Over the past several years, the pandemic and an uncertain, competitive investment landscape have rapidly accelerated technology innovation in the private markets, ushering in a new era for the portfolio monitoring function. Longer hold periods, rising capital costs, and the need for cash-efficient growth have pushed GPs to digitally transform their portfolio monitoring efforts to aggregate more granular data. Concurrently, amid larger private equity allocations, headwinds to PE’s return calculus, and a stagnant exit market, LPs, too, turn to technology in larger and larger numbers to gain greater granularity and transparency into their private market holdings.
Today, industry-leading institutions and sponsors use insights from aggregated portfolio data and live datasets to gain a competitive edge — streamlining operations, improving reporting, and enhancing data analysis. Amid the rapid innovation in private capital market technology, Holland Mountain and Chronograph hosted a panel discussion on how modern solutions are unlocking exciting new functionalities across the portfolio monitoring function, highlighting opportunities with data warehousing and AI and outlining the strategic approach firms must take for successful technology implementation.
By enhancing their portfolio monitoring infrastructure with next-generation solutions, firms have created a unified source of truth for their data. This allows them to extend the reach of their portfolio monitoring data beyond traditional functions like valuations and reporting to include strategic applications in fundraising, deal negotiations, value creation, and more.
GPs are navigating a cold fundraising climate. With intense competition for LP capital, leveraging portfolio company data can offer several key advantages. As fundraising cycles grow longer, relying on a static dataset is insufficient; LPs demand real-time metrics and often pose specific questions that necessitate agile data aggregation. GPs with modern portfolio solutions can easily update their presentations and respond to these inquiries, building LP confidence through prompt and transparent communication.
Portfolio company data can serve as a compelling asset in competitive investment processes, strengthening a GP’s argument for why they offer the best value in a given deal. By consolidating historical and active portfolio monitoring in one place, firms can easily showcase how they’ve added value in similar contexts.
For example, Sam Price, a Panelist from Bowmark Capital, explained how their firm uses its harmonized, granular historical data to gain trust with potential portfolio companies by demonstrating how they’ve impacted growth trajectories in comparable businesses and sectors. Without a sophisticated technological infrastructure, generating these kinds of insights consumes significant time and resources.
The rapid evolution of AI presents one of the most exciting trends for the portfolio monitoring function. AI has already offered meaningful value-add use cases for private equity investors, with many experimenting with the technology across various applications.
This said AI has yet to cause a transformative shift in private market workflows. One challenge is its fast-paced evolution — applications built with ChatGPT-3, for instance, became outdated with the release of ChatGPT-4. Additionally, AI’s main strength lies in generating statistical probabilities, which, while valuable for improving productivity and sparking creativity — can’t produce investment alpha. Skilled professionals remain essential for sound decision-making.
This uncertainty places private equity investors in a challenging position. With true value-added applications still emerging and the technology evolving rapidly, creating a definitive strategy for harnessing AI is challenging. Yet, failure to act risks falling behind the curve. With this in mind, our panelists shared several best practices for achieving “AI readiness.”
Despite a significant move toward data-driven portfolio monitoring, the industry is still in its early stages, with Excel remaining the biggest competitor to broader tech adoption. Currently, only about 65% of LPs and 50% of GPs employ technology in their portfolio monitoring frameworks, with many firms operating off of massive, complex Excel spreadsheets that are error-prone, surface ‘key man’ risk, and lack auditability.
How can firms get investment team buy-in for new technologies? The event panelists offered several key insights:
Request a demo to learn how Chronograph empowers private capital investors to create a single source of truth, power advanced use cases of their portfolio monitoring data, and more.
Get updates in your inbox
Learn how Chronograph can streamline your private capital investment monitoring and diligence