Private Equity Extends the Data Science Value Prop to the Portfolio
TZP Group shares its experience creating a new role to enhance data analytics across portfolio companies.
As with so many other industries engaging in digital transformation, private equity firms are embracing the opportunity to unlock value from the data analytics discipline.
Increasingly, PE firms are taking a data-driven approach to deal sourcing, due diligence and financial strategy. Now, some sponsors are exploring how to apply the value they’ve realized in-house from data analytics, and extending it to their portfolio companies to fuel growth.
One of them is TZP Group, a private equity firm targeting the lower middle market. The firm recently announced that Tamar Shapiro, has joined the firm to fill a new role that TZP created within its Portfolio Operations Group: partner of data & analytics.
“It was exciting for me to come into a firm that specializes in the lower middle market, recognizing that these portfolio companies are sitting on treasure troves of data, and could be doing so much more with it,” Shapiro tells Middle Market Growth. “I wanted to take my experiences to help them advance in their data and analytics.”
Portfolio companies are sitting on treasure troves of data, and could be doing so much more with it.
Tamar Shapiro
TZP Group
PortCos’ Data Science Opportunity
Virtually every business across industries can benefit from a robust data analytics strategy, whether it’s to forecast cash flow, manage inventory or fuel product development.
For private equity firms, data analytics is an increasingly critical component of operations. In a 2020 survey by EY, the majority of private equity CFOs reported plans for their finance teams to spend more time on investment portfolio analytics in the coming years, while 56% reported capturing a measurable ROI on their data management technology investments. Most (56%) also said they are either using or expect to use next-generation data and analytics tools within the firm.
As private equity firms grow more comfortable deploying data analytics strategies internally, some are finding that they can also help their portfolio companies embrace data science to fuel growth and success.
For TZP, establishing the role of partner of data & analytics will see Shapiro working directly with portfolio companies to optimize their own data analytics strategies.
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According to TZP Group partner Dan Gaspar, just about every company within the firm’s portfolio, including B2B and B2C businesses, stand to benefit from Shapiro’s experience, which includes leading analytics strategies at Instagram, Foursquare and American Express. But there are a few key verticals where the firm expects to see the most dramatic impacts from this effort.
“We believe that data science will have applicability across our entire portfolio, but If I had to pick an area where it can really move the needle very quickly, it would be with our investments in direct-to-consumer brands,” Gaspar says. “Those businesses have a trove of data both on their specific product offering and on consumer trends at large. Developing processes to apply that data to improve target advertising, or to optimize pricing, or develop new products, are really interesting areas for us to pursue.”
Shapiro adds that while the D2C arena indeed has significant potential, she also finds it fascinating to explore with portfolio companies across industries the unique ways to apply a data science strategy.
“I think it will touch each of them a bit differently,” she says.
Where to Start
Deploying a dedicated data analytics expert to work directly with portfolio companies is an area of significant potential for private equity firms, considering many lower middle-market businesses struggle to independently deploy a data strategy.
Shapiro and Gaspar agree that simply knowing where to start can be a significant hurdle for many companies. According to Gaspar, there must be discipline around the data collection strategy, as well as the way that data is organized, in order for companies to be able to identify areas of potential value within the data they hold.
But the difficulties don’t end there. Shapiro highlights the struggle that lower middle-market companies endure to access the right talent and resources to deploy their data strategy.
“Data science and data engineering talent is hard and expensive to attract and retain,” she notes. “Most companies don’t know where to start, or what kind of team they need to tackle the problems that are most important to their business, let alone how to get that talent in house.”
Partnering with a private equity investor can help these businesses overcome resource constraints. Access to the right tools and expertise continue to be essential as businesses grow, particularly following M&A activity when it becomes essential to overcome data silos and merge those data “treasure troves.”
Related content: The Importance of Data Quality for Private Equity Deal Teams
Gaspar says he expects more private equity firms to follow the trend of prioritizing a data analytics strategy for portfolio companies, pointing to this strategy as “the way of the future.” But, he acknowledges, it will take time—and a bit of experimentation—to capture the most impactful opportunities for each individual portfolio company’s needs.
As more private equity firms embrace data analytics within their own operations, though, Shapiro expects more sponsors to extend the lessons they learn across their portfolio.
“What has made PE firms successful to date is different than what will make them successful going forward,” she says. “In a world that is so heavily dependent on data and technology, I believe this is something every PE firm should be investing in.”
