How data readiness can improve private equity exit value

Over the past few years, private equity (PE) firms have had to adapt to longer hold periods, increased investor scrutiny and fewer exit opportunities. In a market shaped by geopolitical and economic uncertainty, prospective buyers are more cautious. They want a clear, credible and detailed view of how a business creates value. Without it, they will either discount or simply walk away.

This environment has pushed exit readiness up the agenda. Across markets, sponsors face growing pressure to ensure assets are genuinely fit for sale. Those that can move quickly when opportunities arise and respond to buyer questions with speed and precision, are best positioned to achieve attractive outcomes. At the centre of this challenge is data.

Exit readiness expectations are higher

Achieving a successful exit is becoming increasingly important for private equity investors. Across the globe, PE firms are invested in more than 30,000 companies valued at US$4.2t, including 30% of which that have been held in excess of 5 years. The industry faces growing pressure to return capital in a market where exit opportunities remain constrained. This context underpins the findings of the EY Private Equity Exit Readiness Study 2025¹, which examines the main barriers to realizing value at exit.

The study highlights data exit readiness as one of the most significant challenges. Almost 72% of firms identify weak data and KPI reporting as the biggest finance issue at exit. Two thirds (65%) struggle to reflect value creation initiatives accurately in reported EBITDA, while 41% lack the data granularity needed to substantiate their equity stories.

The underlying message is clear. An exit is a rigorous test of information quality. Assets that are not prepared for the intensity of buyer due diligence see confidence erode, valuations come under pressure and timelines extend. By contrast, strong data exit readiness enables sellers to evidence value credibly, manage diligence more effectively and retain greater control over exit timing and outcomes.  

The imperative for sellers: address data readiness early

Good data readiness combines high quality data, strong reporting capability and clear alignment between operational metrics and financial outcomes.

Achieving this is often challenging. Growth through acquisition can leave data fragmented across systems, while limited operational transparency slows decision making and makes it reactive. Many assets also struggle to track and demonstrate the true impact of value creation initiatives. Left unresolved, these issues surface during diligence, undermining credibility at the point of greatest scrutiny.

Early data exit readiness also delivers benefits well before a sale. Reliable, well aligned data improves decision making during ownership, enabling management to identify opportunities, allocate capital more effectively and course correct sooner. These capabilities strengthen performance ahead of exit and carry through into a more credible and controlled sale process.

If data issues are not addressed, they will erode value at sale. The closer these problems are left to exit, the greater the impact on valuation, timing and deal certainty. Late remediation weakens buyer confidence and increases friction during diligence.

By contrast, early access to verified and consistent data reduces perceived risk and attracts stronger buyer interest. Securing data readiness at least 12 months and ideally 24 months, before exit also allows management to demonstrate a sustained track record of data driven decision making and maintain momentum through the sale process.

Real-world case studies: enhanced data readiness in action

In one exit scenario, a PE-backed fast-growing international technology asset was being prepared for sale but faced challenges due to historic issues with billing data. Reporting was manual and error-prone, which resulted in limited visibility of key value drivers (i.e., churn, retention, cross-sell). These issues made it difficult to clearly explain growth drivers and performance trends to potential buyers. Following a focused data review and remediation effort, which involved re-building 5 years of transaction data and cleansing anomalies, the asset was able to present a clear and coherent growth story of increased retention, international expansion and cross-sell supported by reliable data. The exercise reduced churn by approximately 20%, resulting in increased net retention and a successful exit at a ten-times multiple and five-times the original investment.

In another case, an investor supported an asset in strengthening its business-as-usual (BAU) reporting in advance of a planned exit. The business had grown through acquisitions, with five separate business units operating on different enterprise resource planning systems (ERPS), with limited visibility of performance across the group. Preparation began 24 months before sale, with a focus on building a robust solution to support BAU reporting and value-creation initiatives. This early action enabled clearer insight into operational KPIs and commercial drivers, which enabled the business to identify “at-risk” customers and reduce churn by 5%, as well as undertake a pricing optimisation on underperforming customer segments. These two value-creation levers alone resulted in a 15% increase in EBITDA. Upon exit, management had an established fact base to reference and leveraged it to prove the value added and create a stronger, more defensible equity story.

What are the risks of acting too late?

The case studies above highlight the value of early preparation. By contrast, the risks of delaying data exit readiness are clear and often material. When data issues are left unresolved until a sale process is underway, sellers lose control at the point when scrutiny is highest.

Late action typically forces a reactive data clean up during due diligence, increasing cost, management distraction and execution risk. This can lead to extended diligence timelines, buyer frustration, reduced confidence in management reporting, missed opportunities and ultimately lower valuations driven by metrics that cannot be verified.

The first step: a deep-dive data diagnostic

Data exit readiness is critical to achieving the best possible exit valuation, but there is no single approach that works for every asset. Each business has a different operating model, value creation strategy and buyer profile. As a result, readiness efforts must be tailored to the specific questions and assessment that prospective buyers will apply.

The most effective starting point is a focused data diagnostic. This involves a structured review of data quality, availability and alignment across financial, operational and commercial areas. A well-designed diagnostic provides immediate insight into how effectively data supports decision making, highlights strengths and gaps and informs a clear roadmap for improving systems, reporting and KPIs in ways that directly support exit readiness.

How confident are you that your data would stand up to scrutiny during an exit? To assess this, sponsors and management teams should ask: