Advertisement

Adopting Business Analytics to Leverage Enterprise Data Assets

Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)

Abstract

In today’s rapidly changing business environment, advances in information and communication technologies are happening at a very fast pace. As a result, firms are under constant pressure to quickly adapt, be competitive, and identify new business opportunities. Also, the amount of data collected by organizations today is growing at an exponential rate and includes structured as well as new types of large and real-time data across a broad range of industries such as streaming, geospatial, social media, or sensor-generated data. Enterprise data have become an invaluable strategic asset. Many organizations are using modern Business Analytics (BA) to extract new insights and the maximum possible value from these data assets, which will enable them to make timely and accurate decisions. In this paper, we briefly describe business analytics and discuss how leading world class organizations are adopting it and the technology environments that make it relatively easy and inexpensive and, the subsequent competitive benefits they have achieved. In addition, we will report some findings from surveys of executives, managers, and professionals across industries about the use of analytics in their organizations, done recently by IBM, SAS, MIT, and Gartner. Also, we will briefly address the organizational, cultural, and technological challenges faced by organizations embracing business analytics. Finally, we will discuss the unique obstacles and challenges encountered by firms in developing countries with the goal of raising awareness of organizations in the MENA region not only about these impediments but also about the benefits of these technologies and the crucial role they play in the survival and competitiveness of the firm in the complex and turbulent global market.

Keywords

Business analytics Big data Datasets Competitive advantage 

References

  1. Accenture Global Operations Megatrends Study. (2014). Big data analytics in supply chain: Hype or here to stay? Accenture report. Retrieved from www.accenture.com/megatrends
  2. Clyde Holsapple, C., Lee-Post, A., & Pakath, R. (2014). A unified foundation for business analytics. Decision Support Systems, 64, 130–141.CrossRefGoogle Scholar
  3. Davenport, T. (2013, December). Analytics 3.0. Harvard Business Review.Google Scholar
  4. Davenport, T. H., & Harris, J. G. (2007). Competing on analytics. Boston: Harvard Business School Press.Google Scholar
  5. Evans, J., & Linder, C. (2012). Business analytics: The next frontier for decision sciences. Decision Line, 43(2), 4–7.Google Scholar
  6. Gartner. (2016). Building the digital platform: Insights from the 2016 Gartner CIO agenda report. Gartner Executive Programs, Gartner Corporate Headquarters. Retrieved from www.gartner.com
  7. Harvard Business Review Analytics Services. (2012). The evolution of decision making: How leading organizations are adopting a data-driven culture. Harvard Business Review analytics services report, 2012. Harvard Business School.Google Scholar
  8. Hopkins, M. S. (2010). Are you ready to reengineer your decision making? MIT Sloan Management Review, 52(1), 1–7.Google Scholar
  9. Hopkins, M. S., LaValle, S., Balboni, F., Kruschwitz, N., & Shockley, R. (2010). 10 data points: Information and analytics at work. MIT Sloan Management Review, 52(1), 27–31.Google Scholar
  10. IBM Institute for Business Value. (2012). Analytics: The real-world use of big data—How innovative enterprises extract value from uncertain data. The IBM Institute for Business Value report. Retrieved from www.ibm.com/iibv
  11. Koff, W., & Gustafson, B. (2011). Data rEvolution. Leading Edge Forum, Computer Sciences Corporation.Google Scholar
  12. Long, J., & Brindley, W. (2013). The role of big data and analytics in the developing world. Chapter 3, Accenture. Retrieved from www.accenture.com/technologyindevelopment
  13. Shacklett, M. (2014). Starting with small data in emerging markets to get to bid data analytics. TechRepublic. Retrieved from http://www.techrepublic.com/article/start-with-small-data-in-emerging-markets-to-get-to-big-data-analytics/
  14. The Burtch Works Study. (2015). Burtch Works LLC report.Google Scholar
  15. Watson, H. (2011). Business analytics insight: Hype or here to stay? Business Intelligence Journal, 16(1), 4–8.Google Scholar
  16. Zikopoulos, P. C., Deroos, D., Parasuraman, K., Deutsch, T., Corrigan, D., & Giles, J. (2013). Harness the power of big data—The IBM big data platform. New York, NY: McGraw Hill.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.School of Business and Economics, State University of New York at PlattsburghPlattsburghUSA
  2. 2.School of Business Administration, Canadian University of DubaiDubaiUAE

Personalised recommendations