For private equity firms, data insights hold the key to future value

 Private equity (PE) CEOs should be heartened by some of the findings in PwC’s latest Global CEO Survey. Across all industries, 45% of CEOs say that their company won’t be economically viable a decade from now on its current path, but only 31% of PE CEOs say that. Moreover, prospects are getting worse for other industries but getting better for private equity. In last year’s study, 39% of all CEOs—and 38% of PE CEOs—said that their company wouldn’t make it 10 years on its current path.  

Yet there are still some factors that keep PE leaders up at night. Interest rates remain high, meaning that private companies can no longer rely on cheap capital to fuel returns. What’s more, technological change is relentless: 42% of PE CEOs say it will drive business model change in the coming three years.  

One area where PE has a real opportunity? Generating insights from the wealth of data in their portfolio companies. PE funds are already good at improving operational and financial performance. They make their living by increasing efficiencies and wringing out costs. But data remains an untapped asset, with many firms struggling to operationalize it and drive smarter decision-making.  

Those that can make sense of the data they have access to—establishing the firm as a data and technology platform—can process business intelligence in near real-time, using AI to generate insights in applications ranging from customer engagement to capital allocation. They can also reduce costs by eliminating redundant data platforms.  

Moreover, because firms often buy multiple players in the same industry, they can potentially bundle that, giving them a big advantage over individual companies with smaller data pools. In that way, data mechanics becomes a repeated value lever, with funds becoming more effective at managing portfolio companies. They’re no longer waiting for information to come in; instead, the fund provides the know-how to automate data flows, along with tracking and governance.   

Building a successful data platform can materially change the valuation of what portfolio companies are worth, provided that PE firms can overcome two main challenges.  

The first is consolidating data across portfolio companies, with the goal of improving that data quality, along with operations and decision-making at each portfolio. To achieve this, firms need to pull different information from different places into a single source of truth, incorporating insights about finance, customers, production, and other aspects of the business. Firms then need to bundle that data across multiple companies in the portfolio. Once data is consolidated, firms can build foundational models that encode the dynamics of the markets in which they operate, then run analytics to accurately predict future changes in those markets. Coupled with AI, these models will enable firms to use accelerated data streams to grow revenue and operational efficiency.   

The second major challenge is governance—putting the right guardrails in place over how that data is used. Firms will need to maintain customer privacy, along with addressing issues that arise when portfolio companies are bought and sold (something that PE firms do all the time). With the right governance in place, firms can share data among entities but still control access between the fund and the portfolio companies, with established mechanisms that don’t allow replication and won’t expose sensitive information to the wrong party.  

When firms get these two elements right, they can unlock meaningful value. To see what’s possible, consider a PE-owned manufacturer of car components. The company sells to major retail chains, and it needed to better understand how to allocate its products among those customers.  

The company started by aggregating data up and down the supply chain—inventory data, logistics, production, finance, legal (such as customer contracts) and other factors—into a single database that leaders could use to make smarter decisions. Based on that data, the company was able to take several steps: 

• The company started prioritizing orders across its most important customers based on the true cost-to-serve, factoring in transportation, production, and penalties for stock-outs.  

•  Management rebalanced inventory to reduce holding costs while still meeting service level agreements.  

•  The company renegotiated customer service expectations and order policies to reduce demand volatility.  

• Based on more reliable arrangements with suppliers and customers, the company was able to make its forecasts far more accurate.  

Together, these measures had a significant impact on the bottom line. The company reduced its working capital by more than $50 million, boosted revenue by $115 million, and reduced costs by $42 million. That’s an overall impact of $200 million, based on information the company already had on hand.  

That’s a powerful example, but also a rare one—most PE firms aren’t as advanced in their ability to harness data and improve the performance of their portfolio companies. Firms are moving in that direction, but the ones that recognize the potential and take steps to capitalize can separate themselves from the pack. They can become leaders in translating data insights into value.   

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