The private equity industry is just beginning to tap into the power of big data to evaluate potential investment targets and grow portfolio companies. “It is like it was in 1990 for public markets,” posits Ian Picache, co-founder of Two Six Capital, a San Francisco firm that is pioneering the use of data science in due diligence and value creation. “The use of big data techniques is nascent. It is only a matter of time before the private industry is disrupted. Just as the public markets saw the rise of massive quant hedge funds such as DE Shaw, Renaissance Technologies, and AQR, the same will happen in private equity. In the future, we expect big data to be heavily used in industry.”
“Data and artificial intelligence are necessary conditions for private equity today,” says J. Taylor Crandall, a managing partner and a founding member of Oak Hill Capital Partners, which began investing in 1986 as the family office for Robert Bass, one of four brothers who founded Bass Brothers Enterprises, based in Fort Worth, Texas. “Historically, the data wasn’t available. Businesses were run on visceral intuitions. Now, the data is readily available and exponentially created. Every time you click on the Internet, it’s creating data for somebody to analyze how to run their businesses better. Data analytics is the low-hanging fruit to create value in every portfolio company we own.”
Oak Hill engaged Two Six to analyze cohorts, or customers segments, for its portfolio company Wave Broadband, a regional broadband fiber company offering a full suite of high-speed data, video, and voice services to residential and business customers. The analysis yielded a bundle repricing that proved attractive to a group of customers and improved revenue growth, says Crandall. Subsequently, Oak Hill sold Wave Broadband to RCN Telecom Services LLC, a portfolio company of TPG Capital, for $2.365 billion in 2017. The sale price represented a multiple of 14x Ebitda, compared with the usual 10-12x Ebitda for a cable business, according to Crandall. To ensure that Oak Hill continues to reap the benefits of data science across its portfolio, Oak Hill is currently hiring a senior advisor for data analytics.
There are several underlying technology trends at play to enable the rise of big data, including enormous increases in computing power, cloud computing architecture and inexpensive storage. At the same time, “more and more data is being created every day, as companies increasingly rely on technology to scale and improve their operations, as consumers shift to a digital lifestyle,” says Sajjad Jaffer, co-founder of Two Six Capital. The methods to analyze data have also evolved significantly. “Statistical, artificial intelligence, and machine learning techniques are becoming available and take advantage of the technology infrastructure and availability of data.”
To leverage these trends in the context of private equity investments, Jaffer and Picache founded Two Six Capital in 2013. Since then, the San Francisco firm has served as an advisor to and co-investor with many respected global private equity firms, including Clarion Capital Partners, Francisco Partners and Oak Hill Capital Partners.
Both Jaffer and Picache earned MBAs at The Wharton School, University of Pennsylvania, and Jaffer serves on the advisory board of the Wharton Customer Analytics Initiative. Based on 25 years of intellectual property and research in data science, Two Six Capital’s technology helps PE firms understand past company performance and forecast future business drivers. The firm has analyzed more than $100 billion in granular transaction- level revenue data and has been involved in more than $27 billion worth of completed PE transactions, according to Two Six Capital. To harness the power of data science, the firm combines large-scale engineering, statistics, and machine learning to help investors unmask the intrinsic value of companies.
“We see big data as a board room agenda,” says Picache. “Two Six has developed a technology, process, and people-based playbook to drive operational improvements. The playbook has a broad range of applications across functions including marketing, sales, support, budgeting, R&D and operations. Just like ‘quants’ in the public markets, we can run large-scale iterative tests with management teams to make resource allocation decisions. Two Six can monitor and optimize portfolio companies using actionable dashboards that can be used to make board level strategic choices or tactical campaign-level management decisions.”
Big data in the due diligence process is used for two purposes, explains Jaffer. The first is to understand the target. “By unpacking the data, we determine the key business drivers of the company. These include: where the company is growing, what are the various customer segments, how are the customer segments changing over time. We can predict with a high degree of accuracy what near term (six to 18 months) revenue will be. This helps underwrite the base case and fundamentally improve risk adjusted returns.”
The second is to find value creation opportunities. “In analyzing the data, we see areas in which the company can be improved such as sales, marketing, budgeting, operations, and R&D,” says Jaffer.
The approach works best with businesses that have a lot of data and some repeat sales behavior. “This could be customer, product or channel data,” says Picache. “Generally, we look for 10,000 customers or higher; or 500 products or higher.” The approach scales to handle millions of customers and thousands of products, he says.
Clarion Capital Partners, a New York PE firm that invests in lower middle-market companies, met Two Six Capital through the Wharton Consumer Analytics Initiative. “We found Wharton’s groundbreaking statistical approach to projecting customer lifetime value highly relevant to our investment process in the consumer, media and entertainment industries,” recalls Clarion founder Marc Utay. He was impressed by Two Six Capital’s ability to handle large volumes of data. “Most private equity firms lack the know-how to do this analysis and candidly don’t even have computers which can handle these size data sets. Second, they tailored their industry investment insights based on our commercial diligence hypotheses. While the math can be outsourced, if you don’t have someone working on it that really understands the business, it is hard to make the conclusions actionable. Third, we saw the potential to incorporate the big data analysis into the day-to-day operations of the business.”
Traditionally, Clarion had evaluated consumer services and product companies through an analytical framework, comparing the lifetime value of a customer to the cost of acquiring a customer. “Whether it was for your cable TV service, your cellular service or a product which you would buy more than once, we always analyzed consumer behavior by grouping customers based on their period of initial purchase (cohorts),” says Utay. “In a world where you would reach your customers through general advertising (TV, radio, newspapers etc.), with an inability to track specific responses to specific media (the only real direct measurement of media efficiency was direct mail), you would just look at your total marketing spend divided by your number of new customers to calculate your customer acquisition cost and follow how that was trending.”
“The advent of large datasets tracking consumer behavior from initial contact through purchase and measuring engagement with the customer over their lifetime has fundamentally changed this approach,” Utay explains. “We now have a multiplicity of ways to reach the consumer (traditional advertising, targeted advertising, email, social media, etc.) and with many of these we can measure the consumer response directly. We can measure every touch point with that consumer leading up to a sale and track their business with us over a lifetime. This granular data allows us to analyze what media is most productive and which consumer activity is most predictive of a future sale.”
“Every business knows that a small portion of their customers are unduly valuable,” says Utay. “We can now identify these A+ customers and understand what attributes and activity, early in the consumer’s life, indicate that they’re likely to be one of the A+ customers. We can know which media is most effective to target them. In certain businesses, this can lead to a dramatically different answer on lifetime value. Using averages by cohort can obscure the true value of your best customers and lead to valuation or operating strategy errors. For example, online gaming (e.g. poker) and fantasy sports both have a small number of their customers that play a lot and account for a disproportionate amount of their profitability.”
With help from Two Six, Clarion was able to see the cohort dynamics of the business on a customer-by-customer basis, something that would have been “impossible even 10 years ago,” explains Utay. “As we unpacked the business drivers, the investment thesis in one case showed that the management team’s projections, which seemed initially optimistic, were in fact conservative. In a second case, we saw that the data was not mature enough to draw conclusions with any conviction and this ultimately helped abort what looked like a great investment on the surface.”
For Clarion, the deep analytics approach is now central to the diligence and value creation processes. “Unlike other firms that shield their investment insights from the target company’s management team, we take an open book, collaborative approach,” says Utay. “Our view is that the more we share with the management teams, the smarter we all get. By embedding Two Six’s analytics approach in the process, everyone benefits by identifying how we can collectively improve a deal from a 3.5x (our average) to a 5x return.”
Clarion and Oak Hill may be on the leading edge, but they are far from alone in trying to harness the power of data science. Ninety-four percent of private equity firms say they will use more predictive (applied) analytics within the next two years, and 83 percent are seeking operating partners with digital or technology expertise, according to Ernst & Young LLP’s Private equity Global Divestment Study 2018. “Unlocking portfolio businesses’ potential to benefit from digital and technological changes could be the key to securing greater value,” write EY’s Herb Engert and Bill Stoffel. “PE firms that exploit the power of data and analytics tools at every stage of the transaction process will be able to build a powerful value case for their most attractive assets.”