As investor scrutiny intensifies, inconsistent data limits the ability to analyse and compare performance. We spoke to Chris Sparenberg about how S&P Global is addressing this challenge in collaboration with Mercer and Cambridge Associates
Private market firms are stuck in a challenging holding pattern. While headline deal values have shown signs of a welcome uptick, the realisation environment remains stubbornly sluggish.
According to McKinsey, portfolio company hold periods have stretched to an average of 6.6 years.
As a result, institutional allocators are locked in mature funds far longer than their liquidity models anticipated.
Unsurprisingly, LPs are no longer content to wait for the eventual exit to audit a manager’s underwriting thesis.
Instead, the scrutiny has moved inside the house. LPs are applying the same quantitative, continuous analytical pressure to their alternative allocations that they traditionally reserved for liquid public equities, demanding full visibility into the operational machinery of value creation.
“The context of the market that we’re in today is more than just asset valuations,” explains Chris Sparenberg, head of private market strategy at S&P Global Market Intelligence.
“Cost of capital is higher than when a lot of these investments were underwritten. Exits, therefore, are just tougher generally. Once the cost of capital increased, scrutiny starts to get a lot deeper.”
This macroeconomic shift has fundamentally transformed investor relations.
Armed with longer tenures in the asset class, more sophisticated institutional allocators are becoming highly direct and granular in the metrics they demand between official reporting cycles, forcing finance teams to constantly defend fund trajectories.
Yet, for most GP houses, the ultimate bottleneck is rarely a lack of information; private market firms have data in abundance.
The real breakdown is a structural data integrity problem that makes true cross-portfolio comparison nearly impossible.
The normalisation trap
For GPs, the operational friction tends to begin at the very moment data leaves the portfolio company. Even standard, fundamental financial metrics resist uniform aggregation when managed across dozens of disparate underlying businesses.
Sparenberg highlights top-line revenue reporting as a frequent point of failure. Requesting a basic revenue update from four different deal teams or portfolio CFOs routinely yields four completely different accounting methodologies: adjusted revenue, forecast revenue, last-12-month (LTM) performance, or year-to-date run rates.
“Yes, we answered the revenue question,” Sparenberg notes, “but no, we didn’t give you anything you can use uniformly across portfolio companies.”
This lack of standardisation is becoming a significant liability. LPs are increasingly migrating away from evaluating individual funds in isolation; instead, they are looking to model macro-exposure, operational risk and sector performance across their entire private markets programme.
When a GP’s underlying data is non-standardised, it breaks the LP’s data models.
Solving this requires immense manual effort. Portfolio data remains stubbornly siloed across fragmented internal legacy systems and varying third-party administrator portals.
Reconciling these mismatched definitions into a defensible single source of truth creates an acute operational burden, one that peaks precisely during fundraising or mid-cycle investor reviews when response speed is paramount.
“That’s a challenge all managers are dealing with and it’s something we hear about often: no investor is the same,” Sparenberg says.
“Depending on your strategy, you will have interactions with different LPs who have different desires and different requirements. But then if you’re a multi-strategy manager, that’s a lot of different people to have to respond to.”
There’s a growing sense across the market that we’re approaching standardisation, or at least an acceptance that we need standardisation
Chris Sparenberg, S&P Global Market Intelligence
Engineering a common language
To bypass this manual reconciliation trap, forward-thinking CFOs are shifting their focus toward performance architecture design.
Rather than trying to patch reporting gaps retroactively, managers are building an automated, centralised data infrastructure that enforces data standardisation right at the point of ingestion.
This means embedding uniform definitions for EBITDA, revenue and cash flow directly into portfolio company reporting templates, neutralising the structural lag between forecast and LTM structures.
This structural alignment requires connecting fund-level accounting directly to underlying portfolio company metrics within a single system.
In doing so, finance teams can dismantle the traditional barriers between external administrators, internal finance desks, and deal teams, establishing a reliable, automated flow of data across the entire firm.
Once this internal clarity is secured, managers can look outward, using broader market datasets to benchmark their performance against vintages and sector peers in real-time.
However, the path to standardisation depends heavily on the specific asset class in question.
“Private equity buyouts are maybe the most direct,” Sparenberg observes. “You have standard financial performance information, a pretty well-agreed set of metrics that really matter when you’re charting an investment manager’s performance.”
He adds: “Elsewhere, as private credit continues to evolve, every time you feel like you’re close to maybe finding something that’s universally agreed, another strategy, another deviation from a core strategy might emerge and that might make the picture for metrics a little more complicated.”
Institutionalising the back office
As a result, the pressure to resolve this comparability deficit is driving an industry-wide push toward institutional standardisation. Data providers, consultants, and allocators are actively collaborating to build a unified framework for private market metrics.
“There’s a growing sense across the market that we’re approaching standardisation, or at least an acceptance that we need standardisation,” says Sparenberg.
The market landscape is already shifting to support this. The recent performance analytics launched by S&P Global in collaboration with Cambridge Associates and Mercer underscores a broader momentum toward institutional-grade benchmarking and data transparency.
“As part of the S&P Global, Cambridge Associates, Mercer Performance Analytics initiative, we developed an entirely new taxonomy for private markets — one that’s better reflective of that evolution of private capital,” says Sparenberg.
“It’s building a tiered hierarchy that helps give context for performance, allows managers to better select appropriate peer cohorts, and gives LPs a better sense of their true exposure, drivers of return and overall performance.”
Crucially, this systemic overhaul does not mean forcing GPs to rebuild their reporting habits from scratch. Instead, the focus is on utilising technology to translate existing data streams into a normalised structure. Significantly, GP consent is sought before including their (anonymised) data in the new performance analytics.
“We’re not forcing a change in reporting on managers at all,” Sparenberg emphasises. “We’re taking the data as it’s provided and then we’re enriching it further by applying our taxonomy and doing some of the normalisation. The worst thing we could do is create yet another template and circulate that across the industry. So we have a heavy emphasis on meeting managers where they are and taking what they’re providing.”
Ultimately, the era of passive, fixed-interval investor reporting is giving way to a model of continuous performance interrogation.
The mandate is clear for operational leaders: investor relations can no longer be decoupled from data engineering.
The firms that successfully bridge the data comparability gap will drastically cut their back-office overhead and secure a distinct competitive advantage in a crowded fundraising market.
Chris Sparenberg is head of private market strategy at S&P Global Market Intelligence.
To find out more information about the S&P Global, Cambridge Associates, Mercer Performance Analytics, please visit: spglobal.com/PrivateMarketsPerformanceAnalytics
Watch The Drawdown’s recent interview with Chris Sparenberg here.
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