Data-Driven Decision-Making: From Fine Wine to Fine Arbitrators

n virtually every sector of modern business, data is enhancing if not replacing intuition as the basis for making decisions. This trend holds even for assessments as seemingly subjective and rarified as predicting the quality—and hence price—of an exquisite French Bordeaux.

In selecting international arbitrators, however, intuition still predominates. For example, a recent industry survey by Bryan Cave Leighton Paisner found that the most important qualities in selecting an arbitrator are identified as “expertise” (according to 93% of respondents) and “efficiency” (according to 91%). Expertise and efficiency, however, are not easy to measure or quantify.

These qualities are not credentials that are listed on arbitrators’ CVs. Instead, expertise and efficiency are cumulative, largely intuitive assessments that are drawn from a number of sources and metrics. Moreover, what constitutes the best expertise or means for achieving efficiency may vary from case to case depending on a client’s needs.

Given the confidential nature of arbitration, gathering the relevant information means personal phone calls with individuals who have appeared before a potential arbitrator or, better yet, sat as a co-arbitrator with that person. This kind of ad hoc individual research largely confines assessment of potential arbitrators to feedback from a limited number of individuals. Despite this limited scope, ad hoc research can be time-consuming (and therefore costly), but not always reliable. Without broad data against which to evaluate these inputs, however, it is impossible to determine whether the feedback is broadly representative, readily transferrable to the case at hand, or just an outlier.

Another problem with ad hoc information gathering is that it creates an information bottleneck. Newer and more diverse arbitrators cannot readily develop international reputations as long as personal references are the primary means for determining expertise and efficiency. This informational bottleneck is increasingly intolerable in light of concerns about the lack of diversity among international arbitrators and in-house counsel with corporate benchmarks and applying greater pressure to find newer arbitrators about whom there is a scarcity of information.

Arbitrator Intelligence (AI) seeks to solve these problems by bringing data-driven analysis to arbitrator appointments. The means to these ends is the recently launched Arbitrator Intelligence Questionnaire, or AIQ.

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