The Impact of Creating a Business Intelligence Platform on Higher Education: The Case of the American University in Cairo

The Impact of Creating a Business Intelligence Platform on Higher Education: The Case of the American University in Cairo

Sherif H. Kamel (The American University in Cairo, Egypt), Iman Megahed (The American University in Cairo, Egypt) and Heba Atteya (The American University in Cairo, Egypt)
Copyright: © 2019 |Pages: 28
DOI: 10.4018/978-1-5225-7277-0.ch013
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In today's ever-changing global environment, the higher education industry is facing many diversified and evolving challenges and its landscape is becoming more competitive, dynamic, and complex. To proactively operate in such a changing and complicated environment, innovation, creativity, information, and knowledge represent key competitive edges that need to be introduced, cultivated, and managed effectively. The American University in Cairo (AUC) is a leading institution of higher education in the Middle East North Africa (MENA) region that recognized early on the power of knowledge and the need for a paradigm shift in management that capitalizes on innovative information and communication technologies. Accordingly, the university embarked on an ambitious journey as the first higher education institution in Egypt to build a state-of-the-art business intelligence (BI) platform that would support proactive, informed decision-making as a distinctive and sustainable competitive advantage.
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In an age where organizations are constantly in quest of competitiveness through innovation and transformation, business intelligence (BI) becomes mandatory for organizational effectiveness. This is true for organizations of all forms, sizes and industries, profit and non-profit, small, medium and large, as well as different types including government, private and public sector organizations, including academic and higher education institutions such as university settings. Moreover, it is invaluable for all organizational levels whether strategic, operational and/or tactical. The reason being the impact BI has on the quality of the organization’s decision-making process. BI creates a conducive organizational context to make better and more rational decisions by availing a comprehensive view of organizational data that would allow executives, middle managers and others to be more informed and build their decision making processes on timely and analyzed data to be more certain and accurate of the decisions made (Rouhani, Asgari, & Mirhosseini, 2012).

The role of BI is to create an informational environment with supporting processes by which operational data is gathered from transactional systems and enterprise resource planning (ERP) systems to be analyzed for strategic business and organizational insights. This is where the concept of an “intelligent organization” appears as one that deploys BI to enable faster and smarter decisions than its competition to create a sustainable competitive advantage. Accordingly, the “intelligence” element results from the transformation of huge volumes of data into information and knowledge through mechanisms for filtering, analysis and visualization, in support of the decision making process and corporate strategy tracking and progress (Gupta & Singh, 2014).

Despite the significant impact BI has in supporting informed decision making, strategy management and organizational success, the literature shows that there is a lack of agreement on the definition and real and effective implications of BI (Shollo, 2013). Based on the literature review conducted, following are some key definitions stand out and help illustrate the nature and scope of BI. For example, BI was defined as extracting the information deemed central to the business, and presenting or manipulating that data into information that is useful for managerial decision support (Gibson, Arnott, & Jagielska, 2004). Another definition suggests to perceive BI as combining data from operational systems with analytical front-ends to deliver timely information when decisions need to be made (Negash, 2004). However, in 2008, Baars and Kemper generalized the definition to encompass all components of an integrated management support infrastructure. Moreover, in 2010 Wixom and Watson defined BI as a broad category of technologies, applications, and processes for gathering, storing, accessing, and analyzing data to help its users make better decisions.

In 2011, according to Fitriana, Djatna, & Eriyatno in their analysis of the progress of BI systems, they defined BI as a process for extracting, transforming, managing and analyzing large data to gain information and knowledge that can support decision-making; and in 2014 Uma and Sankarasubramanian identified BI to be the ability to collect and analyze huge amounts of data pertaining to the customers, vendors, markets, internal processes, and the business environment. Therefore, from these various key definitions one can conclude that BI was initially used as a collective term for data analysis abilities, tools, techniques, technologies and solutions used in transforming data into knowledge. However, this understanding with time was broadened to include all the various components and processes associated in using information and analyzing them in order to create an integrated decision support infrastructure. It is important to note that the objective of all BI infrastructures and systems is defining the fundamental direction of an organization by supporting the decision-making process and helping different organizations to forecast the behavior of competitors, suppliers, customers and environments to differentiate themselves, and compete in the global economy (Wieder & Ossimitz, 2015).

Key Terms in this Chapter

Business Intelligence: BI is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.

Data Analytics: DA is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software.

Knowledge Management: It is the efficient handling of information and resources within a commercial organization.

Emerging Economies: An emerging economy reflects the characteristics of a developed market, but does not satisfy standards to be termed a developed market.

Big Data: It reflects extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

Information Management: It is the discipline that analyzes information as an organizational resource, it covers the definitions, uses, value and distribution of all data and information within an organization whether processed by computer or not.

Decision-Making: It is the process of making choices by identifying a decision, gathering information, and assessing alternative resolutions.

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