Demand for alternative investments has been rising steadily despite ongoing market volatility and is expected to continue its growth as investment managers diversify their holdings, hedge against inflation, and seek alpha in private markets. However, such a challenging environment also requires managers to make the best use of their resources—and data is proving to be among a manager’s most important assets.
In collaboration with IQ-EQ, we interviewed over a dozen senior leaders in private equity GP and LP firms across North America and Europe to ask how they are leveraging data to drive growth, what their data management best practices look like and where their priorities lay. Through these insightful interviews it became clear that operational leaders view addressing data quality and organisational culture as vital as technology in tackling data challenges.
Data is the oxygen of an organisation, serving as a strategic asset that drives decisions, growth, and profitability. To be effective, data must be “healthy,” and needs to be accurate, consistent, accessible, and comprehensible across the organisation.
Data is the starting point for knowledge – and in our business, accurate, real time and meaningful data and information contribute to investment success.
Anton KnechtFounder & Managing Partner at Dara Capital
GPs and LPs still grapple with a vast array of data from various sources and each alternative product type comes with unique requirements, adding complexity to data management. Common challenges include disconnected data stores, unstructured data, and non-compliance with data management standards, which all pose both operational and regulatory risks.
Manual processes are also prevalent in the alternative investment industry due to the illiquid and non-public nature of investments. Disparate data repositories, particularly in Excel, hinder transparency, and the ability to generate reports or answer investor queries. This situation increases the risk of errors and diversion of resources from revenue-generating activities.
Our interview findings underscore the importance of better data management practices for all, decreased reliance on Excel, and the need for greater use of technology to streamline processes in this context.
Enabling the Business Through Appropriate Technology Investments
Many firms face challenges as their technology and data management struggle to keep pace with growth, particularly in smaller companies. Interviewees compared the current technology landscape to the visual of a swimming duck — seemingly serene on the surface, but frantically paddling underneath the water.
In support of evolving data demands, two key data objectives stand out:
Data Centralisation: Unify data, aggregating it into a centralised data store for reliable access by other systems.
Efficient Technology Solutions: Seek specialised solutions to reduce manual tasks, releasing staff for revenue-generating activities, although understanding that complete elimination of manual work isn’t feasible in alternative investments.
While private investment is a people and relationship business, technology and data strategy are vital. Technology facilitates capability, with data as the foundation. The challenge lies in selecting user-friendly, flexible solutions. Some companies are adopting a mixed approach with a blend of outsourced technology, services, and strategic in-house development.
Firms that had pursued a single, one-size-fits-all approach found issues where implementation timelines caused a full suite solution to become obsolete before it was launched, which has led to a shift toward a “best-of-breed” strategy, allowing faster implementation. However, more systems result in more data silos, hindering data governance efforts, development of self-service applications, and adoption of new technologies.
To address this, many are prioritising a transition from a system model to a data platform that provides unified, high-quality data. Unfortunately for private assets, manual activities cannot be eliminated, but firms can aim to reduce these with “human-enabled technology” (best-of-breed apps and unified data stores) to improve efficiency and data quality.
Trusting the Data is Key
Addressing data challenges isn't just about technology; it’s also about mindset, behaviour, and organisational culture. Two critical cultural challenges must be tackled by firms:
Changing the attitudes of those resistant to new ways, and
Building trust in enterprise data quality.
When trust is lacking, people often resort to creating their own data silos, perpetuating an unproductive cycle. Overcoming misconceptions and changing beliefs is the challenging part of data governance. Capturing all data in the required repository with consequences for siloed data is essential.
Trust is earned by following appropriate data management and governance processes, ensuring quality, accessibility, and transparency. The benefits of investing time and effort in this transformation are significant. Clean, accurate, and trusted data can boost organisational efficiency, expedite insight generation, and enhance decision-making.
Using enterprise-processed data combined with individual team information also helps to make the decision-making process more scientific thereby reducing the emotional aspect.
Andrew HaywardCFO of Park Square Capital
Andrew Hayward, CFO of Park Square Capital, highlighted the positive impact, noting that teams are now more open to trusting data and learning what’s available, reducing the time spent preparing data and allowing more focus on evaluating opportunities. A data-centric mindset and culture are vital alongside technology solutions.
Alternative investment managers’ evolving data strategies are being driven by growing investor demands and competitive pressures. Key themes include:
Consolidating Data: Migration of data from disparate systems to cloud-based data warehouses. These repositories may be in-house or outsourced but focus will be on seamless data connectivity, bolstered by robust data governance.
Embracing Best-of-Breed: Component-based system strategies are becoming more popular. It is likely that internal development for strategic applications, coupled with outsourcing, will prevail, as GPs seek to integrate point solutions serving increasingly diverse end-users.
Empowering Investors: Self-service tools are transforming the way investors can access and interact with data, ultimately enhancing satisfaction and service efficiency.
Mobile Access: Understanding of the paradigm shift driven by younger investors demanding real-time data — and how self-service options must extend to mobile devices.
Artificial Intelligence’s Transformative Role: The gradual adoption of AI is pitched to focus on driving efficiency, enhancing insights, and aiding regulatory reporting across AIMs.