To improve the manager selection process, investors need granular asset-level data—but struggle to access it in a standardized, consistent way
LPs are increasingly seeking asset-level data that can be broken down by sector, geography, strategy, investment professional, entry valuation, and exit multiples. This helps them understand:
• Which sectors and geographies have contributed most to realized performance
• How loss ratios vary across strategies and investment partners
• Whether deal outcomes are widely distributed or overly dependent on a few winners
• Whether returns come from operational improvement or multiple expansion
But this requires granular data, robust methodologies, and significant analytical effort—resources that are often stretched across growing private markets portfolios.
Data provided by GPs often comes in disparate formats, with inconsistent definitions or unstructured fields. It makes standardization difficult. Investment teams can spend disproportionate amounts of time cleaning, mapping, and rebuilding datasets before any real evaluation begins. This manual and fragmented process limits the number of managers that LPs can review in depth and can impede their search for top-performers.
This raises the need for investors to conduct essential asset-level analysis in a structured, scalable way, without the burden of navigating disparate GP datasets. To meet this challenge, eFront Insight now incorporates Preqin market intelligence and benchmarking alongside eFront analytics and managed data services, allowing LPs to outsource the collection, validation, and processing of fund and asset-level data