Data Science, M&A, and COVID-19

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.” 

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.”

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.”

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.

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.