Rising capital costs and evaporating multiple arbitrage have renewed emphasis on private equity’s ability to drive portfolio company growth. Data can help investors get there – if it is used properly

Housing – defined as everything from rent to fuel to furniture – accounts for one-third of the value of goods and services used to track inflation in the US via the consumer price index (CPI). Yet the method and frequency of rent calculation mean that CPI rent inflation lags the market. The Brookings Institution found that CPI rent peaked in March 2023, one year after other indices that capture rents.

In July 2021, when CPI rent was beginning a gentle upswing from 1.91% while an index run by real estate marketplace Zillow had climbed nearly 8 percentage points over the previous five months, The Blackstone Group was already leveraging information drawn from its 10,000-asset property portfolio. Plugging these numbers into models across its different strategies, the firm was resolved to act.

“We made decisions globally in our portfolio, through pricing actions and cost mitigation and efficiency exercises, that put us ahead of the curve. We also pulled back from making certain investments because we had a view that interest rates were going to rise faster than the market expected,” said Michael Blickstead, Blackstone’s head of Australia and New Zealand private equity.

“If you are missing out on capturing [data] and learning from the insights, you will not be a good investor in this environment.”

Blickstead was speaking at the AVCJ Private Equity Forum Australia & New Zealand 2024 where investors espoused the virtues of value creation in a world where multiple expansion and financial engineering can no longer be relied upon to drive returns. Even buy-and-build, a cornerstone of operational strategies rooted in consolidation and efficiency at scale, is being called into question amid higher capital costs.

Bain & Company identifies this shift in its latest global private equity report, noting that a platform company acquired several years ago at 12x EBITDA with 7x debt now faces a cost of financing double what would have been modelled in 2020. At the same time, if a platform is worth less today than a year ago, the practice of add-ons at lower multiples to bring down the overall cost of acquisition is challenged.

The solution, in Bain & Company’s view, is to double down on organic expansion. This was endorsed by Richard Kunzer, a founding partner at US-based financial services investor Integrum Holdings. “It has become expensive to do roll-ups and fundamentally you are not building anything. It’s generating returns, but can that go on? Organic growth has always been our focus,” he told the forum.

“If you invest behind talent, because most of these businesses are people businesses, distribution businesses, and you invest behind technology – using AI [artificial intelligence] and analytics – to make distribution platforms more effective, and you invest behind business innovation, and you are doing this in partnership with management, you can consistently grow EBITDA.”

Know the numbers

Whether creating tools intended to enable more efficient distribution through digital channels or overseeing a traditional brick-and-mortar rollout, data is increasingly the starting point. Private equity firms have developed the expertise to collect it, analyse it, and turn it into actionable information.

“We see top-performing GPs using data internally or using specialist advisors and finding things within companies that were obvious, but people had never really unpicked and understood what lay beneath the surface,” said Andrew Thompson, head of Asia Pacific private equity at KPMG.

“As we move into generative AI and other new technologies, opportunity identification around the levers of value in a business is fundamentally changing.”

When asked about their approach to deal-making, private equity firms often emphasise sector expertise. Domains are well-defined, and they claim to seldom step beyond those bounds. The argument is that pattern recognition, underpinned by information and expertise gleaned from past investments, represents a powerful differentiator that gives conviction to pursue assets in ways others would not.

The way internal resources are organised and deployed has also evolved. Operations teams comprise sectoral and functional experts – covering areas such as human resources, brand management, technology, and business development – who work hand-in-glove with deal teams from the due diligence phase so that value creation plans can be locked down ahead of an investment.

For TPG, applying technology is key to unlocking growth, not least in Australia, where companies have historically been underinvested in R&D, according to Joel Thickins, the firm’s Asia co-managing partner. Data is integral to these efforts, though not necessarily through finding new ways to capture it. Using existing data flows in a meaningful way is a common starting point.

“There is often a big disconnect in pitch books between where companies are regarding their use of data and where they think they are, at the board level and at the management level,” said Thickins. “How does one collect data, cleanse data, and use it to make better decisions? That could be loyalty programmes, customisation of baskets, or managing supply chains for convenience and value.”

Resources vary by size of GP. Blackstone employs 50 data scientists as part of an offering that leverages the breadth of its holdings, including teams that negotiate portfolio-wide procurement contracts and encourage cross-selling between companies. Australia-based Adamantem Capital has three people working in operations and another three responsible for environment, social, and governance (ESG).

Nevertheless, the language of value creation is much the same. Initiatives are tailored to the nature and complexity of the targets, and given Adamantem’s mid-market sweet spot, companies are more likely to be relatively early in their digitalisation journey. Georgina Varley, a managing director at Adamantem, highlighted the technology investment in local land-based carbon offsets business Climate Friendly.

“There are some highly scientific aspects to what they do in terms of taking GIS [geographic information system] mapping and satellite data. We’ve automated a lot of those processes and trained algorithms to read satellite imagery, so they are better able to identify projects with the highest likelihood of being successful,” she said. “From a sourcing perspective, that saves a huge amount of time.”

Accumulating insights

The private equity firm also implemented data analytics with Retail Zoo, owner of food and beverage brands such as Boost Juice and Betty’s Burgers. While Boost Juice relies on franchise arrangements, Betty’s is rolling out directly owned stores. Demographic and consumer traffic data, including the use of mobile phones to track movement in shopping centres, helped identify optimal restaurant locations.

Adamantem is not alone in making data integral to value creation in casual dining. The success of McDonald’s China under PE ownership is built on maintaining robust same-store sales growth while doubling the store footprint and the introduction of apps and loyalty programmes that have simultaneously pushed digital sales to 90% of total sales and turbo-charged the delivery business.

Carlyle – which agreed an exit last November, putting the firm on course for a 6.7x return – deployed its global portfolio solutions team to help develop middleware. This contributed to an omnichannel digital solution that drove huge customer penetration, according to Geoff Hutchinson, the private equity firm’s head of private equity for Australia and New Zealand.

“Doing that, you have a great understanding of the customer, you can have very targeted offers, and you get much better engagement, more frequent consumption, and bigger ticket sizes,” he explained. “The digitalisation of the customer experience is incredibly powerful.”

Affinity Equity Partners followed a similar digital playbook with the Burger King master franchises in South Korea and Japan. Nick Speer, head of Australia and New Zealand at the firm, observed that digital transformation is a feature of 90% of its portfolio companies across the region – in part because of a tendency to invest in business models that are more traditional in nature.

Scottish Pacific, an Australia-based non-bank lender, is a prime example. Affinity helped elevate a predominantly paper-based operation into the cloud, creating fully integrated digital platforms that have shortened approval times for credit applications and contributed to a 10% jump in operating margins.

“We are now using data analytics and AI to scan the book and identify potential issues,” said Speer, noting that digitalisation has enabled the business to double in size with only incremental additional headcount. “It is also enabling us to think about cross-selling opportunities. We have multiple products we can sell to SMEs [small and medium-sized enterprises] and data analytics can pick that up.”

All about AI

Bain & Company identified three main ways in which private equity firms are mobilising AI: gaining insights into how companies and industries might be enhanced or disrupted by these technologies; sharpening and speeding up due diligence processes; and expanding the scope of information use at the firm level, which can impact investment decision-making as well as back-office functions.

EQT was a relatively early mover in machine learning and AI, spinning out a dedicated unit – known as Mother Brain – from its digital operations team in 2016. Frank Heckes, a partner at the firm, described an evolution in usage from internal customer relationship management platform to venture capital deal-sourcing tool to enabler of private equity bolt-on acquisitions.

“At Icon Cancer Care, [an EQT portfolio company in Australia under the core-plus infrastructure strategy] we have used it to try and help identify novel drug technologies that are relevant to oncology treatment and then we have looked to build partnerships for Icon with those companies,” he said.

Mother Brain is now using large language models (LLMs) to identify companies that fall within EQT’s core sectors, according to an October 2023 blog post based on a master’s thesis by one of the firm’s machine learning engineers. Mapping companies to sectors largely relies on analysis of unstructured text – names, business descriptions, keywords – that is fed into a machine learning solution.

Carlyle is also experimenting with LLMs as an early and significant user of ChatGPT Enterprise, a service launched by OpenAI that offers unlimited high-speed access to GPT-4, the LLM behind ChatGPT, and the comfort of doing so insulated from any data-sharing protocols.

“We have a whole programme developing those tools to be able to better utilise the knowledge across the portfolio,” said Hutchinson. “It is used internally as we think about the insights we can draw from that in doing deals and making investment decisions and it is used to create tools through which portfolio companies can access information and improve different functions of their business.”

Fixing the unfixable?

In its analysis of potential use cases, Bain & Company stressed that generative AI doesn’t create value by itself, but rather “by linking explicitly to pragmatic business objectives.” As such, scattershot initiatives are unlikely to make much impact on a company’s bottom line. The best approach is to employ a series of use cases targeted at specific roles or processes and tie those to desired outcomes.

Investors, for their part, are wary of employing AI for the sake of it. TPG’s Thickins compared the situation to the dotcom boom when “Do you have a website?” was the oft-repeated question. “The website isn’t really the right question,” he argued. “It’s how you are engaging with customers and how does this lead to better outcomes.”

Insights into the transformative potential of cutting-edge technology are useless in an investment context when applied to a poorly chosen asset or in the absence of a strong value creation plan. Investors at the forum alluded to an array of situations where multiple systems have created operational havoc and technologies have failed to transform business models that were broken in the first place.

“The starting point needs to be getting the basics right and thinking about how you use technology as an overlay into that,” said Carlyle’s Hutchinson. “With the tools available, and the speed at which you can develop new tools, there’s a lot you can do.”

For Affinity, it comes back to a fundamental awareness of what is being built and for whom. This involves identifying likely buyers during the underwriting process and factoring that into the investment thesis. With economic conditions making growth harder to achieve, going into deals with a clear idea of what can be done from an operational perspective and how it might pay off becomes even more important.

“We think most businesses have 10, 20 growth opportunities available to them, but if you try to do them all you probably won’t do any of them well,” said Speer. “We are very big on focus, and we spend a lot of time talking about what not to do.”