After two years of difficult market conditions, private equity (PE) activity is finally showing signs of recovery. In the first half of 2025, PE exits reached their highest level in three years, driven by increased corporate acquisitions and continuation funds. Yet challenges remain – geopolitical tension, high interest rates and economic uncertainty continue to make buyers cautious. Valuations are stabilising but still below peak levels, meaning fund managers are taking a more disciplined approach to both deal selection and portfolio management.
For companies planning an exit, particularly those targeting sophisticated PE buyers, this environment demands a far more rigorous approach to data. The era of simply showcasing headline growth is over. Data now underpins every credible value story, revealing operational efficiency, defensibility of revenue and scalability. A solid data strategy, combined with the ability to extract and apply insight, is no longer a ‘nice-to-have’ but fundamental to de-risking transactions and securing strong valuations.
Despite this, robust data remains a major pain point. EY’s latest Private Equity Exit Readiness Study found that 72% of PE respondents cited access to comprehensive data and KPIs – to validate historical performance and forecast future trends – as their biggest challenge, ranking ahead of inexperienced CFOs (63%) and underdeveloped systems and controls (48%).
Much of the difficulty stems from the nature of PE-driven growth. Many mid-market firms expand through complex buy-and-build strategies, inheriting fragmented systems, inconsistent reporting and limited governance. Even organically grown businesses often find that the data used for daily operations lacks the depth and rigour required in an exit process. The focus on top-line metrics often outpaces data maturity.
Historically, data ownership sat within IT or finance, managed through static monthly reports. But PE firms are now far more data-led, analysing a broader and deeper set of metrics from customer behaviour and product revenue to retention rates, ARR and team performance. Extracting this insight requires a cultural shift: treating data as a strategic management asset, supported by infrastructure and people who can translate information into action.
The role of data in shaping valuations will only intensify. It’s no longer enough to claim profitability has grown by a certain percentage; buyers expect that story to be backed by granular, auditable analytics. The static “data cube” of old has evolved into a scalable data asset that continues to deliver insight post-acquisition, giving investors confidence in the company’s ability to manage future growth.
To stand out, management teams must demonstrate how they use data to highlight operational efficiency, scalability and long-term viability.
Data can bring operational efficiency to life through metrics such as customer acquisition cost (CAC), lifetime value (LTV) and their ratio, tracked over time at individual customer level. Support ticket volumes, resolution times and customer satisfaction scores show the strength of service operations. Even development data, from engineering productivity to release cycles, illustrates product efficiency.
Scalability can be evidenced through infrastructure utilisation, cost-to-serve ratios and the automation of key processes. Tracking customer cohort performance over time provides visibility of sustainable growth potential.
Long-term viability depends on demonstrating loyalty and resilience: high retention rates, low churn, strong NPS scores and evidence of cross-sell and upsell success all point to a healthy, durable business with room to expand.
As AI becomes integral to dealmaking, buyers also want to see how firms are using it from analytics that identify at-risk customers to machine learning models that optimise pricing or operations. But this only delivers value if the underlying data foundations and governance are already in place.
In a challenging PE market, differentiation is everything. A clear, well-executed data strategy – presented within a compelling equity narrative – can set a company apart. Showing how AI fits into that roadmap strengthens the story further. Ultimately, investors want confidence that management teams understand, own and use their data in day-to-day decision-making, proving they can execute post-acquisition plans effectively.
The earlier a company starts this journey, the more value it can extract. Many of the metrics that make a business ‘exit ready’ also drive growth during the hold period, shaping equity stories well before a deal is on the table. As the PE landscape continues to evolve, those that leverage data best will command stronger valuations and secure better exits.
