Transforming Data Science into a Competitive Advantage for PE Firms
The Rising Significance of Data Science in Private Equity
To stay ahead in the current market, PE firms require a unique edge. For many, this edge is provided by data science and machine learning, which reveal fresh insights about potential value sources for both targets and portfolio companies — affording the competitive advantage needed for successful bidding and efficient post-deal execution. Now is the time for PE firms to leverage the benefits of data science, lest they risk falling behind.
Data science isn’t a novel discipline in the business world. Insurance companies have deployed advanced data techniques for several decades, while social media companies use data science for diverse purposes, from facial recognition in user photos to micro-targeted ad messaging.
In the past, the use of data science in PE wasn’t deemed practical due to several factors:
- The data required for comprehensive deal analysis wasn’t easily accessible.
- There was a lack of software to efficiently process the data.
- Data scientists weren’t incorporated into the deal process.
- Analysis couldn’t be executed within the short timeframes dictated by the deal context.
However, the past five years have seen a dramatic shift in the landscape, opening up opportunities to integrate data science into the deal process. The advent of advanced capabilities such as cloud computing, open-source software, and a wider pool of trained professionals have enabled the rapid analysis of vast datasets within the narrow time constraints of deal contexts. This presents PE firms with the opportunity to employ sophisticated data analysis methods to uncover value, both pre- and post-deal.
Capitalizing on the Data Advantage to Triumph in Bids
PE firms can leverage data science to probe deeper into data offered by specific targets, and then amalgamate these insights with external data sources. Thanks to technological and procedural advances, these insights can now be obtained at deal speed. This enables PE firms to develop a more comprehensive and accurate depiction of a target’s growth prospects and potential performance enhancements. By harnessing data science, PE firms can reveal hidden value levers related to identified deals, facilitating more competitive decision-making.
Unearthing Growth Opportunities Pre-Deal through Data Science
Crafting a winning valuation necessitates a lucid understanding of a target’s business model, along with its potential threats and opportunities. Key queries include:
- How does the target compare to its competitors in the market?
- Are the sales, marketing, and customer success functions performing efficiently and effectively?
- Which products, value propositions, and brands are underutilized in the market?
While traditional due diligence analysis attempts to answer these questions at a high level, the application of data science can swiftly detect a variety of concealed market signals, and more accurately predict how specific actions or events will influence growth forecasts. Revealing these insights can provide a decisive advantage in competitive bid scenarios.
In essence, data science can serve as a powerful tool to uncover a broad spectrum of potential growth opportunities.
