The private equity landscape is changing dramatically as a result of machine learning algorithms, data analytics and other AI technologies.

Private equity, along with other investment in non-public markets, remains a hot topic for wealth managers. It is therefore important for wealth advisors, family offices and private banks to grasp the dynamics shaping private market investment. One of those forces is technology. In this article the author, Natalie Cramp (pictured), at JMAN Group, explores the increasing datafication of private equity and the shift from a prevalence on personal connections, networks, and intuition to one where decision-making prioritises data and analysis. She asks how private equity firms can stay one step ahead of this transition with new skills, putting data foundations in place and changing recruitment practices. 

JMAN Group is a data consultancy that mainly concentrates on private equity. The editors are pleased to share these views; the usual editorial disclaimers apply. To comment, email the editors at tom.burroughes@wealthbriefing.com and amanda.cheesley@clearviewpublishing.com

Not too long ago, relationships, experience, and a “gut” feeling, coupled with a basic level of technical analysis enabling some data storytelling, might have proven to be all that was needed to secure a lucrative private equity deal. Market conditions have meant that is no longer the case, but data and digital transformation offers opportunities for people to respond to this. 

Over the past decade, there has been a rapid development in the way private equity firms use data throughout the deal lifecycle to make more informed investment decisions, optimise portfolio performance and enable faster identification of potential acquisition targets through advanced analytics and AI. Essentially, data is no longer a ‘nice to have’ but has become a key driver of value creation in private equity.

The rapid pace of this change means that it is now a key focus for those seeking to create a competitive edge in what is becoming an increasingly dynamic investment landscape. Equally, those who fail to take heed risk being left behind. 

For professionals operating in the private equity space today the rise of advanced data strategies, along with the complexities and challenges that it brings, may well feel overwhelming – it represents a significant shift for an industry. Private equity professionals are starting to recognise that they will need to adapt and, in many cases, acquire new skills to make the most of the technology available to them in order to thrive in this new era of data and AI. So just how will we see the traditional skills of a private equity professional changing?

A role that will evolve, not be replaced
The first thing to make very clear is that no machine is ever going to fully replace the human private equity professional. It is a role that relies heavily on skills that robots simply cannot replicate, evaluating complex risks, refining portfolio strategy, creativity and crucially deepening relationships with business owners, investment bankers, and other stakeholders. However, the advent of AI-driven data strategies means that private equity professionals can now access the visibility needed to make faster, more precise investment decisions and uncover hidden opportunities. 

Historically, private equity investment teams have spent enormous amounts of time and resources on network-driven deal sourcing and laborious market research in the hunt for the best opportunities. Often, the amount of capital and time involved will have limited the number of opportunities a firm could effectively pursue, particularly a smaller fund. Using this approach, research suggests that a private equity firm would need to assess approximately 80 prospects to secure one investment. For busy, time-poor investment teams there is a clear incentive to streamline this process as it vastly increases efficiency and enables their skilled professionals to concentrate on identifying better deals early on. 

Data-savvy private equity professionals
At a basic level, many private equity professionals will soon find that their job is no longer predominantly relationship-focused but places equal, if not even greater, weight on the importance of data. Put bluntly, it is balancing the who you know with what you know – as evidenced by granular data and detailed factual insight. With this comes new skills that have never traditionally been called upon. Private equity professionals now need to maximise the potential of data-driven strategy in the sector. This includes the skills they need in relation to interpreting data, making consistent high-quality decisions and harnessing that data to improve strategic thinking. 

The most prominent manifestation of how the advances in AI-driven data strategy are impacting the private equity industry is in the growing use of AI to extract and generate deal sourcing insight, streamline due diligence processes, identify investment growth opportunities and support overall portfolio monitoring. PE professionals have always used and interpreted data to make decisions, but there is an additional level of understanding needed as there is more available data which can be processed rapidly to give insight. Using data in private equity goes far beyond simply knowing the numbers – it’s about being able to ask the right questions to get the data at your fingertips that is of value, extracting meaningful insights, identifying hidden opportunities, taking into account the limitations of the data and making strategic, informed decisions. Private equity professionals also need excellent communication skills to translate complex data insights into actionable information across their teams and stakeholders. 

It’s not about learning to code
This is not about just hiring data professionals to augment private equity teams. It’s about the upskilling of all investment and operating professionals to be able to comfortably use and interrogate data to take the next best action in their roles, evaluate the progress of their targets and their portfolio companies and know the art of the possible to ensure that their portfolio companies are maximising the value creation lever that data and AI offers. 

Future-ready
The private equity landscape is changing dramatically as a result of machine learning algorithms, data analytics and other AI technologies. Whilst data upskilling will be critical for success, it is not as simple as knowing the numbers. Just as important will be having a curious mind and the will to constantly update your expertise and learn new things, and work with experts who can support this. As this transformative period progresses, we can expect to see a new breed of private equity professional that isn’t just data literate; but is agile, creative and able to rapidly adapt data-fuelled insights into innovative strategies, ensuring that they can navigate and capitalise on a dynamic investment landscape.