Private equity sponsors have long poured over cap tables, term sheets, market statistics, regulatory filings, sector reports, demographic figures and career backgrounds in their hunt for the most attractive acquisitions. At the heart of the whole process is the harnessing and analysing of one thing: data.
Strategic investment decisions are predicated on large amounts of disparate pieces of information, and many hedge fund managers seem to understand the value of crunching information from across a disparate universe. Yet it appears private equity may be a little way behind them when it comes to adopting the latest analytics in the due diligence process, if the responses of several sponsors contacted by PEI are anything to go by.
Big data, after all, offers financial buyers the opportunity to uncover either positive or negative information about a target company at a time when competition for deals is stiff. The ability to access traditionally hidden facets that underlie business performance – such as core customer product spending patterns, the impact of macroeconomic trends or the assessment of consumer sentiment about a company's brand – is one of the myriad ways big data analytics can be drawn upon during the due diligence process, according to Nathan Saegesser, a managing director in KPMG's deal advisory practice.
Seth Brody , partner at Apax Partners and global head of the firm's operational excellence group, said the group is able to utilise big data analytics in its deal sourcing and due diligence process. “We parse through terabytes of data, proprietary and public domain, to reveal companies and market segments ripe for deal sourcing activity.”
Once a potential target's data set is received, he said Apax uses analytics to identify “whitespace” growth opportunities, operational efficiencies, and potential future M&A opportunities. “Deal teams are rapidly embracing these capabilities as it differentiates Apax in competitive processes and helps them to work more efficiently,” he noted.
Whether it's the opportunity to acquire a corporate orphan from a large public company, a secondary buyout of a private equity portfolio company, a founder-owned private enterprise or public company, there's an argument to be made that cutting-edge analytics that can process large sets of diverse data may be just the tool to give an investment team the edge it needs to close a deal.
As Saegesser told Private Equity International: “Private equity investors are extremely savvy, always competitive and looking to gain an edge. Big data analytics is one tool that they can use to become more successful investors and move more quickly in a strategic M&A sales process.”
Saegesser said the processing and analysing of raw data in connection with a target company acquisition or conversely a buy side assignment is increasingly appealing to financial buyers. While he declined to identify clients due to confidentiality agreements, the former Lake Pacific Partners private equity professional said KPMG has experienced “strong double-digit growth” in the adoption of the consultancy's big data capabilities in North America and Europe.
Financial buyers already draw upon diverse data sets to support their investment theses, including term sheets, private placement memorandum, SEC filings, industry reports, accounting records from company founders, background investigations and internet research. It stands to reason then that technology that can parse through this information in short order the way big data can could only prove helpful. Moreover, many buyout groups also collect ancillary data supplied by consultants, industry specialists and investment bankers that can be further analysed, whether as comps for comparable businesses, benchmarking or other purposes.
Not everyone is convinced of the value of the big data approach for financial sponsors when it comes to due diligence and the investment selection process. As a private equity scholar who spoke with PEI about the matter noted on background, the buyout industry has traditionally been well served by the use of “small data” in the form of the cash flow, financial performance and other data points that make up the deal analysis process.
For now, the jury is still out about whether private equity sponsors will embrace the use of big data analytics en masse when it comes to due diligence procedures. But, if the large amount of money venture capital investors are putting into big data companies offers any indication, the importance of cutting edge analytics is only going to increase in the coming years.