Data & Analytics supports deal teams and portfolio companies along the entire deal cycle, including the following stages:

• Exit preparation: Approaching the exit preparation of portfolio companies with a proactive and data-driven mindset is essential for a seamless deal process. Ensuring buyer expectations for a unified perspective on the target are met is crucial for maximizing exit value. Initiating this process three to six months ahead of the key due diligence activities is advisable, particularly for buy-and-build platforms. Our strategy is to assess the diverse systems landscape and data storage solutions early on regarding data availability. By engaging with relevant stakeholders to thoroughly understand the business model, we aim to construct a compelling, data-driven equity story. By integrating pertinent data sources into a flexible model, we can deliver timely updates at any point, allowing us to anticipate potential buy-side questions and requirements in advance.
• Deal execution: In recent years, integrating data cubes with detailed customer and revenue information has become essential for transactions, particularly in data-driven business models. The next evolution involves incorporating third-party data and developing multidimensional data models, which are visualized in dynamic dashboards. These tools enable stakeholders to discuss and craft or challenge the core investment thesis based on facts and in real-time. Such dynamic analyses offer a transparent view of the business model and its key value drivers, facilitating precise business planning and valuations. By utilizing alternative data sources — such as website traffic, brand reputation insights, consumer perceptions, and geospatial variables — we can provide a deeper market understanding and a competitive advantage in decision-making.
• Post deal: Adopting a data-driven strategy in the deal execution phase facilitates the early activation of key value creation levers during the holding period. By carrying forward insights and outputs from the due diligence process, companies can maintain full transparency of financial and commercial data from the outset. This approach allows the deal team to steer the business fact-based and consistently uncover new opportunities for value creation, including enhancements in commercial, operational, and financial performance. Using alternative third-party data sources provides valuable benchmarking against competitors, such as analyzing website traffic or store locations.

Private equity investors are well advised to think about an upcoming transaction from a Data & Analytics angle. How can the integration of data-driven strategies, ideally three to six months before due diligence help to meet buyer expectations and maximize the exit value? In what way can advanced data models enriched by third-party data and visualized in dynamic dashboards facilitate discussions about the investment thesis and business planning? How can we continue the data-centric approach, adapted during the transaction, to create transparency with the help of benchmarking through alternative data sources and activate the value creation levers? Data & Analytics is not just an optional tool, but a critical component that is transforming all stages of the deal cycle.

If you have any further questions, please contact our experts Dr. Timo Willershausen (timo.willershausen@pwc.com) and Dr. Johann Wenzl (johann.wenzl@pwc.com), who thankfully shared these insights in our Private Equity Newsletter. In addition, feel free to register to our PE webcast series (link) where we, among others, also cover this topic more in-depth during the session "Analytics Unlocked: Driving Deal Value with Data Insights" on 13 February 2025.