Abstract
Data is captured and analyzed for many purposes including supporting decision making. The expansion of data collection and the increasing use of data-driven decision support is creating a data-driven, global political, economic and social environment. This emerging global society is highly interconnected and many people rely on information technology to support decision making. This chapter explores the impacts that have and might occur as decision support technologies improve and continue shaping global society in new directions. Better understanding of the decision support and analytics phenomenon may help predict future societal changes and consequences. The goal of this analysis is to formulate hypotheses about the impact of decision support for further testing and speculate about long-run consequences. The increasing volume, velocity and variety of data is important to building new decision support functionality. Data collection expansion is part of a self-reinforcing decision support cycle that results in collecting more data, doing more analyses, and providing more and hopefully better decision support. Overall, nine hypotheses are proposed and briefly explored. More research is needed to test and verify them, but anecdotal evidence indicates analytics, business intelligence and decision support are creating a global society that is a data centric, real-time, decision-oriented socio-economic system. Data and decision scientists and technologists should anticipate and ponder the consequences of creating a more pervasive, data-driven global society.
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References
Anthony, R. N. (1965). Planning and control systems: A framework for analysis. Cambridge, MA: Graduate School of Business Administration, Harvard University.
Aziza, B. Big Data ‘A-Ha’ Moment? Forbes CIO Central, February 25, 2013 at URL http://www.forbes.com/sites/ciocentral/2013/02/25/big-data-a-hamoment
Bruner, J. (1968). Stand on Zanzibar. New York: Ballantine Books.
Clarke, A. (1968). 2001: A space odyssey. New York: Signet.
Davenport, T. H., & Patil, D. J. (2012, October). Data scientist: The sexiest job of the 21st century, Harvard Business Review.
Devlin, B. (2013a, February 5). Big analytics rather than big data. B-eye-Network blog. At URL http://www.b-eye-network.com/blogs/devlin/archives/2013/02/big_analytics_r.php
Devlin, B. (2013b, March 4). Big data—Please, drive a stake through its heart!. B-eye-Network blog. At URL http://www.b-eye-network.com/blogs/devlin/archives/2013/03/big_data_-_plea.php
Dyche, J. (2013, March 13). Big data’s three-legged stool. Information Management. At URL http://www.information-management.com/news/big-data-three-legged-stool-10024077-1.html
Economist Special Report. (2010, February 25). Data, data everywhere. Economist. At URL http://www.economist.com/node/15557443
Ehrenberg, R. (2012, January 19). What’s the big deal about Big Data? InformationArbitrage.com blog post. At URL http://informationarbitrage.com/post/16121669634/whats-the-big-deal-about-big-data
IBM ForwardView (2012, April). Watson’s next conquest: Business analytics. At URL www-304.ibm.com/businesscenter/cpe/html0/230318.html?subkey=subscribe&ca=fv1204&me=feature1&re=ushometxt
Franks, B. (2013). Taming the big data tidal wave. Hoboken: Wiley.
Friedman, T. (1999). The Lexus and the olive tree: ?Understanding globalization. New York: Farrar Straus Giroux.
Griliches, E. (2009, September). The impact of a total cost of ownership model. Cisco. At URL www.cisco.com/en/US/prod/collateral/routers/ps9853/impact_of_total_cost_ownership_model__idc_0928.pdf
Heinlein, R. A. (1964). Beyond this horizon. New York: Signet Books.
IBM. (2013). What is big data? At URL http://www-01.ibm.com/software/data/bigdata/. Accessed 6 Mar 2013.
Joy, B. (2004). Why the Future Doesn’t Need Us. Wired. At URL http://archive.wired.com/wired/archive/8.04/joy_pr.html
Kalakota, R. (2013, April 24). Gartner says—BI and analytics a $12.2 Bln market. At URL http://practicalanalytics.wordpress.com/2011/04/24/gartner-says-bi-and-analytics-a-10-5-bln-market/
Kurzweil, R. (2005). The singularity is near. New York: Viking Books.
Manyika, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. (2011, May). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.
Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. New York: Houghton Mifflin Harcourt.
Morris, J. ( 2012, July 16). Top 10 categories for Big Data sources and mining technologies. ZDNet. At URL http://www.zdnet.com/top-10-categories-for-big-data-sources-and-mining-technologies-7000000926/
Power, D. J. (2008). Decision support systems: An historical overview. In F. Burstein & C. W. Holsapple (Eds.), Handbook on decision support systems (Vol. 1, pp. 121–140). Berlin: Springer.
Power, D. J. (2012, April 1). Will thinking machines make better decisions than people? Decision Support News, Vol. 13, No. 7.
Power, D. J. (2013a). Decision support, analytics, and business intelligence (2nd ed.). New York: Business Expert Press.
Power, D. (2013b, January). What is machine data? Decision Support News, Vol. 14, No. 02.
Power, D. J. (2013c, March 17). Does the term big data have utility for managers? Decision Support News, Vol. 14, No. 06.
Power, D. J. (2013d, June 23). What is a data scientist. Decision Support News, Vol. 14, No. 13.
Power, D. J. (2013e, August 4). How will decision support technologies shape our global society? Decision Support News, Vol. 14, No. 16.
Power, D. J. (2013f, September 1). How is analytics, BI and decision support shaping global society? Decision Support News, Vol. 14, No. 18.
Power, D. J., & Phillips-Wren, G. (2011). Impact of social media and Web 2.0 on decision-making. Journal of Decision Systems, 20(3), 249–261.
Provost, F., & Fawcett, T. (2013). Data science for business: Fundamental principles of data mining and data-analytic thinking. Sebastopol: O’Reilly.
Rayner, N. (2011, October 7). Maverick research: Judgment day, or why we should let machines automate decision making. Gartner. At URL http://www.gartner.com/id=1818018
Reynolds, M. (1967). Computer war. New York: Ace Books.
The Matrix. Warner Bros. Pictures, 1999 at URL http://www.imdb.com/title/tt0133093/
Thinkartificial.org, Results from a poll April 22, 2007 at http://www.thinkartificial.org/web/the-fear-of-intelligent-machines-survey-results/
Walker, M. (2013, March 13). In-memory data grids allow data science at faster speeds. At URLwww.datasciencecentral.com/profiles/blogs/in-memory-data-grids-allows-data-scientists-analyze-big-data-at
Zikopoulos, P., DeRoos, D., Parasuraman, K., Deutsch, T., Giles, J., & Corrigan, D. (2013). Harness the power of big data: The IBM big data platform. New York: McGraw Hill.
Acknowledgements
This essay is based upon columns that have appeared in Decision Support News, including Power, D. J. (2013b–f). The feedback of the anonymous reviewers is acknowledged and appreciated.
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Power, D.J. (2015). Creating a Data-Driven Global Society. In: Iyer, L.S., Power, D.J. (eds) Reshaping Society through Analytics, Collaboration, and Decision Support. Annals of Information Systems, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-11575-7_3
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