In the third edition of our private markets series, asset management specialist Dan Sharp explores the evolution of data requirements in the alternatives sector and outline how the increasing complexity of data management is challenging traditional operating models.
What is going on?
- Data volumes have grown exponentially. It is estimated that 90% of data that exists globally became available in just the last two years, a theme set to continue.
- The investment industry is “data hungry”, whether in private or public markets, and how firms manage and utilise data is increasingly becoming a key driver of competitive advantage.
- Today, more so than ever, having a sound data strategy will be the key determinant of a manager’s ability to deliver alpha and their competitive positioning.
- In a recent study conducted by Mercatus and State Street, 80% of firms surveyed were expecting investments in data (and technology) to provide game-changing operational efficiencies, improved decision making, and provide significant competitive differentiation.
- A recent paper published by BCG stated:
“The amount of data available to companies today is increasing exponentially. And companies that choose not to use that data to create value risk hastening their own obsolescence or, at the very least, losing competitive advantage”
- Both research pieces, as well as our on-going market interactions, lend support to our point of view.
What are the data pain points?
- Investor Relations: Rising investor expectations and demands for transparency equate to “data hungry” investors. Data requests span across all aspects of a manager’s business, including deal sourcing, execution, management, operations, finance and ESG. Poor quality data has had an impact on the ability of GP’s to accurately report performance to LP’s.
- Investment Management: Poor data quality and integrity leading to delays and errors in portfolio analysis, resulting in suboptimal investment or financing decision making. Inaccuracies in measuring performance reduce the ability to proactively manage portfolio companies to achieve targeted returns.
- Investment Operations: The existence of labour-intensive, error-prone manual processes to extract, transform, load, and analyse data, creating enterprise (investment, operational, regulatory, and reputational) risks.
- Escalating regulatory pressures: Regulators are increasingly demanding greater transparency, more frequent and detailed reporting, all of which requires rapid access to high-quality data.
- Operating model complexity: Rapidly growing business complexity across investment models, asset classes, and investment geographies increases the volume and variety of data. This often results in the creation of data silos making data management complex and challenging.
- Increasing competition and consolidation: Intensifying competition driven by heightened M&A activity presents post-acquisition integration challenges, one of which is the management of data across the new entity.
What is the opportunity?
We see a significant opportunity to drive greater operational efficiencies and agility, lower long-term costs, improve investment performance, reduce enterprise risk, and improve investor relations. This will be achieved by private market firms undertaking active programs of change that leverage technology, automation, and data to address the challenges.
A good place to start is to assess the maturity of your data capability, and develop a data strategy tailored to your specific position. This provides a platform to design and build a data operating model, ensuring the right tooling is in place as part of your broader strategic technology and data architecture. Contact us to find out more.
Author Dan Sharp
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