- Data science is an evolving and growing area within the context of M&A. Advanced data analytics can support and quantify company positioning, and is increasingly being used by buyers during diligence, by owners to drive value creation initiatives, and by sellers to position a company for sale.
- This is particularly true in light of COVID-19. In the coming months, company buyers and sellers will be challenged to isolate and quantify the near-term impacts of COVID-19 from longer-term business performance.
- Here, we team with Two Six Capital, a leading data science firm, to discuss the evolving role of data analytics within M&A and methodologies businesses can employ to quantify the impact of COVID-19.
Bump or Curve? Divot or Ditch?
Will there ever be another year like 2020? One thing is for certain: For quarters to come, business buyers and sellers will be challenged to separate COVID-19-specific impacts—positive and negative—from longer-term factors endemic to the business.
“Is this sales lift sustainable when COVID-19 is less disruptive? Is the business model temporarily compromised, or has this year of crisis dealt a fatal blow? Is the business on an entirely new trajectory, or is this just a kink in the curve? These are all questions we’re being asked by buyers,” says John Neuner, managing director and co-head of M&A at Harris Williams.
Hence the rapidly growing use of advanced analytics in the context of M&A, says Neuner. New tools and technologies have made it easier to capture actionable insights from data, including data derived from customer transactions, product and service usage, sales and marketing, customer service, and other key facets of the customer relationship.
When combined with strong business acumen and seasoned sector expertise, the opportunity is greater than ever to leverage data to validate company positioning, trends, and growth drivers, and thereby underwrite value.
“To maximize value, the seller has the burden of proof,” notes Geoff Smith, a managing director in the Healthcare & Life Sciences Group. “They must provide the evidence that is underlying the company’s positioning. The story has to match the data, and it’s often the second and third layer of data that is the most important. Sellers have to go beyond current revenue and profits, showing how and why these variables are increasing, and why that will continue.”
Deep Analysis at Deal Speed
Neuner says buyers increasingly want this data early, driving the need for deep analysis “at deal speed.” That, in turn, is boosting demand for services provided by specialist firms such as Two Six Capital, which generally have the focus, technology, capacity and experience to execute in-depth analyses quickly.
“Buyers want the flexibility to move quickly,” says Mike Wilkins, a managing director in the Technology, Media & Telecom Group. “Using these groups on the front end enables that speed. If we can’t move at buyer speed, they can get frustrated and fall away.”
Wilkins notes that the speed at which useful insights can be delivered has dramatically improved. “One reason that data science is growing within M&A is because the speed at which some providers can move allows work to be completed that used to take too long.”
Smith adds that while major private equity groups and their portfolio companies have been using data analytics for several years, it has been from an operational perspective—not in a deal setting. Now, says Smith, the application of advanced analytics is extending to key revenue and profitability metrics, and is moving beyond the largest players: “We’re already seeing more analytics being done in the middle market, and we are doing more of this work on a larger number of our deals.”
COVID-19: A New Reference Point
Ian Picache, co-founder of Two Six Capital, a data science firm focused on private equity, says the widespread impacts of COVID-19 have accelerated demand for M&A-related analytics. “Fundamentally, COVID-19 has changed customer behavior in almost every industry. Every business we're working with has been affected for better or for worse. They’re all looking to understand evolving customer behavior, purchasing patterns, and which products are selling and which aren't.”
Going forward, says Picache, COVID-19 will become the new reference point for resilience and how well global businesses can weather disruption.
According to Picache, companies typically seek one of three types of analyses. First, the most foundational analysis is of the company’s current performance, no small feat in today’s fast-moving environment. The complexity of many organizations is another formidable challenge, with data silos complicating efforts to get a clear, holistic view of performance, says Picache.
At the next level, many companies seek to understand where they are headed via scenario planning, and, as noted above, whether they are experiencing short-term bumps or long-term curves (Figure 1).
“Generally, a positive bump involves the same customers in the same core markets, as well as the same usage patterns—but just more of everything,” explains Picache. “We’ve seen that with some in-home entertainment and hobbyist companies. People are sitting at home and have less to do because of COVID-19, but once this passes, business is going to return to normal.”
In contrast, says Picache, businesses on a new growth curve will see expansion into new markets, customer types and usage patterns. He cites remote workforce technology as one sector undergoing such change due to COVID-19. In either case, large-scale simulations are essential to understanding the trajectory of the business and how best to manage it.
Picache says the most sophisticated analyses go even further, using testing and experimentation to learn in real time which initiatives are generating the desired outcomes. “These analyses can involve different marketing approaches and channels, business models, locations, customer types, usage patterns and other variables. By looking closely at which customers, engagement models, and outlets perform the best you can plan a strategy that optimizes revenue and margins.”
Speed is essential across these analyses, reiterates Picache: “In this time of dislocation, it’s very important to be able figure out what’s happening with the business and adjust as quickly as possible.”
Industry Expertise: The Essential Ingredient
Neuner, Picache, Wilkins and Smith agree that industry expertise is the most essential input into any of these analyses. Customer behavior is changing fundamentally, impacting businesses positively and negatively depending on sector. “Customer retention and profitability look very different across consumer segments,” says Neuner. “The differences are even larger when comparing direct-to-consumer businesses to healthcare, B2B services, technology and industrials. Also, data is just data: Broad and deep deal and sector experience enables our bankers to quickly use that data to focus on the key proof points and metrics that effectively convey the story to buyers.”
For location-based and multi-site businesses, adds Neuner, key imperatives include understanding the extent to which increased online behavior will persist, and how to reopen brick-and-mortar locations accordingly.
On the other hand, notes Wilkins, many Harris Williams technology clients are now trying to understand how to capitalize on the lift they are seeing from COVID-19-related surges in adoption, particularly those that support remote working, collaboration and communication. “Take usage as an example,” adds Wilkins. “It costs very little for software companies to support additional customer use. However, healthcare or gym utilization is a very important source of costs. So the same data from one industry to another can have vastly different meanings.”
While sector-specific nuances abound, any company stands to benefit from a deep, well-rounded view of its customers. Picache says many organizations struggle to attain an integrated view of customer behavior, and only gain such a perspective by integrating data from transaction systems, usage logs, enterprise resource planning (ERP), customer relationship management (CRM), business intelligence (BI) and data warehouse systems (Figure 2).
“A lot of what we’re doing for clients now is stitching together several data sources from various silos in a company,” he says. “Often the finance team will have great transaction data. But that data is separate from usage data, which is separate from sales, marketing and customer support.”
Figure 2: Integrating Data to Drive Insights
Sales Transactions Across Systems: ERP, CRM, e-Commerce, BI, Data Warehouse
Picache adds that tying together available data sources can yield unexpected insights: “As an example, a lot of companies don't know that their highest revenue-generating customers are actually not their most profitable ones. Why? Because they were very expensive to acquire and are also expensive to serve and retain.”
Conversely, understanding which customers are most profitable—particularly when new customer types are walking in the door—can drive strategies to acquire and retain more of them, and “stay on the curve” the COVID-19 crisis has enabled. If current conditions have steered the company into a ditch, the same analysis can illuminate the best path out.
There are also certain analyses that are more or less important to specific industries. Neuner says that one of the most important questions to location-based and multi-site clients (a broad landscape across fitness, consumer health, entertainment venues, restaurants, and retail) —especially now—is which outlets drive the most performance and which should be shuttered, and how revenue will be affected.
As shown in Figure 3, one way to answer this question is by modeling customer attendance and capacity. By studying overall capacity system-wide on an outlet-by-outlet basis, it becomes possible to understand the differences between outlets, and how changing capacity will impact the company’s performance.
“When we did this analysis for a client recently, we found that the company could cut its capacity in half and only have a 5% drop in revenue,” says Picache. “And because its utilization was so low, it could reopen with full social distancing practices in place without any real impact on revenue.”
Even before the disruptions of the COVID-19 crisis, in-depth data analysis was a hallmark of successful M&A. Today, the pressing need to discern between temporary and longer-term impacts and devise sure-fire strategies to optimize business value has intensified the need for smart analytics.
That’s where industry expertise comes in. Attaching the “why” to the “what,” and, ultimately, getting to a “how,” requires deep knowledge and experience of a sector’s dynamics, as well as its history and future. Marrying the quantitative with the qualitative is now, more than ever, essential to realizing the potential value of any transaction.
Published August 2020
Two Six Capital is a leading data analytics advisory firm focused on serving private equity firms and their portfolio companies worldwide. Two Six Capital pioneered data science for private equity in 2013 and is backed by 25 years of research from Wharton. The firm uses proprietary technology to combine large-scale engineering, statistics, and machine learning to understand, project, and drive revenue. Two Six Capital has been involved in over $32 billion of private equity transactions that have closed and has analyzed over $150 billion of granular data.