Application of BI Technologies on Universities in General

  • A brief review of the application of BI technologies on universities in general.

In today’s digital era, both for-profit and non-for-profit organisations operate within a dynamic, highly competitive and technologically turbulent environment. Consequently, the development of strategic agility and business velocity by utilizing the unprecedented breadth of information plays a catalytic role in organisations’ sustainability and prosperity. In organisations’ quest to cost-effectively and rapidly harness data, business intelligence technologies seem to be a propitious tool. Business Intelligence (BI) is defined as a set of technologies, processes and methods enabling users to gather, store, access and analyse data in order to convert it into meaningful and useful information that facilitates business decision making (Negash, 2004). Business Intelligence systems not only can manage all forms of quality data (Dell’Aquila et al., 2008) but they can also generate ready-to- use information at the right time, area and format which leads to timely and more effective decision making and planning (Negash, 2004). Although the concept of BI is not widerspread (diadedomenh h xrhsh tou) for some industries, the term BI emerged fifty years ago (in 1958) by Hans Peter Luhn in an IBM article (Cebotarean, 2011). The most ubiquitous term of Business Intelligence is that suggested by Howard Dresner in 1989 who characterized BI as an “umbrella” concept as it encompasses all the decision making and information systems within all functions of an organization (Cebotarean, 2011). Business intelligence is the evolution of data warehousing, since what differentiates it from the latter is the fact that it provides users with tailored solutions adjusted to the specific business sector, business problems and needs (White, 1999). In corollary, BI technologies facilitate and accelerate access to all forms of up-to-date information and its dissemination among all departments for customised decision making, planning and problems solving by generating an accessible and flexible operating environment (White, 1999).What emerges from this is that BI application benefits the organization both through the development of competitive “intelligence” which gives a valuable insight of the competitive environment of the organization and as a managerial tool for effective management of the organization- either by enhancing its functionality in terms of cost-effectiveness and time-savings or by monitoring and optimizing its business units (Berta, 2012). Many industries have widely deployed BI technologies due to the plethora of advantages that provide. However, in education sector, the paucity of previous BI applications on Universities, the perceived less competition and managers’ perception that activities such as teaching are more essential for University’s well-function decelerated the adoption BI technologies by Universities (Piedade and Santos, 2010). Nowadays though, the wide breath of daily digitized data yielded at every educational activity (Selwyn 2014), the increased competition on the one hand and the decreased number of prospective students due to the increased tuition fees on the other as well as Universities’ funding requirements which accomplishment is depending on University’s data provided to government (HEFCE, 2013) and the high and varied expectations of all stakeholders such as students, alumni and lecturors have rendered BI imperative for Universities’ sustainability. This is reflected by the incremental adoption of data-driven approaches by Universities (Selwyn, 2014) not only for addressing internal issues in fields such as administration, admissions, library and operational resources management but also for attracting and retaining students through profiling and tracking and better understanding of their competencies to name some but a few (Piedade and Santos, 2010). One of the core applications of BI on Universities is those related to students. By conducting students’ surveys and leveraging daily data generated by students’ interaction with Universities’ platforms and facilities, Universities can gain a better insight of their own student marketplace and students’ needs and habits, monitor student achievements, evaluate their satisfaction and strengthen their relationship with alumni and current and potential students (Jisc, 2012). Therefore, not only can universities employ BI technologies to attract, satisfy and retain students (Weaver, 2013) through Student Relationship Management (SRM) but they can also improve students’ academic performance through customized offerings and in turn increase of satisfaction (Piedade and Santos, 2010). For instance, University of Maryland, Baltimore County (UMBC) has utilized BI technology in order to provide students with a platform that allow them anonymously to juxtapose their academic activities (Siemens and Long, 2011). Moreover, as Admission office is probably the first contact of students with the University, it is critical to be well-informed, well-organised and available. The admissions personnel are responsible not only effectively and timely cope with students’ applications but it should also reply to any enquire and make recommendations to students as well as instill University’s culture in students. Consequently, admission offices should be able to store, access and deal with a wide array of data in order to keep in touch with applicants and disseminate the elicited information to other departments by leveraging advanced BI technologies. Along with the fact that the first applications of information management systems on Universities appeared for library and academic resource management purposes (Langlois, 1998), libraries are a cornerstone of every world-leading University (Weaver, 2013). Nowadays, with the widespread usage of digital libraries due to the constant access to a vast breadth of knowledge regardless of time and country boundaries, Universities are heavily invest in acquiring academic databases (Zhang, 2011). Therefore, a core challenge faced by University’s libraries is the aggregation of both digital and physical recourses and their integration into a unified platform in order to interrelate and detect users’ preferences and provide them with cutomised recommendations according to their field of research and cross-referencing articles and books (Zhang, 2011). The mobile application of Boston College University Libraries which provides both librarians and students with an interactive platform of reading lists recommendations according to the subject, information of the availability of study rooms and computer clusters is a representative example of BI applications(Logi Analytics, n.d.). Finally, librarians can track information resources scarcity and optimize the library classification system and improve library services by utilizing data related to frequency of book loans, books condition and frequency and purpose of library usage (Zhang, 2011). Last but not least, BI technologies are employed by Universities for improving cost-effectively Campus buildings utilisation and Campus facilities (Jisc, 2012). By monitoring the usage of University’s buildings, electricity consumption and staff requirements, universities can optimize and detect superfluous operating expenses (Berta, 2012). Finally, through text mining, Universities can extend and tailor University’s accommodation and its facilities through students’ feedback to increase students’ satisfaction and identify patterns in order to suggest off-campus accommodation that meet students’ needs. In general, not only do BI technologies enhance students’ learning experience (Siemens and Long, 2011) through improvements in course context and learning methods (Langlois, 1998) , but they also provide Universities with useful KPIs illustrating University’s performance and areas for improvement (Berta, 2012) that could be utilized to increase University ranking and improve their competitive position (Selwyn 2014). It is also worth noting that the development of BI decrease the uncertainty of decision making for Universities (Selwyn, 2014) as well as for government as it generates tractable data that promote transparency (Eynon, 2013) and thus, contributes to raising funds (HEFCE, 2013) . A description of the organisation including the business area of interest and the available datasets (existing or possible to be obtained either internally or externally). The University of Manchester is one of the world’s leading research Universities envisioning to be amongst the top 25 research Universities worldwide till 2020 (Strategic Plan, n.d.). The University of Manchester is inextricably linked to the history of city of Manchester, as it constitutes a national heritage chronologised in 1824 (Strategic Plan, n.d.). In its status quo was formed in 2004 after the University of Manchester Institute of Science and Technology (UMIST) merged with the Victoria University of Manchester (UoM history, 2015). Its societal and scientific contribution is evident, as it counts of twenty-five Nobelist among them Rutherford who proved the “splitting of atom” (Strategic Plan, n.d.). Therefore, its academic reputation has spawned the interest of recruiters, rendering University of Manchester a point of reference for top-companies and leading to noticeable external funds raining (The University of Manchester, 2014). The University of Manchester is the largest single-site University in the United Kingdom possessing 339 campus buildings in Manchester (The University of Manchester, 2014, p.32). On top of that, it invests more than any other UK University in improving and expanding its facilities (Strategic Plan, n.d.). The University of Manchester structure is comprised by four faculties with the Faculty of Medical and Human Sciences accompanied the most Institutions and Schools (11 in number) (The University of Manchester, 2014, p.18). Moreover, its campus includes 23 accommodation buildings tailored according to students’ needs and preferences and provides students with approximately 8,500 rooms (The University of Manchester, 2014, p.12). It is worth noting that one of its top priorities is the environmental sustainability as its activities has a great impact on local community (Strategic Plan, n.d.). It is exceptional that the University of Manchester has the largest student community compared to other Universities in the UK with more than 265,000 alumni connected in 200 countries around the world (UoM Alumni, 2015) and 38,430 current students (The University of Manchester, 2014, p.12). Moreover, it provides the largest variety of degree programmes and therefore it employs more than 17,000 people (The University of Manchester, 2014, p.12). In this line, it is evident the emphasis is given on people not only to preserve and instill the University of Manchester’s culture and heritage but also to ensure high quality services. Last but not least, the University of Manchester Library has a significant cultural heritage value as it has academic collections dating back five millennia as well as great contribution to the reputation of the University of Manchester (Library strategy, 2013).Moreover, it is “the largest non-legal deposit academic library” in the UK (, 2015) and one of only five national research libraries (The University of Manchester Library, 2015).According to SCONUL’s research, the University’s Libraries have the second-highest number of users with the Main Library being the most popular among the users (LibQUAL, 2011) and one of the largest e-resources (SCONUL, 2012). In particular, the University has eleven Libraries in which four million books and printed academic resources are provided, notwithstanding the 450 thousand e-resources and hundreds of databases (Library strategy, 2013). In University’s quest to provide students and staff with efficient, extended and high-quality research and study experience, the University has launched The Alan Gilbert Learning Commons building in 2012, offering more than one thousand study spaces and hence expanding its IT accessible spaces to over three thousands (Strategic Plan, n.d.). Before this investment, the University Library had far below the average IT-enabled seats (284 units) compared to other research UK Universities (SCONUL, 2012, p.21) which was inadequate if we consider that it has approximately fifty thousand potential users including students and staff, spends more than any UK University and five times more than average spending on acquiring e-resources (SCONUL, 2012, p.58) and according to LibQUAL report 72% of University users visit libraries in order to access e-resources (LibQUAL, 2011) . However, the University’s emphasis on harmonizing the use of today’s highly-needed digital resources by heavily investing in information systems and technology with the use of physical resources by enhancing libraries, has not only rendered the University’s library as one of the most well-resourced libraries but it has also improve the quality of research and learning (Strategic Plan, n.d.). The University of Manchester Library plays a pivotal role not only in University’s reputation and performance (Tenopir et al., 2012), but also in students’ choice of University. According to Price et al. (2003), four of the first six determining criteria for students’ University choice are related to library facilities (Price et al. 2003). On top of that, there is a strong empirical evidence that the usage of libraries from students is positively related to students’ retention, performance and success (Emmons and Wilkinson, 2010; Wong and Webb, 2010; Stone and Ramsden, 2013). Furthermore, the Tenopir et al.’s research (2012) in which University of Manchester participated illustrates that sufficient library resources contribute to the recognition and reward of academic staff research (Tenopir et al., 2012). Finally, intriguing of new ideas and improvement of assignment is strongly attributed to adequacy and use of libraries for both University of Manchester students (Jubb et al., 2010) and academic staff (Tenopir et al., 2012) Driven by Library contribution and value, most of the University of Manchester departments collaborate in order to continuously improve and extend its provided Library facilities (Library strategy, 2013). For instance, it participates and develops several new projects aiming at enhancement of collaboration and customization, such as “StORe” project enabling the researchers to share data and relevant information and the project “Scarlet Augmented reality” (The University of Manchester Library, 2015) and facilitating the usage and access for both digital and physical resources (e.g the mobile application which interactively illustrates available computer clusters). Although, according to LibQUAL’s survey (2011) 94% of respondents were satisfied with Libraries’ facilities, 87% of respondents was satisfied with Main Library amenities, mainly due to issues pertaining to the physical environment of library and resources availability (LibQUAL, 2011). In this paper, we will articulate the functionality of library classification combined with computer clusters allocation by analyzing a synthetic dataset. However, it is a wide range of available datasets of past and up-to-date data, available internally by the University of Manchester Library and IT department as well as externally through Society of College, National and University Libraries (SCONUL), LibQUAL+®,Higher Education Statistics Agency (HESA) and JISC and its platforms such as MIMAS.

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