Data Scientists Key to Winning Deals at Blackstone

Investment banks and hedge funds aren’t alone in incorporating data science into their business models. Private equity funds are also turning to data science, both to win deals in the first place and to help them manage portfolio companies after a purchase. 

Speaking at the recent Alternative Investments Conference in London, Lionel Assant, head of European private equity at Blackstone, said the fund now has 14 analytics professionals, “up from zero five years ago.” 

Analytics teams can be instrumental in enabling private equity funds to win over management teams and do deals, Assant added. He cited the example of Packers Sanitation Services Inc. (PSSI), an American company that cleans food factories, which Blackstone purchased in 2018. Blackstone’s analytics team “aggregated tens of thousands of pieces of data” on PSSI’s potential clients: “The management team said it was awesome: Our data team helped swing the deal.”

Blackstone’s data science team is run by Matthew Katz, a former Credit Suisse strategist who joined from Point72 in 2015. Katz’ team includes data scientists hired from the likes of McKinsey & Co., Millennium and rival private equity fund Cerberus. Cerberus in particular is amassing a large data team under head technologist Len Laufer, the former head of JPMorgan’s intelligent solutions team; Laufer hired Benjamin F. Sylvester III, another JPMorgan intelligent solutions specialist, to head the global analytics team in 2018. Laufer, in turn, has hired the likes of John Tang, the former chief data scientist at Barclays’ UK Information Business. 

Profiles of former Cerberus data professionals on LinkedIn suggest the firm uses its own data analytics team to help portfolio companies conduct “exploratory analyses” of potential markets and build forecasting models. 

Adam Braff, a data and analytics consultant who was previously a managing director and chief data acquisition officer at hedge fund Point72, suggests that private equity funds everywhere are increasingly interested in data analysis: “There are three uses cases for data analysts in private equity… One is as a kind of screener function to work out which companies to talk to. The second is for due diligence: There is only so much data you can get from the inside, and it helps to understand things like market share. The third is to help improve the performance of companies in the portfolio.”

Improving portfolio companies has become increasingly important to private equity funds’ success. “The days of financial engineering are over” in private equity, said Assant, who added that the amount of work required to generate returns in the “high teens” is “significantly more” than it used to be. Managing portfolio companies is the work of teams of 50 “operations professionals” comprised of ex-CEOs and functional experts.”

Procurement experts also play an important role (Blackstone’s procurement team saved its portfolio companies $180 million last year). Same with the data analysts. “If you don’t have a strong operating function, you can’t compete in today’s PE market,” Assant concluded.  

A modified version of this article originally appeared on eFinancialCareers.