Managing Director & Senior Partner
Related Expertise: プリンシパル・インベスター、プライベート・エクイティ, ファンド戦略・オペレーション, デジタル/テクノロジー/データ
The global private equity (PE) industry is continuing to outperform other asset classes, but at the same time, it is being buffeted by a changing environment. Unprecedented levels of dry powder and a steady rise in the number of new firms are leading to intense competition for high-quality assets. Average deal multiples have increased by 40% over the past five years, and the number of deals that close in less than five weeks has risen tenfold. Compounding these issues is the surge in unregulated yet high-caliber sources of private-debt financing; it is further driving up the price of quality assets across deal sizes.
These challenges spotlight an opportunity for investment professionals at PE firms: as the world becomes increasingly digitized and analytics tools become more powerful, investors can gain a clear edge over competitors by using data analytics to better identify and assess targets. Top-performing firms are beginning to view data analytics as a complement to their existing channels, procedures, and processes.
Data analytics can improve a PE firm’s performance all along the deal value chain. But in this article, we focus on the initial stages: deal sourcing and due diligence.
Deal sourcing is the first stage of the PE value chain. It is often the most important stage for generating a competitive advantage and still very much a human endeavor—there is no algorithm or digital process that can source winning investments.
But by using data analytics tools, investment professionals can gain access to far more information about a much larger universe of companies than they could possibly do through traditional processes. They can also evaluate a tremendous amount of unstructured data—such as social media posts, quality ratings, and customer reviews—to identify potential targets. Moreover, new tools are emerging to help investors understand which information is truly relevant and the meaning of data patterns and trends.
In short, data analytics tools can provide richer and more comprehensive information about a potential opportunity than conventional processes can produce. These tools can also help investors assess multiple variables, such as increasing consumer engagement and the opinions of influencers, and thus generate deeper and more actionable insights. Professionals who use these tools will be able to see various aspects of a potential investment (or the sector in which it operates) faster and with more granularity than their competitors will be able to do. (See the exhibit below.)
For example, one rapidly evolving digital tool, social media analytics, can monitor brands—tracking the number of customer mentions or brand hits in the media, for example—and send customized alerts when patterns shift or certain thresholds are reached. Receiving advanced notice about brands that are generating buzz lets investment professionals further analyze those companies, assess the market positioning of the brands, and evaluate consumer sentiment in online discussions. (See “How Social Media Analytics Can Be Applied to PE Deal Sourcing.”)
Social media analytics is an evolving tool that can help investment professionals translate broad investing themes and trends into actionable insights, in the form of attractive investment opportunities. PE firms can contract with a growing number of vendors that provide social media analytics as a service.
Here’s an example of how this tool could be used. (See the exhibit below.)
Social media analytics is often associated with B2C industries. Many PE firms view it as a way for consumer-focused companies to anticipate current and potential customers’ wants and needs and stay a step ahead of the competition. However, such tools are equally applicable to all industries.
Indeed, the global PE industry is beginning to understand the sheer potential of applying these innovative tools early on in the investment value chain. “Digital and advanced analytics during the sourcing process allow us to move around pieces of complex data in different ways to really see the excitement of an opportunity,” noted a partner at a large-cap fund. “We have the same data as everyone else, but we can generate completely new insights if we just interpret patterns differently. We’re not quite there yet, but we’re rapidly moving in that direction.”
Importantly, data analytics tools enable investment professionals to identify more proprietary deals. (A proprietary deal can take one of two forms: a deal in which a firm is the only bidder, or a deal in which a firm is the first of multiple bidders and has a significant head start in terms of a relationship and access to company information.) The investment director at a leading midmarket fund told us, “Of course, everyone is trying to find a proprietary deal, but we know that it’s nearly impossible once transaction sizes move beyond the lower midmarket.”
After identifying potential targets, investment professionals can partner with companies that have the data analytics tools required to create multidimensional views of those opportunities. These tools can complement conventional analytics processes and, in the hands of those who understand how to use them, allow investors to dig deeper into companies’ performance and potential.
For example, data analytics tools can help an investor explore how to develop or grow a market for a company or its products. Key areas of analysis may include potential pockets of value, customer demographics, brand value relative to the competition, and potential new customers. These tools can also help validate the market—and company—specific assumptions being used in valuation models and inform a PE fund’s subsequent bidding strategy. By combining data analyses with conventional analyses, investors can gain unique insights and spot early indications of value creation opportunities. (See “Data Analytics Delivers Due Diligence Insights for a PE Firm.”)
An investment professional at a leading PE fund was conducting due diligence on a consumer products company. In addition to using more conventional analyses, the investor and his strategic partner used data analytics to understand how the company performed relative to its competitors in several areas. (See the exhibit below.)
In addition to the uses we’ve mentioned, data analytics tools are helping PE firms in the following ways:
Data analytics tools are increasingly applicable to helping PE investment professionals identify potential targets and conduct due diligence. And as the world is increasingly digitized, the trend is likely to gather momentum. These tools are continuously evolving and can be customized to reflect the theses and investment strategy of a given PE firm; we have only scratched the surface of the proprietary insights that can be generated. The investment professionals who embrace and apply these tools will give themselves a sustainable edge. Those who don’t risk putting themselves at a permanent disadvantage.