The emergence of data science in PE
To win in the current market, PE firms need an edge. For many companies, data science and machine learning are uncovering new insights about potential sources of value for both targets and portfolio companies — providing the edge they need for bidding and successful post-deal execution. The time for PE firms to realize the benefits of data science is now. Firms that do not employ data science risk being left behind.
Data science is not a new discipline in business. Insurance companies have been using advanced data techniques for decades. Social media companies use data science for everything from facial recognition in user photos to micro targeting ad messaging.
Historically, using data science in PE was not considered feasible for several reasons:
— The data necessary for complex deal analysis was not readily accessible.
— Software to effectively process the data was not available.
— Data scientists were not integrated into the deal process.
— Analysis could not be done in the short timeframes demanded by the deal context.
Over the past five years, the opportunity landscape for bringing data science into the deal process has changed dramatically. Advanced capabilities such as cloud computing, open-source software, and greater access to trained professionals have made it possible to quickly analyze various massive data sets in a tightly time-bound deal context. PE firms now have the opportunity to implement sophisticated methods of analyzing data to uncover value both pre- and post deal.
Leveraging the data advantage to win the bid
PE firms can use data science to delve deeper into the data provided by specific targets and combine these insights with external data sources. With advances in technology and processes, these insights can now be gained at deal speed. This will help PE firms build a more comprehensive and accurate picture of their target’s growth opportunities and potential performance improvements. By using data science, PE firms can uncover potential value levers related to identified deals that might not be obvious in order to make more competitive deal decisions.
Identifying growth opportunities pre deal through data science
Establishing a winning valuation requires a clear picture of the threats and opportunities of a target’s business model.
— What is the target’s position among its competitors in the market?
— Are the sales, marketing, and customer success functions operating efficiently and effectively?
— What products, value propositions, and brands are underleveraged in the market?
These questions and many others are key to understanding potential growth opportunities. While traditional due diligence analysis tries to answer these questions at a high level, applying data science can quickly identify a range of hidden market signals and more accurately predict how specific actions or events will alter growth forecasts. Uncovering these insights can provide a definitive advantage in competitive bid situations.
Data science can be used to identify a wide range of potential growth opportunities.
Source: KPMG
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