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Digital Transformation of Higher Education: Competing on Analytics

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Abstract

Digital transformation of higher education is about more than just technology. The goal is to adopt new ways of working in order to continue delivering user-focused services in the face of changing technology, competition, audience needs and behavior. Digital (core) services, digitally skilled educators and students, decisions that consider available evidence are some of the characteristics of a digitally transformed higher education. In conditions of great uncertainty and competition higher education have to move from wondering what the future might hold to predicting the future - making proactive decisions and taking action based on that information. Evidence-based, quantitative and predictive decision making is a quite reliable way of gaining competitive advantage. With the widespread availability of data in many businesses, leading business organizations have recognized and significantly leverage the power of analytics in the most important decisions affecting their business. This is a path that higher education institutions should follow in order to turn their data into meaningful value. Conventional and unconventional (unstructured), internal and external data should be used to discover hidden patterns underlying performance in different areas, track admissions, optimize enrollment, manage grants, enhance academic advising etc. To gain insights from vast amounts of accumulated data and, what is even more challenging, translate these insights into powerful business decisions higher education institutions have to catch up with big data and data analytics tools and techniques as fundamental enablers of evidence-based, data-driven predictive decisions. Pointing out that digital transformation of higher education institutions is critical to their future success we are focusing on data aspects of this transformation, bearing in mind that data itself is an asset while the real challenge is turning that data into value. This paper points to the need for a more comprehensive adoption of big data and analytics solutions in higher education: key imperatives of adoption are listed, some activities that seem suitable for analytics pilot projects are considered, and expected business advantages are described. Finally, we emphasize that, due to increasing number of open source platforms and tools, the adoption of data analytics in higher education is becoming less and less a matter of money, and much more a matter of recognizing the value of generating useful insights and spawning innovations and a matter of preparedness of higher education institutions for such an undertaking.
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... Relying on the value of data, analytics platforms deliver the capabilities needed by decision makers as seen on Table 1. (Seres et al. 2018) Schools that learn to break down these barriers will have a greater chance of developing a comprehensive picture of their students and degree programs. Three main areas of analytics can be summed under three categories: admission tracking, enrollment optimization and academic advising (Seres et al. 2018) Using big data capabilities to generate and analyze data, institutions can learn useful information such as: ...
... (Seres et al. 2018) Schools that learn to break down these barriers will have a greater chance of developing a comprehensive picture of their students and degree programs. Three main areas of analytics can be summed under three categories: admission tracking, enrollment optimization and academic advising (Seres et al. 2018) Using big data capabilities to generate and analyze data, institutions can learn useful information such as: ...
... Because it can be said that digital transformation is not only based on the use of technology, but also on a vision and strategy. This concept, which is not an instant process, requires long-term planning (Seres et al., 2018). In this context, there are different definitions of digital transformation in the literature. ...
... In addition, several studies evaluate the outcomes and trends of digital transformation [13,16,17] or mention the challenges and opportunities of online learning during the Covid-19 outbreak [18] or emphasize human behaviour regarding devices and technology [19]. Most of the studies mainly look at the current state of digital transformation at universities [4,16,20] or mention the challenges lecturers and students face in digital transformation [1]. Some other studies mention human factors [19], the role of leaders [9], and information systems [3] in promoting the digital transformation of universities. ...
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Chapter
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