Why Corporate Governance Needs to Account for Data-Driven Mergers

Why might an insurance company acquire a robot manufacturer or a retailer acquire a home security provider?  The answer might have once been diversification, but now it is more likely to be a desire for data.  A new type of merger, the data-driven merger, is playing an increasingly important role in the economy, and analyzing Elon Musk’s acquisition of Twitter as an example  reveals how Elon Musk’s business strategy could be just a play for data, and how corporate governance does not adequately account for such acquisitions.

Data mergers typically involve large conglomerates – often but not usually big-tech firms – that acquire companies rich in data primarily to gain access to their data. As we explain in our new article, these deals merit particular scrutiny because of their potential for circumventing antitrust regulations. We recommend a three-step approach. First, recognize data harvesting as central to the company’s valuation. Second, analyze the data aspects and purposes in high-tech companies’ mergers, whether these mergers are vertical or horizontal within a corporate family. Third, examine how these companies plan to use and make money from the collected data. This analysis may uncover insights missed by traditional antitrust and corporate governance analyses, and Musk’s acquisition of Twitter offers a case study in how the current corporate governance paradigm does not adequately account for the increasing value and role of data in modern corporations.

Consider the dispute between Musk and Twitter over the quantity of bots on the platform. Most corporate governance analysis focused on the impact of the metric used to measure Twitter’s daily active users – mDAU – in examining Musk’s attempt to kill the deal over Twitter’s alleged failure to disclose the full scope of its bot problem. Yet this focus failed to account for the broader and increasingly crucial role that data plays in valuation.

Each of Musk’s ventures relies on extensive data collection and analysis. Viewing his acquisition of Twitter as a play for data to fuel those other ventures better explains his obsession with bots and related false data and more generally highlights a pivotal shift towards valuing companies based on their potential to contribute to and leverage vast data collections. Twitter’s API, which governs how external software can access this data, imposes strict limitations on usage and sharing. To obtain the full scope of the content, Musk needed to own Twitter. Owning Twitter allows access to data that is concealed from users by complex privacy policies that obscure data sharing practices. But owning all that data is only helpful for use in other artificial intellegience and data-intensive ventures to the extent of the quality of the data. If the data needs to be scrubbed to be put to Musk’s intended uses, the value of the data, and, thus, of Twitter, declines. Viewed in such a light, it makes sense that corporate governance rules strained to comprehend the bot dispute when focused on the mDAU metric makes sense – corporate governance needs a better way to recognize and account for the true intrinsic value of data to increasingly data-centric economic endeavors.

Federal laws appear inadequate for considering the complexities of data-driven mergers, suggesting that state law might provide a more effective governance solution. In particular, most shareholders affected by a botched data merger may be unable to seek monetary damages under Section 13(d) of the Exchange Act, highlighting the limitations of current securities regulations to address these harms. Although the regulatory landscape goes beyond the SEC, the 1934 Act plays a key role because publicly traded companies are required to meet rigorous reporting standards. Adisclosure regime can protecte investors and promote good governance, yet it can be manipulated by management to circumvent state law duties, highlighting the limitations of reporting systems in portraying a company’s full business value beyond existing financial metrics. At present, mandatory reporting focuses on tangible data and omits soft information like user authenticity, which can significantly impact valuations.

State laws, by contrast, protect shareholders by requiring a minimum standard of director behavior and shareholder rights to information. Although state laws, like the Model Business Corporation Act and the Delaware General Corporation Act, impose fiduciary duties on directors, shareholders can shape the scope of liability for breach of such duties by contract. Moreover, under the landmark cases Revlon, Inc. v. MacAndrews & Forbes Holdings, Inc. and Unlocal Petroleum Corp v. Mesa Petroleum Co., directors are required to consider shareholder value and justify defensive measures against takeovers. Putting them to full effect likely requires a shift to formal inclusion of the intrinsic value of data into the valuation of a company. For example, in a data merger, formally incorporating data into the valuation of a company could mitigate the risks of data-driven mergers and acquisitions and protect shareholders. To ensure that boards and shareholders understand the importance of data to a company or to potential acquirers of a company, properly addressing data driven mergers and acquisitions may require the incorporation of data protection and privacy into the corporate governance frameworks.

To properly value mergers and acquisitions in the future, the impact of data must be considered.  Doing so could give shareholders additional powers to challenge mergers, and give the market a fairer assessment of company value.

This post comes to us from Carliss Chatman, an associate professor at SMU Dedman School of Law, and Carla L. Reyes, Robert G. Storey Distinguished Faculty Fellow and associate professor at SMU Dedman School of Law. It is based on their recent article, “Uncovering Elon’s Data Empire,” forthcoming in the Stetson Law Review and available here.