Best Practices for Research Analytics & Business Intelligence within the Research Domain

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While an increased number of industries with business operations have been shaping their use of data analytics, the use of such tools and methods within the higher education research domain, specifically research administration, is still in its infancy. This mixed-methods study collected data to identify best practices in how universities and other research organizations use data analytics to drive their strategic agendas, create efficiency in operations, and promote complex research proposals throughout their institutions. Research methods included a survey to collect data on how research offices are using analytics and business intelligence tools, Rasch analysis (Rasch, 1993) to examine survey instrument quality and provide insights into the use of analytics and business intelligence tools in research offices, and interviews with research administrators and stakeholders to identify best practices in using data tools to impact their decisions, processes, and programming. Results from the Rasch analysis showed that except for two recommendations for individual scales, all survey scales exhibited satisfactory reliabilities and rating scale performance. Findings from interviews revealed best practices such as clear ownership and definitions of the data entry process, identified stewards of each of the high-level areas of data, and confirmed understanding of terms after data requests.