Using Data for a Happily Ever After in M&A

When a leading electronic manufacturing company looked for opportunities to expand, an unexpected market caught management’s attention—baby care. On paper, the opportunity appeared exciting: the company’s single offering in this market was performing well and the market itself was growing rapidly. The company began looking for inorganic routes to gain a stronger foothold. They believed they found a perfect partner in a company that was well entrenched in the baby care market, with a full stable of products from electronics to feeding accessories.

As part of the due diligence, one of the many factors highlighted was that the company to be acquired used BPA in their feeding bottles. While this issue was considered and discussed, along with the many other risks identified, no one knew how fast public sentiment would turn against BPA. Less than a year after the acquisition, the entire range of feeding bottles was off the shelf.

This cautionary tale highlights one of the biggest problems with mergers & acquisitions: shortsightedness in using data to gain a more complete picture of business decisions.

Understanding the tricky nuances of consumer behavior

Before a company makes an acquisition, top management spends significant time and resources studying the company they are acquiring, market potential, legal compliance, financial health and so on. Yet, a few years into the relationship, they realize the opportunity was not as lucrative as they had thought it would be because of an unanticipated change.

Unanticipated change often appears in the form of a shift in consumer perceptions that results in a change in consumer behavior. Acquiring companies seldom have expert knowledge about the market they are entering through the acquisition. This makes it very difficult for them to understand or predict these shifts in perception before they gain momentum and cause change. There are numerous examples of “troubled acquisitions” that have resulted from this blindness, across the globe. In India, business giant TATA spent close to $17 million acquiring the country’s largest chain of brick-and-mortar book stores, Landmark. Earlier this year, they announced the closing of a large number of these stores. Their failure to understand a shift in consumer preferences led to significant losses.

One of the most critical aspects of the due diligence process is the macroeconomic audit, which, in conjunction with a marketing audit, will paint a portrait of the future growth potential of the company being evaluated.

The traditional method of doing this has involved a great reliance on information generated by the company to be acquired. This has typically taken the form of primary research a company has conducted through interviews and focus group discussions with a small sampling of customers, a SWOT analysis based on its understanding of the industry and other similar methods. The acquiring company filters this information based on opinions it gathers primarily through desk research, using analyst reports, influencer group reports and other data sources.

Companies Divorced from Digital Data

Unfortunately, the traditional process all too often ignores valuable sources of unbiased information like social media and HTML data have been completely ignored. Companies simply can’t afford to be divorced from digital data available to them—and data analytics can help modernize the research process for M&As.

Using analytics, social media data, for example, offers companies the opportunity to listen to natural conversations of large populations of consumers. From these conversations, it is easy to determine what or who is influencing them and how their perceptions are being molded. It also provides an unbiased platform to understand consumer preferences and patterns or behavior.

Similarly, by combining multiple sources of data, it is possible, for instance, to predict the sales of a product with high accuracy. Models can also be built to predict a behavior, like such as which consumers are “critical consumers” and about to lapse.

In addition, heat maps can be created to view consumer browsing patterns to identify reasons for abandonment of shopping carts, for instance, or where they spend the maximum time when browsing on a particular site.

These are just a few examples of how companies can apply the power of data analytics to influence how it reacts and responds to its customers and the market. The insights gained from analysis of a company’s own data and metadata from outside sources can result in more accurate and profitable decisions, from subtle changes to investing strategic assets that impact the entire organization. Relying on the sophistication of data analytics can systematically remove the “gut feeling” of executive decision making, reducing the potential for ill-fated moves. After all, the goal of any acquisition should be a long and fruitful relationship.