How using data analytics in private equity can better inform portfolio strategies in a downturn

The potential for a recession holds significant implications for even the private equity market. Financial giants with their own private equity arms, such as Blackstone, have already cashed out of deals to ease the pain of major write-downs and their resulting losses, while the Federal Reserve’s continued war on inflation means lending costs will continue to increase. 

Leveraging data can help. By connecting people, processes and technology, private equity firms can maximize their portfolio companies’ value. Still, not all dealmakers add data analytics capabilities to assess portfolio performance in real-time. 

Many portfolio companies are hunting for new sources of data monetization as we head into 2023.  By taking advantage of underutilized data sources and lucrative cross-sell opportunities, private equity firms can help their portfolio companies make decisions based on quantifiable revenue—rather than the potential for revenue—while still preparing for a downturn. 

Leverage indirect data monetization 

Operating partners should look at their internally focused strategic initiatives and ensure that they are data-driven. The following steps will help craft an indirect data monetization strategy—an approach using data-based insights to improve internal processes—for each portfolio company: 

Use data to understand your customers 

To improve company-wide decision-making, first map out customer behavior: when to put the right information in front of a particular user at the ideal time to spur a desired action—like the purchase of a product or service or downloading software. By getting a more holistic picture of their customers’ preferences, private equity firms will be able to act on these metrics and make decisions that reinforce long-term profitability. 

By knowing their customers inside and out, private equity firms can also focus on deepening their relationships with the customer segments that are most valuable to their portfolio companies. For instance, before making a major business decision like reducing a company’s workforce, data will show which customers will be most affected—allowing firms to plan accordingly. 

Understanding what customers are willing to withstand is critical, especially in an environment where new customers may not be coming in. Private equity firms can leverage customer feedback and sentiment data to explore whether adjusting prices on popular products, or even adjusting package size (if the company sells physical products), is a feasible way to boost organic growth. Giants like PepsiCo have employed both strategies to great financial success and little pushback from consumers. As a result, the company has raised its revenue forecast twice in the last two quarters even with a rise in production costs. 

Find opportunities for cost-cutting 

Data analysis can also shed light on customer-facing processes that can be automated or streamlined using a low-touch, digital-first approach, (e.g., online chat bots or streamlined movable apps.) By leveraging learnings about a portfolio company’s customer base, private equity firms can determine whether its customers will accept a lower cost approach to customer service. 

For one software provider, we discovered that as much as 60% of its customers could be moved to a digital-first customer success approach, lowering organizational costs while freeing up talented employees for higher value work.  

Identify low-performing product segments 

Using data can also enable private equity firms to identify product segments that can undergo product rationalization––the evaluation of products that may bear unnecessary costs and fail to assist an organization in meeting its strategic goals—with minimal impact. Companies in the industrial sector have long adopted this approach with high levels of success, deploying a stock keeping unit (SKU)-based model that populates cost of inventory, stocking, or manufacturing through inexpensive, scannable codes. Companies held by private equity firms may benefit from a similar product management system.  

Employ direct data monetization 

What can private equity firms do with data that has already served its purpose or seemingly holds no value? They can unlock a new revenue stream by packaging that data in a way that holds value for third-party organizations. The market for data monetization is already far-reaching—its value is expected to grow from $2.9 billion in 2022 to $7.3 billion by 2027. Jumping in now can prove lucrative for private equity firms while presenting little opportunity cost or disruption. 

Look for your ideal data consumers 

The initial search for third-party data purchasers doesn’t have to leave private equity firms’ current ecosystem. In fact, industry-adjacent partners are the ideal springboard. Dealmakers should sift through their suppliers, their suppliers’ customers, and even their own customers’ customers to source potential strategic partnerships.  

Learn how to best package your data 

Define what value these partners can extract from their portfolio data, how to deliver the data itself, and how to price it. In most cases, they should collaborate with a digital consultant to ensure they are maximizing their data’s potential. 

Target big data consumers  

Consider hedge funds alongside the suppliers and customers in their current ecosystem. To snag an incremental edge in their investments and an alpha risk ratio, hedge fund managers are constantly trying to track discretionary spending for individual products all over the globe. 

By analyzing that data over time, hedge fund managers can make smart decisions related to foreign exchange, hedging, and spending forecast development before consumer spend reports arrive. This means they have a significant incentive to purchase vast quantities of consumer data. 

Cross-sell into your customer base 

Leverage a company’s receipt and transaction data to identify value creation levers between companies in their portfolios. Here’s how they can start: 

Evaluate company sales history 

Taking stock in past strengths and weakness may generate greater value than dealmakers expect. In a recent engagement with a food manufacturer, we used the company’s sales history to identify over $80 million in cross-selling opportunities.  

Incorporate machine learning into data analysis 

In another client relationship, we leveraged machine learning to identify customers most primed for cross-sells––the company went on to capture $150 million in cross-sell revenue over the next year. 

Make data a fundamental part of your recession strategy 

In an economic slowdown, understanding your portfolio companies from a data perspective is critical to making informed investment and management decisions. 

There is no one-size-fits-all approach to value creation in a downturn, and private equity leaders need to understand their customers, along with their sectors, to prepare for a downturn––while also laying the groundwork for a bright future.