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Customer relationship management (CRM) has been defined in different ways but focuses on two main aspects: customer relationships and corporate profitability (Iacob, 2009; Khan et al., 2012). Khan et al. (2012) also defined CRM as a set of guidelines, procedures, processes, and strategies that enable companies to understand how customers interact with them and to maintain comprehensive customer information. CRM is part of management processes to achieve and sustain customer loyalty (Iacob, 2009).
Business intelligence (BI) is a set of tools, techniques, and processes that assist an organization in utilizing raw data in different forms to acquire knowledge and consequently make better fact-based decisions (Jennex & Bartczak, 2013). BI makes the best use of data, whether it is structured (e.g. relational database) or unstructured (e.g. web logs). In its raw state, data does not identify any particularly useful facts unless data has been processed in a proper way. Data can come from different business processes such as sales, customer usage, or logistics. The granularity of facts that BI stores is important to summarize data for strategic views, while drilling down to a single fact about specific customers for operational actions (Dobrev & Hart, 2015). Furthermore, storage capabilities available today make detailed, massive data easier to maintain, process, and retrieve. Organizations can create and discover knowledge through capturing new knowledge from specific explicit sources (Nonaka, 1994). BI techniques improve the efficiency and effectiveness of knowledge creation through combination. “BI systems combine data gathering, data storage and knowledge management with analytical tools to present complex internal and competitive information to planners and decision makers” (Jennex and Bartczak, 2013, pg.25). Both business intelligence and knowledge management focus on strategic intelligence, which adds value to organizations (Daliker, 2011). Therefore, it is critical to understand BI’s uses and how it can help organizations with answering business questions and decision support. BI has been used differently under various forms. Some concepts that resemble or overlap with BI are worth shedding light on, such as data warehouse (DWH), online analytical processing (OLAP), and data mining (DM) (Munyoroku, 2016). Advanced analytics and algorithms are critical today to harness valuable knowledge and business value from big data and the internet of things (Jennex, 2017). System use, including knowledge management tools (Jennex, 2008; Jennex & Olfman, 2006; Al-Busaidi, 2010), is a critical indicator of an information system’s (IS) success (DeLone & McLean, 2003).
BI is vital for telecommunications in gaining competitive advantages over competitors (Masoud & Ahmed, 2017). Also, BI has an important role in CRM in telecommunications, especially in understanding customers. Literature reviews underscore the importance of investigating the benefits of BI application in CRM. Moro, Cortez, and Rita (2015) conducted a literature review for articles from 2002 to 2013 in BI and highlighted researches gaps, as CRM has not been one of the top-investigated areas for BI applications. Additionally, Khan et al. (2012) recommended further investigation of CRM and data warehouse in industries such as telecommunications. More recently, Trieu’s (2017) literature review of the last 15 years articles highlighted a lack in finding a systematic framework an organization can use to highlight the values of BI.