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Understanding Requirements and Benefits of the Usage of Predictive Analytics in Management Accounting: Results of a Qualitative Research Approach

  • Rafi WadanEmail author
  • Frank TeutebergEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 353)

Abstract

The accuracy of a forecast affects the financial result of a company. By the improvement of Management Accounting (MA) processes, the introduction of advanced technology and additional skills is prognosticated. Even though companies have increasingly adopted Predictive Analytics (PA), the impact on MA overall has not been investigated adequately. This study investigates this problem through a single case study of a German company. The interview results provide an overview of requirements and benefits of PA in MA. In the future, Management Accountants will be able to focus on business partnering, but require advanced statistical knowledge to fully benefit from PA.

Keywords

Predictive Analytics Management Accounting Forecasting Competencies 

References

  1. 1.
    Cokins, G.: Top 7 trends in management accounting. Strateg. Financ. 95(6), 21–30 (2013)Google Scholar
  2. 2.
    Hofer, P., Eisl, C., Mayr, A.: Forecasting in Austrian companies; do small and large Austrian companies differ in their forecasting processes? J. Appl. Acc. Res. 16(3), 359–382 (2015)Google Scholar
  3. 3.
    Fabianová, J., Kačmáry, P., Molnár, V., Michalik, P.: Using a software tool in forecasting: a case study of sales forecasting taking into account data uncertainty. Open Eng. 6(1) (2016).  https://doi.org/10.1515/eng-2016-0033
  4. 4.
    Kerkkänen, A., Korpela, J., Huiskonen, J.: Demand forecasting errors in industrial context: measurement and impacts. Int. J. Prod. Econ. 118(1), 43–48 (2009)CrossRefGoogle Scholar
  5. 5.
    Seufert, A.: Die Digitalisierung als Herausforderung für Unternehmen: Status Quo, Chancen und Herausforderungen im Umfeld BI & Big Data. In: Fasel, D., Meier, A. (eds.) Big Data. EHMD, pp. 39–57. Springer, Wiesbaden (2016).  https://doi.org/10.1007/978-3-658-11589-0_3CrossRefGoogle Scholar
  6. 6.
    Lee, J., Elbashir, M.Z., Mahama, H., Sutton, S.G.: Enablers of top management team support for management control systems innovations. Int. J. Acc. Inf. Syst. 15, 1–25 (2014)CrossRefGoogle Scholar
  7. 7.
    Henke, N., et al.: The age of analytics: competing in a data-driven world. McKinsey Global Institute (2016)Google Scholar
  8. 8.
    Baesens, B., Bapna, R., Marsden, J.R., Vanthienen, J., Zhao, J.L.: Transformational issues of big data and analytics in networked business. MIS Q. 40(4), 807–818 (2016)CrossRefGoogle Scholar
  9. 9.
    Yoo, Y.: It is not about size. J. Inf. Technol. 30(1), 63–65 (2015)CrossRefGoogle Scholar
  10. 10.
    Leavitt, H.J.: Applied organizational change in industry: structural, technological and humanistic approaches. In: Handbook of Organizations, pp. 2976–3045 (2013)Google Scholar
  11. 11.
    Van den Broek, T., Van Veenstra, A.F.: Modes of governance in inter-organizational data collaborations. In: Proceedings of the 24th European Conference of Information Systems, Münster, Germany (2015)Google Scholar
  12. 12.
    Woerner, S., Wixom, B.H.: Big data: extending the business strategy toolbox. J. Inf. Technol. 30(1), 60–62 (2015)CrossRefGoogle Scholar
  13. 13.
    Redman, T.C.: Data Driven: Profiting from Your Most Important Business Asset. Harvard Business Press (2013). ISBN 978-1-4221-6364-1Google Scholar
  14. 14.
    Chatfield, A., Reddick, C., Al-Zubaidi, W.: Capability challenges in transforming government through open and big data: tales of two cities. In: Proceedings of the 36th International Conference on Information Systems, Fort Worth, USA (2015)Google Scholar
  15. 15.
    Taipaleenmäki, J., Ikäheimo, S.: On the convergence of management accounting and financial accounting – the role of information technology in accounting change. Int. J. Acc. Inf. Syst. 14, 321–348 (2013)CrossRefGoogle Scholar
  16. 16.
    Warren Jr., J.D., Moffitt, K.C., Byrnes, P.: How big data will change accounting. Account. Horiz. 29(2), 397–407 (2015)CrossRefGoogle Scholar
  17. 17.
    Schwegmann, B., Matzner, M., Janiesch, C.: A method and tool for predictive event-driven process analytics. In: 11. Internationale Tagung Wirtschaftsinformatik (WI), Merkur, pp. 721–735 (2013)Google Scholar
  18. 18.
    Breuker, D., Matzner, M., Delfmann, P., Becker, J.: Comprehensible predictive models for business processes. MIS Q. 40(4), 1009–1034 (2016)CrossRefGoogle Scholar
  19. 19.
    Huikku, J., Hyvönen, T., Järvinen, J.: The role of a predictive analytics project initiator in the integration of financial and operational forecasts. Baltic J. Manage. 12(4), 427–446 (2017)CrossRefGoogle Scholar
  20. 20.
    Granlund, M.: Extending AIS research to management accounting and control issues: a research note. Int. J. Acc. Inf. Syst. 12, 3–19 (2011)CrossRefGoogle Scholar
  21. 21.
    Elbashir, M.Z., Collier, P.A., Sutton, S.G.: The role of organizational absorptive capacity in strategic use of business intelligence to support integrated management control system. Acc. Rev. 86, 155–184 (2011)CrossRefGoogle Scholar
  22. 22.
    Yin, R.K.: Case Study Research: Design and Methods, 4th edn. Thousand Oaks Zahra (2009)Google Scholar
  23. 23.
    Flyvbjerg, B., Budzier, A.: Why your IT project may be riskier than you think. Harvard Bus. Rev. 89(9), 601–603 (2011)Google Scholar
  24. 24.
    Booth, P., Matolcsy, Z., Wieder, B.: The impacts of enterprise resource planning systems on accounting practice - the Australian experience. Aust. Acc. Rev. 10(3), 4–18 (2000)CrossRefGoogle Scholar
  25. 25.
    Lamnek, S.: Methoden und Techniken. Qualitative Sozialforschung (Band 2), 2. Auflage, Benz, Weinheim, p. 102 (1993)Google Scholar
  26. 26.
    Laforest, J.: Safety diagnosis tool kit for local communities. In: Guide to Organizing Semi-Structured Interviews with Key Informants. Institut national de sante publ., Quebec (2009)Google Scholar
  27. 27.
    Henttu-Aho, T., Järvinen, J.: A field study of the emerging practice of beyond budgeting in industrial companies: an institutional perspective. Eur. Acc. Rev. 22, 765–785 (2013)CrossRefGoogle Scholar
  28. 28.
    Grabski, S., Leech, S., Schmidt, P.: A review of ERP research: a future agenda for accounting information systems. J. Inf. Syst. 25(1), 37–78 (2011)Google Scholar
  29. 29.
    Brands, K., Holtzblatt, M.: Business analytics: transforming the roles of management accountants. Manage. Acc. Q. 16(3), 1–12 (2015)Google Scholar
  30. 30.
    King, M.F., Bruner, G.C.: Social desirability bias: a neglected aspect of validity testing. Psychol. Mark. 17(2), 79–103 (2000)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Universität OsnabrückOsnabrückGermany

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