At Advent, data science is embedded across the investment lifecycle. Jesse Thomas, Head of Data Science, explains how his team leverages data to help Advent see opportunities earlier and support portfolio companies more effectively.
Why did Advent make data such a priority?
We live in a data rich world, but there is a drought of insight. At Advent, we’ve always believed that differentiated insights drive better performance. As the availability of data exploded, it became clear that we needed dedicated capabilities to capture and apply those insights systematically.
Our data science team complements the investment expertise Advent has built over the last 40 years, applying analytical precision to bring a powerful new capability to every stage of the deal cycle.
Where do you see the biggest impact of data science in the investment lifecycle?
Data is an asset, but not everyone knows how to leverage it for impact. At Advent, we’re seeing tangible results across the investment lifecycle.
Diligence is a key focus area. By analyzing large, unstructured datasets – such as digital footprint data, hiring trends, or consumer reviews – we can uncover opportunities faster and then carry the ball further.
Equally value creation is a priority. Many of our portfolio companies hold untapped data assets. By helping them structure, analyze, and act on that data, we can drive real performance improvements in areas such as pricing, customer retention, and operational efficiency.
Can you share a concrete example from the portfolio?
A great example is in customer retention. Across portfolio companies such as Planet, Xplor, and myPOS, we analyzed customer usage patterns to understand where engagement was trending lower. We then built an AI-driven model that flags when a customer becomes less engaged.
This model delivers tailored customer-retention lists to account managers weekly, enabling proactive outreach that improves satisfaction and retention. Importantly, it’s a proprietary Advent capability that can be deployed across multiple companies in as little as six to eight weeks.
AI is a buzzword these days. How do you separate hype from substance?
AI is everywhere in today’s conversation, but the real value comes with focus and discipline. We start with the business: how can it serve customers better, compete more effectively, and grow? From there, we identify where AI can truly move the needle.
We’ve seen success in areas like customer experience, product innovation, and operational decision-making, but we’re pragmatic. If the biggest opportunities lie elsewhere, in pricing, distribution, or M&A, that’s where we focus. What’s critical is that AI serves as a powerful enabler, not a distraction.
Another misconception with data, data science, and AI is that miracles can happen. I think it’s important not to underestimate commercial intuition – the intuition of founders and management teams. It’s the job of my team to marry those intuitions, with the insights driven from the data, to help form nuanced actionable insights.
How does the data science team work with Advent’s portfolio companies?
Collaboration is the foundation. Our data science team works hand in hand with deal teams and portfolio management, listening first and then tailoring solutions to each business context.
Sometimes that’s a complex machine learning model. Other times, it’s a simple dashboard that provides clarity on a key metric. Our role is to translate the potential of data into practical, actionable insights that support strategy.
What excites you most about the future of data in private equity?
We’re only scratching the surface. As data becomes more granular and computing power continues to advance, the ability to understand businesses in real time will transform how we invest and operate. What excites me most is the opportunity to combine human judgment – the experience of our investment and management teams – with the precision and scale of data science. That combination is where the magic happens.
