Dear Timothy: In my office we have recently been discussing how analytics is changing IR. Some see it as getting too much into the weeds and one coworker said it felt like we were "telling people what to do." How can we address these concerns and move forward?
Great question! First of all, we need to look at what analytics is. Since the term can carry different meanings, let’s take a quick look at some of the popular definitions. Gartner Research defines analytics as a term to “describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen.” Another definition given by David Park in the EE Times (August 2017) draws a distinction between analysis and analytics in that analysis is conducted to understand what happened in a situation based on the collected data, while analytics is carried out to address why the situation happened and what will happen next. In a sense, analytics is considered to be a broader term that encompasses various types of analyses, such as descriptive, inferential, and predictive, and with specific end goals and logical actions in mind that connect the means to the ends.
So, in light of the above definitions on analytics, how does analytics change IR? I would suggest to you that IR is also a broader term that covers a variety of “research conducted within an institution of higher education in order to provide information which supports institutional planning, policy formulation, and decision making” (Saupe, 1981). Saupe further defines research in IR as activities for curating “information about the college or university [that] results from analyses of quantitative data and qualitative assessments.” Although the specific duties and functions of IR professionals may vary depending on the missions of the colleges and universities they serve and the reporting lines of the positions, analysis and reporting are considered by far the most commonly carried out tasks involved in the work of IR across different types of higher education institutions and IR positions. Of interest to our discussion is that the analyses we have been conducting in IR are likely already a part of the analytics we are now hearing more about in the field. Our involvement in analytics may be through supporting enrollment management for establishing and evaluating predictive models for market share analysis. It may include the work we do in analyzing data from learning management systems to help with early identification of at-risk students. To a certain extent, IR professionals are already exposed to or actively engaging in analytics in some ways even though we might not be conceiving the relevant tasks as analytics, such as predictive or learning analytics. With specific actions in mind, analytics is much closer to the analysis tasks than the traditional reporting tasks we do in IR. With the advent of Big Data and advancements in information technology, the term analytics at this juncture would seem to be referring to specialized analytical activities that involve transforming large volumes of data into insights and actions, and by doing so in a more systematic and automated fashion. For IR professionals to support institutional planning, policy formulation, and decision making, it is only a natural extension of expanding our ability from answering the questions about what happened, to the questions about why it happened and what can be done to address the issues in the future. When analytics is done right, our learning will be improved and the insights for informing actions should be embraced —even if we need to tell others to do the right thing. In that case and in Saupe’s words, offering actionable insights to inform decisions will contribute to the betterment of our colleges and universities or institutional effectiveness through “sound plans, appropriate policies, and correct decisions.” As we know, student success is improved as well.
Last but not least, what about reporting? Again, with rapid advancements in information technology, it would not be far-fetched to assume that given the types of data and ways of accessing these data, the time we spend on reporting tasks would likely be diminished through further data standardization and automation in the future. What this scenario tells us is that the IR duties and responsibilities are changing and that analytics will take up a prominent place in our future work. Considering Christensen’s idea on disruptive technology that has played a role in displacing some long-established technology in our society, such as smartphones and landline phones, it is high time for IR professionals to identify emerging opportunities for expanding our analytical skills that will continue to contribute to our colleges and universities, and embrace the change that is certainly coming our way. AIR offers many great opportunities to enhance our knowledge and skills in this area. I would highly recommend to our colleagues to check out an upcoming publication by Karen Webber and Henry Zheng on this very topic for reference. Let me leave you with a parting thought by quoting Professor Aoun’s words in his book on Robot-Proof: “…the dawn of the robot age will be an opportunity, not a threat.” Together we can explore new opportunities to strengthen our profession and community!
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