Each year, attorneys and business development staff email thousands of research requests to the Research Services team at Squire Patton Boggs. Since requests are authored in unstructured natural language, it is difficult to categorize them, automatically suggest analytical resources, or see patterns in requests over time and anticipate rather than respond to requests.
Using a variety of tech-enabled approaches, Mind-Alliance helped the Global Director of Research Services develop a taxonomy of research request types. Analyzing a corpus of research requests surfaced meaningful patterns in the data. These insights are now enabling the department optimize its processes, accelerate research analyst productivity, and increase the utilization of e-resources. The Research Services team is now able to become more proactive and to provide anticipatory intelligence support to business development.
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