internally based on information obtained from sources believed to be reliable; however, HarbourVest does not guarantee the accuracy or completeness of such information. This proprietary database is intended to be representative of the broader private equity market and does not reflect the investment performance of any HarbourVest investment or the experience of any investor in any HarbourVest fund.
Most measurement tools stop at the fund level and struggle to explain how a collection of decisions
Sofia Gertsberg joined HarbourVest in 2016 to lead the firm’s Quantitative Investment Science team. The team’s objectives are to utilize HarbourVest’s proprietary data set to develop quantitative tools and models to enhance fundamentally-driven investment and portfolio construction process across the firm.
