Nowadays, it is possible to digitally capture almost all data and store them in high storage capacity devices. The term big data refers to the massive amounts of data from a wide variety of sources, often available in real time. Undoubtedly, big data provide organizations the chance to gain a competitive advantage if data can be analysed effectively to make better business decisions. Lots of Italian researchers are dealing with big data in their studies across a wide range of disciplines, but few Universities seem to have explored the impact that big data management could have on their own organization. The benefits of big data and analytics on higher education institutions are manifold; the paper focuses on the two relevant dimensions of student careers and performance management. The Italian public universities receive state funds partially on the basis of a competitive allocation model in which the number of the high-quality students enrolled and the adoption of a periodic selfevaluation system play a fundamental role. Therefore, universities should use big data to predict academic and behavioural issues of their students, to prevent students from dropping out and, in general, to monitor the predictive variables that lead them to graduation. By means of predictive modelling of data mining, universities could be able to estimate the students preparation, engagement and academic performance at each time of their career. Since 2013 all the Italian Universities have adopted the guidelines about the Self-Assessment, Periodic Evaluation, Accreditation of the degree programmes (AVA) developed by the National Evaluation Agency that is also entrusted with the evaluation of the quality of research activities and of the university collaborations with stakeholders. A second field of application in which big data and analytics can be very useful is the performance management (PM), whose implementation, with the adoption of the performance cycle, highlighted the importance to have an analytics structure available in order to support the governance processes of the organization as a whole. In Italian universities, PM is considered to be the tool to improve efficiency, effectiveness, quality of policies, programs and services. In order to achieve these objectives, the University of Bari has long been developing an “in house” business intelligence system that organizes data flows, inner processes and causal relations. This paper aims at proposing the measurement model adopted by University of Bari as an Italian public university case study to demonstrate its feasibility and the organizational implications when measures are supplied to academic bodies, public sector managers and stakeholders.

360◦ university governance through big data

D'Uggento A. M.;CEGLIE, ROSA;Iaquinta M.
2019

Abstract

Nowadays, it is possible to digitally capture almost all data and store them in high storage capacity devices. The term big data refers to the massive amounts of data from a wide variety of sources, often available in real time. Undoubtedly, big data provide organizations the chance to gain a competitive advantage if data can be analysed effectively to make better business decisions. Lots of Italian researchers are dealing with big data in their studies across a wide range of disciplines, but few Universities seem to have explored the impact that big data management could have on their own organization. The benefits of big data and analytics on higher education institutions are manifold; the paper focuses on the two relevant dimensions of student careers and performance management. The Italian public universities receive state funds partially on the basis of a competitive allocation model in which the number of the high-quality students enrolled and the adoption of a periodic selfevaluation system play a fundamental role. Therefore, universities should use big data to predict academic and behavioural issues of their students, to prevent students from dropping out and, in general, to monitor the predictive variables that lead them to graduation. By means of predictive modelling of data mining, universities could be able to estimate the students preparation, engagement and academic performance at each time of their career. Since 2013 all the Italian Universities have adopted the guidelines about the Self-Assessment, Periodic Evaluation, Accreditation of the degree programmes (AVA) developed by the National Evaluation Agency that is also entrusted with the evaluation of the quality of research activities and of the university collaborations with stakeholders. A second field of application in which big data and analytics can be very useful is the performance management (PM), whose implementation, with the adoption of the performance cycle, highlighted the importance to have an analytics structure available in order to support the governance processes of the organization as a whole. In Italian universities, PM is considered to be the tool to improve efficiency, effectiveness, quality of policies, programs and services. In order to achieve these objectives, the University of Bari has long been developing an “in house” business intelligence system that organizes data flows, inner processes and causal relations. This paper aims at proposing the measurement model adopted by University of Bari as an Italian public university case study to demonstrate its feasibility and the organizational implications when measures are supplied to academic bodies, public sector managers and stakeholders.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/230326
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