In the world of finance, the more investors know about an asset, the greater their competitive advantage. Data science has taken this relationship to new levels.
By Sandra Gittlen
Sajjad Jaffer was working on an investment thesis, looking for an edge through academia. The thesis focused on private equity value creation, through top-line growth, not from traditional cost-cutting. Jaffer WG01 was coming to understand that the increasingly quantitative role of the chief marketing officer needed to be better aligned with the financial bent of investors and CFOs. In short, he wanted to connect the dots between marketing and finance. After an extensive search, he found his edge in the research of Peter Fader and Eric Bradlow W88.
For 25 years, Fader and Bradlow had been espousing potential real-world applications for their unique analytics and statistical models to predict customer lifetime value (CLV)—in particular, for corporate valuations for companies in the marketing science business.
Jaffer shared the research with his classmate Ian Picache WG01. It resonated with him because most of Picache’s investments during years in venture capital and private equity were in companies where understanding customer lifetime value was critical to the success of the business.
“Ian and I were convinced there was a pony here, and started building a team of data scientists through the Wharton network,” Jaffer says, adding that their first hires were Pete and Eric’s loyal student protégés. “We pretty much bleed red and blue over here,” says Picache. Out of the firm’s 11 full-time employees, seven come from Wharton’s Ph.D., undergraduate and MBA programs (another is an astrophysicist from Penn).
Jaffer and Picache founded Two Six Capital with a vision to transform investing through data science. Named for the birth date of Picache’s first-born child, the firm has achieved significant momentum in private equity in a short timeframe. Over the last two years, Two Six Capital has participated in $10 billion worth of private equity transactions, including some of the largest buyouts of 2015.
As Fader put it for an article on the Wharton Magazine website, “[They are] putting serious money where someone else’s mouth was.”
Two Six’s models use a company’s historical customer, product and channel data to validate its valuation, project future value, and identify opportunities for reorganization and growth. For instance, Two Six Capital can determine which customers are worth retaining and how well certain products and channels are performing. When millions, if not billions, of investment dollars are on the line, having that kind of insight creates a true competitive advantage, according to Jaffer.
“What Two Six Capital has done is recognize that whether you have 100 customers or 10 million customers, you make profits one customer at a time. In today’s data-rich and fast-computing world, this philosophy is monetizable, and Two Six Capital is using state-of-the-art methods to accomplish it,” says Bradlow, the K.P. Chao Professor, vice dean of Wharton’s Doctoral Program and co-director of the Wharton Customer Analytics Initiative.
“We take transactional data resident inside the business and ingest it into our platform to find out how this business has made money until now and where the opportunities lie for the future,” Picache explains.
The proprietary analytics platform, which has analyzed over $20 billion in individual transaction data across a range of industries to date, has the capability to analyze hundreds of millions of rows of data overnight. It’s been purpose built for diligence and value creation, the co-founders explain.
BIG DATA IN ACTION
At its heart, Two Six’s concept is relatively simple.
“We are able to say what a customer will do and for how long, using a minimal amount of data,” says Fader, who serves as Wharton’s Frances and Pei-Yuan Chia Professor and as co-director of the Wharton Customer Analytics Initiative with Bradlow. “That is far more valuable than the quick and dirty calculations most companies give you.”
The goal of the analysis is fourfold: to understand customer growth; customer quality, including where customers originated and their spending habits; product quality; and channel quality. This “inside out” data-driven process can be a powerful complement or alternative to traditional methods, including surveys, interviews, benchmark studies and gut intuition.
Value creation has become the critical component of generating outsized returns, raising the importance of analytics across the entire investment process, Jaffer and Picache say. The Two Six platform allows private equity investors to see the “value creation roadmap” before a deal occurs, they claim. During diligence, investors, banks, lenders and ratings agencies understand which customers or product SKUs should be treated as stable bonds and which ones should be priced as options.
After an investment, Two Six’s approach can be embedded in driving operational improvement in portfolio companies. Typical improvements include sales and marketing, finance and budgeting, operations and supply chain, category management and merchandizing, and research and development.
As you might expect, Two Six Capital can also get involved when private equity firms are ready to sell a portfolio company.
“We can see the path to substantiating a price and driving returns,” Picache says. “Our benchmark is whether we helped a company grow faster and become more profitable. Do we have a clear understanding of who the best customers, products and channels are and where the best return is on marketing dollars?”
To test their models early this year, the Two Six Capital team analyzed projections they made on a 2013 investment. The models came up 99.5 to 100 percent accurate in terms of predicting customer behavior—“a huge validation of our crystal ball,” Picache says.
Fader adds that, over time, the analysis and resulting actions will only get sharper because private equity firms can start to see similarities among companies and therefore implement repeatable processes.
“You can benchmark and cross-learn the industry in a really rich way,” he says.
“Basically any company with any one of the following: lots of customers, products or channels,” adds Picache, pointing to the variety of applicable industries, like retail, media, technology and industrials.
Yes, Data Is Everywhere
Data analytics already plays a major part in investing. It helps maximize return for a given risk level or minimize risk for a given expected return. Today, new types, such as trading based on artificial intelligence programs, may move quantitative techniques closer toward the center of intelligent investing.
Such were some of the insights shared by Chris Geczy, an adjunct finance professor who has the privilege of studying the intersection of theory and Wall Street as director of both the Wharton Wealth Management Initiative and the Jacobs Levy Equity Management Center for Quantitative Financial Research. Geczy teaches a quant finance course that he describes to his students as “there is no such thing as non-quant today.” Instead, finance exists in a world where analytics promises (or threatens) to replace financial advisers. Where regulators, lawmakers, academics and executives are attempting to map connectedness across entities, market participants and scenarios to see how the world of finance is connected in ways not visible to the naked eye. Where practitioners apply data to the soft side of consumer opinion and other psychometrics.
He envisions a wide spectrum of ways in which analytics is going to be connected “symbiotically” to users. To allow them to cut through the noise of data that exists today. To overcome natural human tendency to reduce explanations to what is understandable to us. And to create very bespoke ways to make more money. “If a firm is not using analytics, then they should be worried,” he says.
A CAPITAL IDEA
Like Jaffer and Picache, another alumnus has tapped into models from the Fader and Bradlow braintrust. Marc Utay W80 WG81, managing partner at Clarion Capital Partners LLC, a private equity firm focusing on the lower middle market for business and health care services, media and entertainment, and consumer, uses analytics to help winnow pools of prospects. He first learned of the professors’ work from his son, who took a class from Fader while he was at the University of Pennsylvania.
“I could see the applicability of his work to businesses we were investing in,” Utay says of Fader.
Analytics enables Clarion Capital to either gain some insight that will change its view of the value or to identify what can be done with the business that someone else might not see. Traditionally, investors look at a company’s average customers and, if the business has a catalog or online business, review how many people come to the website, how many are converted to customers, how many pages were viewed, how many started to check out and how many units were ordered. With Fader and Bradlow’s model, investors can look at the customers individually rather than the averages, Utay says, and sometimes the conclusions drawn about the company’s worth can be “profoundly different.”
For instance, a few summers ago, Clarion considered investing in a fantasy sports betting site. “It was a terrifically run company and was highly analytical,” he says. Utay looked at the daily betting pattern for 30,000 people over the previous 18 months. He then took a subset of that data and parsed it using the Fader/Bradlow methodology.
“What we believed by the end of our analysis was that the company’s view of its lifetime value actually was understated,” he says. “That allowed us to be competitive, and we were in the bidding until nearly the end.”
Investors often find corporate valuations to be ridiculously high, and it would take five years of data to gain a real history. With Fader and Bradlow’s analytical techniques, Clarion is able to draw conclusions earlier, providing a competitive advantage.
Utay says he has to be discerning in where he points the analytical tools because the lower middle market is notoriously lacking in strong, clean and useful data, and the time it takes to do the analysis can inflate deal costs. Each year, Clarion looks at 300 to 400 opportunities that result in three or four deals. Although he would like to someday have a hybrid analytics model that can be used in initial screening, right now he has to be more discriminating. Therefore, Clarion uses traditional analysis to trim the field to 25 opportunities ready for a deep dive and even then, if the company doesn’t have good data, then it wouldn’t be a candidate for the methodology, which is best used on highly transactional businesses such as retail.
BEYOND THE TANK
Utay says the value of analytics doesn’t stop once the ink dries on the deal. Instead, he uses the insight gleaned during due diligence periods to figure out hiring needs, product direction and more. The model that Fader and Bradlow created can generate a unique perspective on how private equity firms should direct companies to spend their budgets. For instance, knowing details such as the likelihood of a customer to leave and how often customers are renewing a subscription guides marketing spending decisions. In fact, Clarion organizes all of its learning about the company or its market from the due diligence phase and prepares a detailed deck for target companies. Clarion finds that sharing this information with the entrepreneur accomplishes two purposes: first, the entrepreneur can effectively critique the analysis and identify where nuances in the marketplace could lead to slightly different conclusions; and second, it creates an opportunity to have a strategic discussion with the entrepreneur about where the market and company are heading.
“People question why we would open the kimono to someone we have to negotiate with. It’s simple: We gain a lot more than we’d lose,” he says. “I’ve never met an entrepreneur that didn’t know more about the business than we do, so maybe they can challenge our conclusions due to nuances we might have missed. Together, we get smarter.”
Also, Utay explains that sharing information creates a better relationship and could save money on the deal. “We have four companies currently in our portfolio where we were not the highest bidder,” he says.
In one instance, although a deal wasn’t struck initially, a company took the advice laid out in Clarion’s deck and implemented change. Later, when the company again was looking for a partner, Utay considered it a signal that the company would be a great fit.
Although he acknowledges that everyone in finance uses some element of analytics, he does not feel many are doing it the way Clarion does.
“We are often the only ones asking for the data we need to do the analysis,” he says.
Fader foresees analytics soon being an integral part of the evaluation process for many private equity, hedge fund and venture capital firms.
“This group of companies is looking for every angle and edge and source of value,” he says. “With analytics, that edge is right there in front of them.”
—Sandra Gittlen is a freelance technology and business writer in the greater Boston area.