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Data Analytics Is (Slowly) Transforming Private Equity

Data analytics is one of the hottest areas in business these days. Companies are increasingly adopting it to transform human resources, sales and marketing, business development, operations and other areas, across a wide spectrum of industries. The approach holds the promise of more objective decision-making and a stronger bottom line.

But when it comes to the world of private equity it’s a different story, according to Sajjad Jaffer, co-founder of the advisory and investment firm Two Six Capital. He said that when he and Ian Picache started their analytics-based firm in 2013, there had been “no technological innovation in private equity since the invention of the Excel spreadsheet.”

Jaffer and Picache noted that Two Six Capital has pioneered the use of data science in private equity, and to date has been involved in over $27 billion worth of closed private equity transactions. They think of their company as “launching the next wave around data-powered investing.”

They delivered the keynote, “Pardon the Disruption: How Data Analytics Is Revolutionizing Private Equity,” at a recent Wharton Customer Analytics conference at Wharton San Francisco. Their talk was followed by a panel discussion by veteran private equity professionals from both general partner and limited partner firms.

What Two Six Capital does, Jaffer said, is understand and project a portfolio company’s revenue. There are two facets to this: transaction due diligence, or “understanding a business from the bottom up,” and value creation post-investment, which Jaffer characterizes as yielding “board-level insights … understanding how a portfolio company performs and then driving operational improvements.”

While other investment firms have similar goals, Two Six Capital’s self-described secret sauce is technology. “Using large-scale, cloud-based engineering we can handle very, very large data sets in very, very short timeframes. Billions of rows of data,” Picache said. He noted that their in-depth methods enable them to view “what is going on in a business in a minute-by-minute, day-to-day basis.” He compared this continual monitoring to trying to lose weight: If you really want to see results, you need to step on the scale every day.

He talked about the difficulty — for any investment firm — of accurately predicting a portfolio company’s growth, and how data analytics can change the game. “Right now in the industry, when most associates at a private equity firm go to sell [a company], they [just] put ‘12%’ in there. It is a relatively finger-in-the air approach,” he said. “But we — because we count every customer, every transaction — get a much more granular perspective.”

Jaffer and Picache said that Two Six Capital has pioneered the use of data science in private equity, and to date has been involved in over $27 billion worth of closed private equity transactions.

Two Six Capital uses about 28 standardized analyses and 18 statistical machine learning models to understand data, according to Picache. These tools are like paint colors that enable the company to create a picture of a business, he said. “We can figure out … is this business doing well [or] badly? Are there opportunities to change things?”

They come to their conclusions fast, Jaffer said, asserting that speed is one of Two Six’s competitive advantages. “In commercial diligence you’ve got four to six weeks to make a go/no-go decision on the deal. [We can] take in large volumes of data, and quickly come up with a point of view on [the question], ‘Is this company going to make returns — yes or no?’”

Regarding value creation, Jaffer and Picache said Two Six tries to introduce new skillsets into the management team to grow the business and drive the culture. That culture should include an almost “maniacal” focus on monitoring data. Jaffer noted that in addition to working across the entire spectrum of the private equity cycle, Two Six now offers vendor due diligence: helping companies position themselves for sale.

The two speakers said they have worked with a broad range of industries across the globe, citing, for example,Citigroup, Pet Circle (an Australian e-commerce retailer), and Allegro (a major Polish online marketplace). About half of their business is outside the United States, with 40% in Europe and 10% in the Asia-Pacific and Latin America regions. Forty-five percent of their work involves consumer retail.

Finding the Disconnects Through Data

Jaffer and Picache discussed how using data can reveal insights that topple conventional wisdom. Picache gave the example of a business that operated in 122 countries. Two Six modeled out all the countries, and as might be expected, each country had a different level of market penetration. In one particular region that was seen as critical to the business, Two Six Capital was working alongside Bain on the transaction. “Bain said that Region A was … a mature market, lots of competitors in the space; it’s not going to grow very much.”

Bain’s argument made a lot of sense, said Picache. But when the team actually examined the data, a different scenario emerged. “The data showed that we were at the beginning of a growth trajectory and that the growth trajectory was going to persist,” he said. “Because we time-stamp every single time a [new] customer comes into the system … we knew that the velocity at which customers were entering … was accelerating.”

Picache said Two Six Capital’s prediction turned out to be correct. Region A was the engine of the business, experiencing 100% growth last year.

Of the experience, Picache commented, “We love [to find] things that don’t seem to make sense [at first glance],” because those disconnects lead to deeper insights.

“In commercial diligence you’ve got four to six weeks to make a go/no-go decision on the deal. [We can] take in large volumes of data very quickly, and quickly come up with a point of view….” –Sajjad Jaffer

Jaffer and Picache talked about the critical importance of having a strong team around them. Jaffer said Two Six Capital has brought together skillsets that “have never coexisted under one roof,” including private equity domain expertise, consulting expertise, and data scientists and engineers backed by Ph.D.-level research. He said these kinds of scientists and engineers would typically be found at a Google or Facebook. “They are bringing a very different capability to this industry that frankly hasn’t been done before.”

Picache added, “One of the challenges [in our business] is the people. If I look at all of the guys on my team, they are all unicorns … it is one of the most difficult skillsets to hire for.”

GPs and LPs Weigh In on Data Analytics

In the panel that followed Two Six Capital’s keynote, a private equity investor echoed both the importance of data analytics in private equity and its relative novelty in the field. He noted that many investment firms for the past 15 years have been using Salesforce, but that it has limitations. The investor said that while Salesforce is a great company, “unless you are integrating a lot of data analytics and data layers on top of it, it’s just a place for logging companies and data as opposed to really adding any… data intelligence.”

Regarding portfolio management, he said that a management team’s own attitude toward data tells you something about their company. “Those that actually resist [data analytics] should actually raise some alarm bells for you…. Is it a point of pride? Are they trying to get the highest valuation for their companies by not showing you the full transparency of data?” Instead, “the management teams that embrace analytics are those that you want to back.”

Jasper Ridge managing partner George Phipps said he is beginning to see private equity firms do just that: Gravitate toward portfolio companies that exhibit an ability, or capacity, to support data analytics. Furthermore, limited partners are starting to judge general partners by their savviness about data analytics.

Marc Utay, managing partner at Clarion Capital since its founding in 1999, was asked how he has seen things change in private equity over the past two decades. He noted that the industry’s use of data analytics is “pretty nascent.” He added that one factor slowing down its adoption is that private equity can be a low-velocity business; for example, his firm does just two to three deals a year, he said. So while Clarion has a sophisticated algorithm to rate firms, seeing the results of their assessments takes time. “Come back and talk to me in 10-15 years and I will tell you how good our algorithm was.”

Utay also noted that “intellectually, I don’t think there has been a huge change. We always did cohort analysis,” he said, meaning that they grouped a company’s customers by similarities to understand their behavior and to project growth. Nevertheless, Clarion has been moving more toward data analytics in the past few years because “the tools … and the availability of data have changed dramatically.”

He talked about the new capabilities for assessing consumer businesses. “We can literally follow [customers] in our categories, everywhere you go around the internet, and understand your path to making a decision. And that is an enormously powerful thing [that] has only been available for the last few years.” He said these kinds of tools, while not yet widely adopted in private equity, have the potential to “upend everything.”

“The management teams that embrace analytics are those that you want to back.”

Utay noted — as did Jaffer and Picache — that having knowledgeable talent in data analytics is a big factor in its successful application. This could be a problem especially for smaller companies with fewer resources, he said. “The challenge in our business is, do we really have the people in place that can actually absorb and use some of these tools?” Simply “hiring a smart guy in data science” isn’t really going to address that, he said.

There was some question among the panel as to whether the world of private equity would ever fully embrace data analytics. The main roadblock identified was one of culture: resistance to change. “I think it’s just human nature to get stuck in inertia,” said a private equity investor. “And I think we have a lot of work to do as an industry, to be frank.”

Utay thinks that if the use of data analytics in private equity ultimately fails, it will be “100% about culture” rather than availability. The rest of the world is going to improve the underlying intellectual property, he said, and make it more affordable to more firms. Eventually, fewer data experts will be needed per company. At that point, he said, “it is going to be about … can you take data analytics and integrate it into the way you think?”

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