Data Diligence: The Missing Method In M&A Due Diligence

At their own peril, PE firms, boards and CIOs discount the financial value and market potential of corporate data assets, especially during times like these. Currently, we are in the throes of not only a pandemic-prompted recession but also on the cusp of a massive global economic reconfiguration. As a result, corporate entities themselves will transmogrify at a rate we have not ever experienced. Executives and boards will be compelled to evaluate and divest of entire flagging business units, or worse, put the assets of their insolvent businesses up for sale. 

Enter private equity firms. PE firms are poised to have a field day mopping up, integrating, recombining and reselling businesses over the next couple years at least. Greg Layok, managing director at West Monroe Partners predicts that we’re in a brief moment of frozen corporate deal-making prior to a major transaction boom, “Companies that are distressed and on the edge of faltering will be looking to sell, while stronger companies will seek buying opportunities.” 

However, most PE firms, VCs, and the corporate transaction units of consulting firms have done little to keep up with the Information Age other than merely favoring digital businesses. And CIOs and other executives have done little to measure and promote the value of their off balance sheet assets. In particular, Layok argues that there is tremendous unrecognized and unexplored value companies’ data assets. 

At the core of M&A matchmaking operations is a process known as due diligence, an antediluvian approach to expediently if not thoroughly valuing a business. Balance sheets and income statements are one way to evaluate a company, but PE firms and the like have developed methods for looking deeper for sources of value, potential opportunity and exigent risk. This enables them to ascribe premiums or discounts to businesses before bringing them into the portfolio or passing on the opportunity altogether. 

However, in evaluating the due diligence processes from a dozen or so corporate deal-makers, it’s clear that data assets are regularly overlooked. While some approaches do include evaluating a candidate business’s information technology capabilities, the due diligence focus on IT almost completely ignores the “I” while fixating on “T”. As a result, PE firms tend to depreciate the potential value of the company’s data assets. In today’s world where over 80 percent of corporate value is comprised of intangibles compared to less than 20 percent a few decades ago, according to the intellectual property firm Ocean Tomo, most of this intangible value is wrapped up in a business’s data. To overlook this primary source of value as part of a corporate valuation is an egregious oversight. 

“Corporate transaction experts trained in accounting standards may see it as a moot point to recognize information as an asset when valuing the business, simply because information isn't recognized as a balance sheet asset,” says Joe Sommer, senior manager in Ernst & Young’s data and analytics practice within its Financial Services Organization. “This is probably short-sighted in today’s data-driven economy.” Layok suggests it’s not so much an oversight as “a lack of institutional know-how in valuing data and identifying avenues of value creation from data.” 

Assessing the Value and Opportunities of Data

Yet both Sommer and Layok both acknowledge that just as with other asset classes, there are a variety of ways to assess the value of any given data asset. This includes determining its various quality attributes such as its accuracy, completeness, integrity, scale, precision, and timeliness. Each of these can be objectively measured, yet scant few organizations do so, even themselves. Additionally, one can determine the financial value of a data asset by applying somewhat adapted versions of established cost-, market-, and income-based valuation approaches. Adapted, because data has some unique economic qualities that other assets do not, such as that it can be reused without depletion, and used simultaneously for multiple purposes.

PE firms that do evolve to considering the potential value of data will have a unique edge: they’re a melting pot of sister companies with the ability to mix and match data from each to form unique efficiencies and competitive advantage, and even new value streams via externally monetizable data products. 

Sommer likens the naivete of data integration and monetization possibilities to those who separately enjoy peanut butter and chocolate but had never considered how delicious and market-expanding it would be to combine them. 

Moreover, it’s not just a company’s data that offers an additional indicator of value or risk, but also the organization’s overall data and analytics capabilities. If only data assets are being acquired devoid of the company’s data-related capabilities, as in the case of a bankruptcy fire sale, this may not be of particular interest. But when IT and business functions themselves are part of the potential investment, then evaluating the businesses’ data-related culture, leadership, strategy, organization, literacy, governance, deployment, and architecture should be requisite—even if only subjectively assessed by qualified experts. 

The Data Diligence Approach

Sommer submits that a PE firm could get a real jump on its competition, probably several years, by determining a methodical approach to valuing a company's data and data-related capabilities, and developing a set of benchmark ratios. Or, by partnering with such experts to develop and implement formal procedures for data diligence.  

Indeed, data diligence should be part of a PE firm’s repertoire, but it should also be something CIOs or chief data officers (CDOs) perform jointly with their CFOs to ensure they completely understand the value of their business, not just in anticipation of M&A activities. A data diligence process should address key considerations such as: 

• Data Valuation — How does data contribute to business efficiencies and revenue generation? What is the data’s cost basis and potential market value?  
• Data Synergies — How well will the acquiree’s data management function, architecture, and culture integrate with those of the acquiror? 
• Data Opportunities — What are innovative ways to generate value, or monetize, the company’s data assets, either on their own or when combined with those of portfolio companies or business partners? 
• Data Risks — Are their quality or consistency issues in the data? How well does the data environment mitigate regulatory or other compliance requirements? 
• Data Challenges — What challenges will there be in integrating or leveraging the acquired data assets? Or in integrating the data management or analytics functions of the two businesses being merged? 

Only with a complete picture of a company’s data and data-related capabilities can a PE firm expect to make fully informed decisions about whether or not to execute on deals and how to price them accordingly. 

DOUG LANEY BIO

Doug Laney is the Data & Analytics Strategy Innovation Fellow at West Monroe where he consults to business, data, and analytics leaders on developing new value streams from their data assets. He originated the field of infonomics and authored the bestselling book, “Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage.” Laney is a three-time Gartner annual Thought Leadership Award recipient, co-chairs the annual MITCDOIQ Symposium, and is also a visiting professor at the University of Illinois Gies College of Business and the Carnegie Mellon University Heinz College. Follow and connect with Doug on Twitter and LinkedIn.