DISCIPLINE IS DISPERSION
Evolving data practices of a value-driven private markets industry
KEY TAKEAWAYS
Fund and portfolio look through are now top of mind
Firms are aspiring for real-time valuations
Manual data processes create a host of integration challenges
There appears to be a disconnect, between the rapidly intensifying data needs of private markets firms and their data management practices.
At Private Equity Wire®, we’ve noted since the start of the year that discipline is the key word for the industry in 2026. From drawn out fundraising cycles to long auction processes, and from value creation and exit readiness to the economics of continuation vehicles – every aspect of the transaction lifecycle is under heavy scrutiny.
Success in this ecosystem belongs to firms that can navigate these processes with a firm grip on strong fundamentals and measurable value drivers. Discipline is already driving dispersion in performance and long-term capital access – a gap that will continue to widen as the industry evolves.
REPORTING NEEDS
Underpinning discipline is data. Speculative decision-making has little room in the private sphere, but informed execution is a perennial challenge in a historically opaque industry. As our data finds, the directions of travel in private markets are intensifying and diversifying data needs in equal measure.
Top of the list when it comes to firms’ most pressing reporting needs is fund and portfolio look-through – cited by more than
half (51%) of the 100+ respondents to the Private Equity Wire® Q1 2026 Reader Survey. Fund-level performance metrics are falling out of fashion – with LPs more closely demanding information on underlying assets and the value drivers therein. Managers themselves could benefit from greater visibility in what is an increasingly volatile macro-economic landscape.
Jason Mirsky, Head of Data Solutions for Securities Services at J.P. Morgan, notes: “Increasingly, we are seeing investors look for advanced solutions – such as Fusion – to aggregate private and public market data into a whole-of-fund view and to gain look-through capabilities for increased transparency and precise analysis. Consistent and clean data is the cornerstone of generating actionable insights.” Fusion is J.P. Morgan’s data management and analytics solution for institutional investors.
Closely tied in with these factors are LP reporting and cashflow forecasting, cited by 49% and 46% of managers respectively as their top data needs. Liquidity is the defining need of the decade, which puts forecasting in sharp focus as a tool – for survival and differentiation alike. And performance attribution and benchmarking is cited by 32% of firms as a top priority.
Real-time portfolio valuations are also gaining attention, with over 40% of firms identifying them as a significant need. With the democratisation of private markets down the wealth chain and increasingly into retail rampant, demand for more frequent and granular valuations will emerge – as the public and private investor experience converge.
APPROACHES TO DATA
The wave of modernisation and maturity is in full force, but the supporting mechanics appear to be lagging. A remarkable 57% of firms place spreadsheets and manual tracking in their top-three data sources – overall placing only second on the list behind internal portfolio management systems (68%). Other notable sources are private market data providers (54%), GP reports (41%) and custodians/fund admins (32%).
Figure 1. Most critical reporting needs for private markets firms
No surprises that manual data entry and processes are also firmly in the top-three challenges when it comes to data management – cited by 54% of managers. This list, however, is dominated by challenges around data quality and inconsistency, as noted by 73% of managers, while 35% also say a lack of common identifiers is a top barrier. Other challenges revolve around the aggregation of private and public market data (32%) and limited data integration capabilities (30%).
Many firms lag in their data management because the complexity and fragmentation of private markets data makes it difficult to establish a single source of truth or gain holistic fund view. Multiple sources, bespoke reporting formats, and evolving investor demands often lead to manual entry and reconciliation, resulting in errors and inefficiencies. The lack of common identifiers and limited integration capabilities further compound the problem, making it hard to aggregate and analyse data across funds, portfolios, and asset classes.
“As a global custodian, J.P. Morgan has access to a breadth of private and public assets data,” says Mirsky. “We have firsthand experience aggregating data across asset classes, and we’re able to use this expertise to solve the kinds of problems highlighted here, with platforms like Fusion.”
Data quality and inconsistency
Manual data entry and reconciliation processes
Lack of common identifiers across systems
Difficulty aggregating private and public asset data
Limited data integration capabilities
Outdated or legacy systems
Slow query performance or data latency
Analyst note: Respondents were asked to pick their top three
Firms can leverage linked data models, with a built-in semantic layer and AI/ML driven entity ID resolution, to simplify access to data across various sources, providing a consistent and business-friendly terminology for analysing data. Built by J.P. Morgan’s data experts, Fusion’s data model is inherently scalable and designed to ease the operational workflow of navigating and discovering data in your investment universe.
A semantic model and knowledge graph that unifies public and private assets, according to Mirsky, facilitates advanced natural language Q&A across invested and research universes. He explains that with common identifiers and a data structure that captures the complex relationship between financial data elements, investors gain a more nuanced and detailed understanding of their data, unlocking whole of fund exposure and look-through analytics.
“We hear from clients that possess great volumes of data, but struggle to aggregate and extract value from it,” says Mirsky. “Fusion provides consistent and normalised data, alongside a full suite of data management capabilities, to support firms looking to make the most of their private and public data.”
Transparency and standardisation are hallmarks of mature industries, and while these have traditionally run at odds with the bespoke, proprietary edge of private markets offerings, they now manifest as key differentiators in the era of discipline.
Figure 2. Primary data sources for private markets firms