The Strategic Adoption of Big Data in Organizations

The Strategic Adoption of Big Data in Organizations

Nabeel Al-Qirim (United Arab Emirates University, UAE), Kamel Rouibah (Kuwait University, Kuwait), Mohamad Adel Serhani (United Arab Emirates University, UAE), Ali Tarhini (Sultan Qaboos University, Oman), Ashraf Khalil (United Arab Emirates University, UAE), Mahmoud Maqableh (The University of Jordan, Jordan) and Marton Gergely (United Arab Emirates University, UAE)
Copyright: © 2019 |Pages: 12
DOI: 10.4018/978-1-5225-7277-0.ch003

Abstract

This chapter investigates the strategic adoption of big data (BD) and analytics (BDA) in organizations. BD represents a large and complex phenomenon which spans different disciplines. BD research is fraught with many challenges. This research develops BD adoption model that could aid organizations in assessing the strategic importance of BD to gain different advantages including gaining a competitive advantage. BD is considered a radical technology and realizing its advantages in organizations is challenged with many factors. The research attempts to outline the different aspects of BD highlighting different contributions, implications and recommendations.
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The Strategic Advantage Of Bda

IDC (2012) projects that by 2020 the digital universe will reach 40 zettabytes (ZB), which is 40 trillion GB of data and that the amount of B2C and B2B transactions will be 450 billion per day. The challenge here is that will we be able to deal with such amount of data as existing technologies in place are still handles terabyte to PB data only. This development in data has led to the growth of BD repositories, BD analytics/mining (BDA), and business intelligence (BI) which is driven mostly by the need of enterprises to be more competitive in: becoming more customer-centric, entering new markets and creating new business models and improving operational performance (Columbus, 2016) including improving decision making (Janssen et al., 2017). BDA is the process of uncovering actionable knowledge patterns from BD (in Habib ur Rehman et al., 2016). From now onwards BD and BDA are used interchangeably here to refer to big data.

Côrte-Real et al. (2017) found that BD can provide value at several stages: knowledge, dynamic capability (organizational agility), business process, and competitive performance. Habib ur Rehman et al. (2016) found the literature praising BD in that it could help enterprises maximize their profits by optimizing business process models and improving internal business processes. They also found that the convergence of IoT with BD and CC has taken enterprises to the next level for value creation. BD is seen as a way to enhance organizational agility and to survive in competitive markets in areas of production and operations or product and service enhancement (Côrte-Real et al., 2017). Frizzo-Barker et al. (2016) contributed the hype surrounding BD to the fact that data has become cheaper to store and analyze and easier to collect through web clicks, RFID tags, sensors, loyalty cards and barcodes. They highlighted the following benefits of BD: availability, visibility, and transparency of information and in helping businesses market products and services in a new way, optimizing operations and processes, measure and manage predictive-ity by finding new patterns and connections. However, they found most of the BD research is concentrated in large in the USA followed by Europe and Asia respectively and in large organizations only.

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