Watch Out! Private Equity Transforms Digitally

by Karolina Jaszczuk and Victoria Rakitin

Introduction

It started with the microchip in the fifties, home computers in the seventies, cloud computing in the last decade, and most importantly on-premise tech with Covid-19: the digital transformation is sweeping over, and it has finally arrived to Private Equity (PE). This paper will review digital transformation trends in PE, diametrically observing the impact of digital technology–big data, machine learning, and AI included–in pre-deal and post-deal investments. Considering ﬁrms such as EQT Ventures and Bain Capital as case studies, we will capture the impact of this digital revolution in a contemporary-world scenario.

In a broad sense, the digital revolution implies integrating current digital tools and data and analytics technologies into a business. PE ﬁrms are boldly heading in this direction–and it is true that whoever is not, is quickly left behind. In fact, according to S&P Global’s 2022 Global Private Equity Outlook illustrated in Exhibit 1, Europe is leading the race towards digital prowess in PE, with nearly three-quarters of survey respondents displaying at least an early implementation phase. Nevertheless, it is evident that digital transformation is high up on PE agendas across all regions, even Latin America.

Before diving into the topic, we want to draw a line between simple “digitization” and digital transformation through innovative technologies. While the first involves solely transposing physical information and amending an analog form, such as paper documents, to a digital format that can be used in computers, the second (which this article discusses) encompasses a much wider scope that vertically impacts a company in all stages of its business. Digital transformation requires “cross-cutting organisational change as well as the implementation of digital technologies,” which becomes a core value in PE and a source of value creation throughout the industry’s operating process.

The Digital Revolution in the Pre-deal PE Process

PE has traditionally relied on resource-intensive methods to source deals, but now many businesses are starting to use big data and AI to streamline the process to identify better opportunities earlier. This digital transformation responds to a shift in interest in the PE industry to do direct sourcing as opposed to relying on intermediated deals or sponsored deals. Considering the array of companies in the United States, there are about 5,000 to 6,000 companies that are publicly traded and a few hundred thousand that have transacted or have some sort of sponsorship. However, there are tens of millions of bootstrap companies–those that start with little capital and no outside funding–that PE struggles to draw information from but sees ample opportunities in. It is this group of companies that becomes enabled to PE by the digital transformation.

AI algorithms (offered by businesses such as Fractal Analytics and Kensho Technologies, or in-house by proprietary platforms) can analyse large amounts of seemingly inconclusive data to identify patterns and trends and provide PE ﬁrms with insights that they can use to make more informed investment decisions. Altogether, these algorithms allow industry leaders like KKR, Blackstone, and EQT Ventures in: deal origination (to see more possibilities), target outreach (to get there early), and market intelligence (to ﬁnd the right deals). Of striking relevance in the last decade is EQT Ventures’ development of Motherbrain, their proprietary investment platform driven by diversiﬁed big data and cutting-edge algorithms. Motherbrain “scans the startup universe for leading signals in the digital footprints of companies,” enabling EQT Ventures to future-proof potential portfolio companies that have promising outlooks. So far, Motherbrain has directly led to investments in 7 startups out of the 50 the ﬁrm has made, including an investment in Handshake, a career networking business, which at the start of 2022 was valued at nearly $3.5 billion.

Also in the pre-deal stage, the digital revolution enables PE ﬁrms to perform scenario and growth analyses on ﬁnancials, which in turn allows them to develop appropriate growth models for potential portfolio companies. KPMG is one example among dozens in PE who has a proprietary platform with virtual data rooms for limited partners to access data, check risk positions, and do scenario analysis in real time. This data informs KPMG’s models, which

absorb both internal and publicly available market data. PE ﬁrms, in turn, can use this in order to generate alpha or mitigate risk.

A valuable example is Two Six Capital, a data science consultancy ﬁrm. Two Six Capital understands data by using around 28 standardised analyses and 18 statistical machine learning models, such that speed and eﬃciency become a top realised competitive advantage. Two Six Capital co-founder Ian Picache makes it clear: in an interview published in Knowledge at Wharton, he explained that “in commercial diligence, you’ve got four to six weeks to make a go/no-go decision on the deal. Two Six Capital can take in large volumes of data, and quickly come up with a point of view on [the question], ‘Is this company going to make returns — yes or no?’”

The Digital Revolution in the Post-deal PE Process

The role of technology goes beyond ﬁnding new investment targets for PE funds and beyond optimising the process of ﬁnding new investment targets. Moving deeper into the deal lifecycle, PE funds are starting to notice the advantages that leveraging software developments can provide to their businesses in the post-deal investment phase. As reported by a KPMG survey of PE ﬁrms and portfolio companies, almost a third of respondents said that they planned to invest signiﬁcantly more in digitising the customer-facing side, while data analytics was close as a priority for substantial capital allocation (Exhibit 2)

Moreover, many agree that cost reduction is merely a beneﬁcial by-product of digital transformation. Its full potential can be realised by leveraging automation-enabling tools to increase competitiveness and help scale portfolio companies. A stellar example of leveraging technology in value-creation strategies is Bain Capital’s investment in Kantar, a marketing research, and media company. The company was looking for ways to optimise supplier and risk management, automatize data collection and analysis and digitise internal and external processes. On the advice of KPMG, Kantar implemented a cloud-based procurement technology platform and systematically started to unlock best practice source-to-contract processes and supplier risk analysis tools. Equally important, the ﬁrms ensured that the Kantar team was engaged in the journey and trained in the new system from the get-go. The new technology system enabled the company to retain more control over the procurement process and eﬃciently mitigate risks.

A turning point in the digital transformation of PEs will be the modernising of its operations by leveraging AI, Hyper Automation, and Process Re-engineering technologies. Robotic process automation has made it possible to automate repetitive back- and mid-office manual operations, such as: trade, settlements, and fund accounting. Quick data access is crucial for PE firms to answer investor questions, help instil conﬁdence in buyers, and accomplish the sale sooner. Automation will facilitate easier analysis and enable PEs to identify and address compliance and risk issues, ahead of time. This technology has also been a benefit to leading PE firms.

Where are we headed?

PE ﬁrms increasingly look to data and analytics to improve informed decision-making. As presented above, digital transformation has its application not only in deal sourcing and growth modelling during the pre-deal phase but also can be leveraged for improving portfolio management, due diligence, and creating value strategies at the exit stage.

The digital transformation of the PE industry does not mean a complete elimination of human judgement and experience, especially in crucial investment decisions. Human resources, as well as some traditional methodologies to ﬁnd and evaluate the potential investment targets of their portfolios, like company earnings, industry reports, cash ﬂows, and expenses, will remain important in the deal processes.

On the other hand, digital transformation carries some risks that any company should consider in advance. The primary concern is data security, in particular in cloud-based environments, where misconfigurations can lead to insufficient breach detection. Similarly, in the case of automation platforms, if the volume and complexity of data exceeds expectations, it can ultimately lead to poor performance of the systems. It is therefore crucial to manage expectations, establish realistic goals for the business and hire qualified staff to manage new technology implementations. By understanding the risks and learning how to mitigate them all organisations will be able to reach their digital objectives. PEs should therefore prioritize new methods of risk identification and automation controls that will enable them to identify risks ahead and address them in a timely manner.

Ultimately, in accordance with the arguments presented above, some tools of digital transformation, such as big data and advanced analytics will soon become a game-changing necessity for PE ﬁrms that wish to win against the competition.