Private equity firms are always looking for ways to maximize their returns on their investments. Turns out data science is the newfound weapon in the hands of the firms to maximize their returns.
Data science has been a buzzword in the industry for some time now. What’s new, it is now used in private equity as well. Investment banks and hedge funds have been using data science to propel their business. Now private equity funds have turned to data science to win deals and help them manage portfolio companies post-purchase. Among the U.S. top private equity firms, Blackstone is leading the way in using data science to further its private equity business.
According to Lionel Assent, Head of European Private Equity at Blackstone, the fund now has 14 data analytics professionals, grown from zero to five, in the last five years. The emphasis on data science to generate more business is increasing among private equity firms. A few deals demonstrate the application of data science
The fund bought Packers Sanitation Services Inc., an American company, in 2018. Blackstone’s analytics team collected thousands of pieces of data on the company’s potential clients. The data helped the management team swing the deal.
Blackstone now has a large pool of data analytics professionals. The private equity firm counts former Barclays and Goldman Sachs technologist John Stecher as chief technologist officer and former Credit Sussie Strategist, Mathew Katz, head of the data science team. The team includes data scientists hired from McKinsey & Co., Millennium, and Cerberus.
Cerberus, another private equity firm, has Len Laufer, former head of J.P. Morgan’s intelligent solutions as head of the data team. Benjamin F. Sylvester III, another former JP Morgan Intelligent solutions Specialist, heads the global analytics team. John Tang, a former chief data scientist at Barclay’s UK Information business, is another addition to the global data team.
The data team at Cerberus helps its portfolio companies to conduct an exploratory analysis of potential markets and building forecasting models.
Data analytics, like for any other business, is proving to be an essential instrument in transforming private equity business. Data analytics is mainly useful for private equity funds in the following three use-cases.
1. First, in finding potential companies for investment
2. Second, to perform due diligence
3. Third, to improve the performance of portfolio companies
These are the three areas for which private equity firms are seeking data analysts. Interest in data analytics is increasing among private equity firms, suggests, Adam Braff, a data and analytics consultant, former managing director, and chief data acquisition officer at Point 72, a hedge fund.
It is not surprising that data analytics is used to improve the performance of portfolio companies. As the performance of portfolio companies becomes increasingly crucial to the success of the firm, data analytics will gain more domination in the private equity industry. Work needed to generate returns in the high returns in significantly more than it used to be.
Managing portfolio companies is a significant function in the daily business functions of successful PE firms. Consequently, Blackstone boasts of a large operations team. The firm has a team of 50 operations professionals, comprising ex CEOs and functional experts. Further, procurement experts are crucial to the success of portfolio companies. Blackstone’s procurement team saved as much as $180m last year. Data analysts had a similar effect on the business. PE firms should have a strong operating function to compete in the current PE market, Assent suggests
