Recently, CRC Press published Data-Driven Law: Data Analytics and the New Legal Services by Edward J. Walters. The volume’s contributed chapters cover a wide range of topics at various levels of mathematical rigor, but they all underscore the importance of how data science can greatly improve the quality and efficiency of the legal process from document discovery to predicting potential judgments. While Data-Driven Law does not specifically discuss arbitration or other alternative dispute resolution mechanisms in which Dispute Resolution Data (DRD) specializes, we nonetheless believe that the book’s publication is a strong leading indicator of the growing role that data analytics will play throughout the legal profession. Certainly, we recognize that many strategic decisions in this profession are informed by the invaluable wisdom that practitioners have accumulated over a career’s worth of experience. What we aim to provide is a means to help augment that wisdom with knowledge derived from the analysis of data that have been collected thoughtfully, thoroughly, and systematically. In this way, practitioners need not rely exclusively on hunches or educated guesses to guide their decision-making processes. With the power of data, they can now provide their clients with more definitive and fact-based assessments of how likely a case will result in a particular outcome, given a set of defined input parameters.
To that end, we presented the first in a series of blog posts discussing the results of data-driven analyses which support the notion that the most frequently observed outcome of international arbitration cases is settlement or withdrawal. In most cases, settlement/withdrawal is reached relatively quickly, often less than a year following the claim date, and also prior to any counter-claim, preliminary hearing, or hearing on the case’s merits. Our results were derived from an aggregate view of all available international commercial arbitration case data in the DRD repository, which presently consists of nearly 4,000 cases dating back to 2005.
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