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From Big Data to Smart Data – Problemfelder der systematischen Nutzung von Daten in Unternehmen

  • Steffen WölflEmail author
  • Alexander Leischnig
  • Björn Ivens
  • Daniel Hein
Chapter

Zusammenfassung

Die zunehmende Digitalisierung von Geschäftsprozessen, Leistungen oder sogar ganzen Geschäftsmodellen bietet Unternehmen vielfältige Möglichkeiten zur Wertgenerierung mit Daten. Die zielgerichtete und systematische Verarbeitung und Nutzung von Daten stellt Unternehmen verschiedener Branchen jedoch vor große Herausforderungen. Der vorliegende Beitrag gibt einen Überblick über grundlegende Prozesse der systematischen Verarbeitung und Nutzung von Daten in Unternehmen. Darüber hinaus diskutiert der Beitrag mögliche Problemfelder, die bei der Nutzung von Daten entstehen können und gibt Handlungsempfehlungen, wie Unternehmen diese Herausforderungen bewältigen können.

Literatur

  1. Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: cognitive absorption and beliefs about information technology usage. MIS Quarterly, 29(4), 665–694.Google Scholar
  2. Akter S., Wamba S. F., Gunasekaran A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment?. International Journal of Production Economics, 18(2), 113–131.Google Scholar
  3. Alavi, M., & Leidner, D. E. (2001). Knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136.Google Scholar
  4. Audzeyeva A., & Hudson, R. (2016). How to get the most from a business intelligence application during the post implementation phase? Deep structure transformation at a U.K. retail bank. European Journal of Information Systems, 25(1), 29–46.Google Scholar
  5. Barton, D., & Court, D. (2012). Making advanced analytics work for you. Harvard Business Review, 90(10), 78–83.Google Scholar
  6. Barua, A., Konana, P., Whinston, A. B., & Yin, F. (2004). An empirical investigation of net-enabled business value. MIS Quarterly, 28(4), 585–620.Google Scholar
  7. Berners-Lee, T., & Shadbolt, N. (2011). There’s gold to be mined from all our data. The Times 1: 1–2. http://www.thetimes.co.uk/tto/opinion/columnists/article3272618.ece, Zugegriffen: 28. Feb. 2018.
  8. Bernstein, P. A., & Haas, L. M. (2008). Information integration in the enterprise. Communications of the ACM, 51(9), 72–79.Google Scholar
  9. Bertolucci, J. (2015). Big data success remains elusive. InformationWeek. http://www.informationweek.com/big-data/big-data-analytics/big-data-success-remains-elusive-study/d/d-id/1318891, Zugegriffen: 28. Feb. 2018.
  10. Bhatt, G. D. (2000). An empirical examination of the effects of information systems integration on business process improvement. International Journal of Operations & Production Management, 20(11), 1331–1359.CrossRefGoogle Scholar
  11. Bischoff, S., Aier, S., Haki, M. K., & Winter, R. (2015). Understanding continuous use of business intelligence systems: a mixed methods investigation. JITTA: Journal of Information Technology Theory and Application, 16(2), 5–38.Google Scholar
  12. Brown, B., Chui, M., & Manyika, J. (2011). Are you ready for the era of ‚big data‘?. McKinsey Quarterly, 4(1), 24–35.Google Scholar
  13. Brynjolfsson, E., Hitt, L. M., & Kim, H. H. (2011). Strength in numbers: How does data-driven decision-making affect firm performance?. Social Science Research Network. https://ssrn.com/abstract=1819486.
  14. Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314–347.Google Scholar
  15. Chen, D. Q., Preston, D. S., & Swink, M. (2015). How the use of big data analytics affects value creation in supply chain management. Journal of Management Information Systems, 32(4), 4–39.Google Scholar
  16. Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: from big data to big impact. MIS Quarterly, 36(4), 1165–1188.Google Scholar
  17. Chen, M. S., Han, J., & Yu, P. S. (1996). Data mining: an overview from a database perspective. IEEE Transactions on Knowledge and Data Engineering, 8(6), 866–883.Google Scholar
  18. Choo, C. W., Bergeron, P., Detlor, B., & Heaton, L. (2008). Information culture and information use: an exploratory study of three organizations. Journal of the Association for Information Science and Technology, 59(5), 792–804.Google Scholar
  19. Clarke, R. (2016). Big data, big risks. Information Systems Journal, 26(1), 77–90.CrossRefGoogle Scholar
  20. Cress, U., Kimmerle, J., Hesse, F. W. (2006). Information exchange with shared databases as a social dilemma: the effect of metaknowledge, Bonus Systems, and Costs. Communication Research, 33(5), 370–390.CrossRefGoogle Scholar
  21. Davenport, T. H. & Harris, J. G. (2007). Competing on Analytics: The New Science of Winning. Boston: Harvard Business School Press.Google Scholar
  22. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.CrossRefGoogle Scholar
  23. De Luca, L. M. D., & Atuahene-Gima, K. (2007). Market knowledge dimensions and cross-functional collaboration: examining the different routes to product innovation performance. Journal of Marketing, 71(1), 95–112.Google Scholar
  24. Dobre, C., & Xhafa, F. (2014). Intelligent services for big data science. Future Generation Computer Systems, 37, 267–281.Google Scholar
  25. Duan, Y., & Cao, G. (2015). Understanding the impact of business analytics on innovation. Proceedings of the 23rd European Conference on Information Systems, Muenster, Germany.Google Scholar
  26. Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2): 897–904.Google Scholar
  27. Ghasemaghaei, M., Ebrahimi, S., & Hassanein, K. (2017). Data analytics competency for improving firm decision making performance. Journal of Strategic Information Systems, in press.Google Scholar
  28. Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: an organizational capabilities perspective. Journal of Management Information Systems, 18(1): 185–214.Google Scholar
  29. Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information and Management, 53(8): 1049–1064.Google Scholar
  30. Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98–115.Google Scholar
  31. Hazen, B. T., Boone, C. A., Ezell, J. D., & Jones-Farmer, L. A. (2014). Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications. International Journal of Production Economics, 154, 72–80.Google Scholar
  32. He, J & King, W. R. (2008). The role of user participation in information systems development: implications from a meta-analysis. Journal of Management Information Systems, 25(1), 301–331.Google Scholar
  33. Hitt, L., Jin, F., & Wu, L. (2015). Data skills and value of social media: evidence from large-sample firm value analysis. Proceedings of the 36th International Conference on Information Systems, Fort Worth, TX.Google Scholar
  34. Jayachandran, S., Sharma, S., Kaufman, P., & Raman, P. (2005). The role of relational information processes and technology use in customer relationship management. Journal of Marketing, 69(4), 177–192.Google Scholar
  35. Kautz, K., & Mahnke, V. (2003). Value creation through IT-supported knowledge management? The utilisation of a knowledge management system in a global consulting company. Informing Science, 6, 75–88.Google Scholar
  36. Kettinger, W. J., & Marchand, D. A. (2011). Information management practices (IMP) from the senior manager’s perspective: an investigation of the IMP construct and its measurement. Information Systems Journal, 21(5), 385–406.Google Scholar
  37. Kettinger, W. J., Zhang, C., & Chang, K. C. (2013). Research note – A view from the top: integrated information delivery and effective information use from the senior executive’s perspective. Information Systems Research, 24(3), 842–860.Google Scholar
  38. Klein, R. & Rai, A. (2009). Interfirm strategic information flows in logistics supply chain relationships. MIS Quarterly, 33(4), 735–762.Google Scholar
  39. Kohli, A. K., & Jaworski, B. J. (1990). Market orientation: the construct, research propositions, and managerial implications. Journal of Marketing, 54(2), 1–18.Google Scholar
  40. LaValle, S., Lesser, E., Shockley, R., Hopkins, M. S., & Kruschwitz, N. (2011). Big data, analytics and the path from insights to value. Sloan Management Review, 52(2), 21–31.Google Scholar
  41. Leischnig, A., Wölfl, S., Ivens, B., & Hein, D. (2017). From digital business strategy to market performance: insights into key concepts and processes. Proceedings of the 38th International Conference on Information Systems, Seoul, South Korea.Google Scholar
  42. Li, G., Lin, Y., Wang, S., & Yan, H. (2006). Enhancing agility by timely sharing of supply information. Supply Chain Management: An International Journal, 11(5), 425–435.Google Scholar
  43. Lycett, M. (2013). ‚Datafication‘: Making sense of (big) data in a complex world. European Journal of Information Systems, 22(4), 381–386.CrossRefGoogle Scholar
  44. Marr, B. (2015). Where big data projects fail. Forbes. https://www.forbes.com/sites/bernardmarr/2015/03/17/where-big-data-projects-fail/#2dbe1db2239f. Zugegriffen: 28. Feb. 2018.
  45. Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Review: Information technology and organizational performance: an integrative model of IT business value. MIS Quarterly, 28(2), 283–322.Google Scholar
  46. Menon, A., & Varadarajan, P. R. (1992). A model of marketing knowledge use within firms. Journal of Marketing, 56(4), 53–71.Google Scholar
  47. Moorman, C. (1995). Organizational market information processes: cultural antecedents and new product outcomes. Journal of Marketing Research, 32(3), 318–335.CrossRefGoogle Scholar
  48. Morgan, N. A., Anderson, E. W., & Mittal, V. (2005). Understanding firms’ customer satisfaction information usage. Journal of Marketing, 69(3), 131–151.Google Scholar
  49. Otto, B. (2011). Organizing data governance: findings from the telecommunications industry and consequences for large service providers. Communications of the Association for Information Systems, 29(1), 45–66.Google Scholar
  50. Pearson, T., & Wegener, R. (2013). Big data: the organizational challenge. Report from Bain and Company, San Francisco, CA. http://www.bain.com/Images/BAIN_BRIEF_Big_Data_The_organizational_challenge.pdf. Zugegriffen: 28. Feb. 2018.
  51. Phillips-Wren, G. E., & Hoskisson, A. (2014). Decision support with big data: a case study in the hospitality industry. Decision Support Systems, 2, 401–413.Google Scholar
  52. Reid, F. J. M., Malinek, V., Stott, C. J. T., & Evans, J. B. T. (1996). The messaging threshold in computer-mediated communication. Ergonomics, 39, 1017–1037.Google Scholar
  53. Ringel, M., Taylor, A., & Zablit, H. (2017). The most innovative companies 2016. Boston Consulting Group.Google Scholar
  54. Roberts, N., & Grover, V. (2012). Leveraging information technology infrastructure to facilitate a firm’s customer agility and competitive activity: an empirical investigation. Journal of Management Information Systems, 28(4), 231–270.Google Scholar
  55. Rollins, M., & Halinen, A. (2005). Customer knowledge management competence: towards a theoretical framework. Proceedings of the 38th Annual Hawaii International Conference on System Sciences, Hawaii, USA.Google Scholar
  56. Rowley, J. (2007). The wisdom hierarchy: representations of the DIKW hierarchy. Journal of Information Science, 33(2), 163–180.CrossRefGoogle Scholar
  57. Russom, P. (2008). Data requirements for advanced analytics. TDWI Checklist Report.Google Scholar
  58. Schroeck, M., Shockley, R., Smart, J., Romero-Morales, D., & Tufano, P. (2012). Analytics: the real-world use of big data. IBM Global Business Services, 12, 1–20.Google Scholar
  59. Sivarajah, U., Kamal, M.M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of big data challenges and analytical methods. Journal of Business Research, 70, 263–286.Google Scholar
  60. Tambe, P. (2014). Big data investment, skills, and firm value. Management Science, 60(6), 1452–1469.CrossRefGoogle Scholar
  61. Van den Driest, F., Sthanunathan, S., & Weed, K. (2016). Building an insights engine. Harvard Business Review, 94(9), 64–74.Google Scholar
  62. Van Alstyne, M., Brynjolfsson, E., & Madnick, S. (1995). Why not one big database? Principles for data ownership. Decision Support Systems, 15(4), 267–284.Google Scholar
  63. Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: what data quality means to data consumers. Journal of Management Information Systems, 12(4), 5–33.Google Scholar
  64. Watson, H. J. (2014). Tutorial: big data analytics: concepts, technologies, and applications. Communications of the Association for Information Systems, 34, 1247–1268.Google Scholar
  65. Wedel, M., & Kannan, P. K. (2016). Marketing analytics for data-rich environments. Journal of Marketing, 80(6), 97–121.Google Scholar
  66. Wölfl, S., Leischnig, A., Ivens, B., & Hein, D. (2017). Analytics, innovativeness, and innovation performance. Proceedings of the 38rd International Conference on Information Systems, Seoul, South Korea.Google Scholar
  67. Yi, X., Liu, F., Liu, J., & Jin, H. (2014). Building a network highway for big data: architecture and challenges. IEEE Network, 28(4), 5–13.Google Scholar

Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  • Steffen Wölfl
    • 1
    Email author
  • Alexander Leischnig
    • 2
  • Björn Ivens
    • 3
  • Daniel Hein
    • 1
  1. 1.Otto-Friedrich-Universität BambergBambergDeutschland
  2. 2.School of Business and ManagementQueen Mary University of LondonLondonUK
  3. 3.Lehrstuhl für Betriebswirtschaftslehre, insbesondere Vertrieb und MarketingOtto-Friedrich-Universität BambergBambergDeutschland

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