Big Data as Strategic Enabler - Insights from Central European Enterprises

  • Rainer Schmidt
  • Michael Möhring
  • Stefan Maier
  • Julia Pietsch
  • Ralf-Christian Härting
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 176)


Big Data increases the amount of data available for analysis by significantly increasing the volume, velocity and variety. Big Data is the coincidence of technological developments with a radical transformation of information flows. Beyond technological considerations only few, general analyses of the strategic impact of Big Data exist. Therefore, we designed a study analyzing the strategic impact factors of Big Data. The study is based on a survey from 148 responses of enterprise specialists and managers in the field of Big Data, originating from central European enterprises. Key findings are that idle data have a negative moderate effect and the type of business process has a positive effect on the perceived advantages of big data. Furthermore there is an effect of the perceived advantages of big data on the planned and current use.


big data strategy business intelligence empirical research business information system 


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  1. 1.
    Gantz, J., Reinsel, D.: Extracting value from chaos. IDC IView, 1–12 (2011)Google Scholar
  2. 2.
    Mearian, L.: World’s data will grow by 50X in next decade, IDC study predicts,
  3. 3.
    Porter, M.E., Millar, V.E.: How information gives you competitive advantage. Harv. Bus. Rev. 63, 149–160 (1985)Google Scholar
  4. 4.
    McAfee, A., Brynjolfsson, E.: Big data: the management revolution. Harv. Bus. Rev. 90, 60 (2012)Google Scholar
  5. 5.
    LaValle, S., Lesser, E., Shockley, R., Hopkins, M.S., Kruschwitz, N.: Big data, analytics and the path from insights to value. MIT Sloan Manag. Rev. 52, 21–32 (2011)Google Scholar
  6. 6.
  7. 7.
    Bughin, J., Chui, M., Manyika, J.: Clouds, big data, and smart assets: Ten tech-enabled business trends to watch. McKinsey Q. 56 (2010)Google Scholar
  8. 8.
  9. 9.
    Kaisler, S., Armour, F., Espinosa, J.A., Money, W.: Big Data: Issues and Challenges Moving Forward. In: 2013 46th Hawaii International Conference on System Sciences, pp. 995–1004. IEEE Computer Society, Los Alamitos (2013)CrossRefGoogle Scholar
  10. 10.
    Brynjolfsson, E., Hitt, L., Kim, H.: Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? (2011)Google Scholar
  11. 11.
    Breuer, P., Forina, L., Moulton, J.: Beyond the hype: Capturing value from Big Data and advanced analytics,
  12. 12.
  13. 13.
    The Hidden Biases in Big Data - Kate Crawford - Harvard Business Review,
  14. 14.
    Möhring, M., Schmidt, R., Wolfrum, N., Kammerer, M., Maier, S., Höritz, S.: How Big Data Transforms the IT Department to a Strategic Weapon. In: Proceedings of the IADIS International Conference Information Systems 2013, Lisbon, pp. 323–326 (2013)Google Scholar
  15. 15.
    Schmidt, R., Möhring, M.: Strategic alignment of Cloud-based Architectures for Big Data. In: Proceedings of the 17th IEEE International Enterprise Distributed Object Computing Conference Workshops (EDOCW), Vancouver, Canada, pp. 136–143 (2013)Google Scholar
  16. 16.
    Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A.H.: Big data: The next frontier for innovation, competition, and productivity. McKinsey Glob. Inst., 1–137 (2011)Google Scholar
  17. 17.
    Kemper, H.-G., Baars, H., Lasi, H.: An Integrated Business Intelligence Framework. In: Rausch, P., Sheta, A.F., Ayesh, A. (eds.) Business Intelligence and Performance Management, pp. 13–26. Springer, London (2013)CrossRefGoogle Scholar
  18. 18.
    Barton, D.: Making Advanced Analytics Work For You. Harv. Bus. Rev. 90, 78–83 (2012)Google Scholar
  19. 19.
    Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: From big data to big impact. MIS Q. 36, 1165–1188 (2012)Google Scholar
  20. 20.
    Brown, B., Chui, M., Manyika, J.: Are you ready for the era of “big data”? McKinsey Q. 4, 24–35 (2011)Google Scholar
  21. 21.
    Hannula, M., Pirttimäki, V.: Business intelligence empirical study on the top 50 Finnish companies. J. Am. Acad. Bus. 2, 593–599 (2003)Google Scholar
  22. 22.
    Kart, L., Heudecker, N., Buytendijk, F.: Survey analysis: big data adoption in 2013 Shows Substance behind the hype (2013)Google Scholar
  23. 23.
    Commission, E.: NACE Rev. 2–Statistical classification of economic activities in the European Community. Luxemb. Off. Off. Publ. Eur. Communities (2008)Google Scholar
  24. 24.
    Mayer-Schönberger, V., Cukier, K.: Big data: a revolution that will transform how we live, work and think. John Murray, London (2013)Google Scholar
  25. 25.
    Stigler, S.M.: The Story of Statistics: The Measurement of Uncertainty Before 1900. Harvard University Press (1986)Google Scholar
  26. 26.
    Boscovich, R.J.: De litteraria expeditione per pontificiam ditionem, et synopsis amplioris operis, ac habentur plura ejus ex exemplaria etiam sensorum impressa. Bononiensi Sci. Artum Inst. Atque Acad. Comment. 4, 353–396 (1757)Google Scholar
  27. 27.
    Boscovich, R.J.: De recentissimis graduum dimensionibus, et figura, ac magnitudine terrae inde derivanda. Philos. Recentioris Benedicto Stay Romano Arch. Publico Eloquentare Profr. Versibus Traditae Libri X Adnot. Suppl. P Rogerii Joseph Boscovich SJ Tomus II, 406–426 (1757)Google Scholar
  28. 28.
    Mason, C.H., Perreault Jr., W.D.: Collinearity, power, and interpretation of multiple regression analysis. J. Mark. Res., 268–280 (1991)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Rainer Schmidt
    • 1
  • Michael Möhring
    • 2
  • Stefan Maier
    • 2
  • Julia Pietsch
    • 2
  • Ralf-Christian Härting
    • 2
  1. 1.Hochschule MünchenMünchenGermany
  2. 2.Hochschule AalenAalenGermany

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