Simulation-Based Quantification of Business Impacts Caused by Service Incidents

  • Axel Kieninger
  • Florian Berghoff
  • Hansjörg Fromm
  • Gerhard Satzger
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 143)

Abstract

Today, business processes heavily depend on IT, so that business results are affected by the quality of supporting IT services. To gauge the quality of service from a business point of view, we need to consider the service incidents that occur over a reference period and evaluate the effect of each service incident individually. In this work, we address this problem by developing a procedure to monetarily quantify the negative impact of single service incidents on the service customer business.

We first review related literature to identify approaches to quantifying the negative consequences associated with a service incident. Based on our findings, we propose a simulation-based procedure for estimating the monetary impact. Contrary to existing approaches, we first apply business process simulation as a formal analysis technique to determine the effects of single service incidents on process performance. Then, the impact on process performance is translated into its monetary equivalent.

Keywords

IT Service Management Business Impact Analysis Discrete-event Business Process Simulation 

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References

  1. 1.
    Sauvé, J., Moura, A., Sampaio, M., Jornada, J., Radziuk, E.: An introductory overview and survey of business-driven IT management. In: 1st IEEE/IFIP International Workshop on Business-Driven IT Management, Vancouver, pp. 1–10 (2006)Google Scholar
  2. 2.
    OGC: IT infrastructure library (ITIL): Service operation. The Stationary Office (TSO), London (2007)Google Scholar
  3. 3.
    Kieninger, A., Satzger, G., Straeten, D., Schmitz, B., Baltadzhiev, D.: Business Cost Budgets: A Methodology to Incorporate Business Impact into Service Level Agreements. International Journal of Service Science, Management, Engineering, and Technology 3(3), 49–64 (2012)CrossRefGoogle Scholar
  4. 4.
    Franke, U.: Optimal IT service availability: Shorter outages, or fewer? IEEE Transactions on Network and Service Management 9(1), 22–33 (2012)CrossRefGoogle Scholar
  5. 5.
    Kieninger, A., Straeten, D., Kimbrough, S., Schmitz, B., Satzger, G.: Leveraging Service Incident Analytics to Determine Cost-Optimal Service Offers. In: 11th International Conference on Wirtschaftsinformatik. AIS, Leipzig (forthcoming, 2013)Google Scholar
  6. 6.
    Webster, J., Watson, T.: Analyzing the past to prepare for the future: Writing a literature review. MIS Quarterly 26(2), xiii–xxiii (2002)Google Scholar
  7. 7.
    Wiedemann, J.: IT-Notfallvorsorge im betrieblichen Risikomanagement: Entwicklung eines Gestaltungsmodells unter Berücksichtigung ökonomischer Aspekte am Beispiel einer TK-Unternehmung. Ph. D. thesis, Bochum (2008)Google Scholar
  8. 8.
    Suh, B., Han, I.: The IS risk analysis based on a business model. Information and Management 41(2), 149–158 (2003)CrossRefGoogle Scholar
  9. 9.
    Moura, A., Sauvé, J., Jornada, J., Radziuk, E.: A quantitative approach to IT investment allocation to improve business results. In: 7th IEEE International Workshop on Policies for Distributed Systems and Networks, pp. 87–95. IEEE Computer Society, London (2006)CrossRefGoogle Scholar
  10. 10.
    Jin, L.-J., Machiraju, V., Sahai, A.: Analysis on service level agreement of web services. Technical report, HP Laboratories (2002)Google Scholar
  11. 11.
    Jakoubi, S., Tjoa, S., Goluch, S., Kitzler, G.: A formal approach towards risk-aware service level analysis and planning. In: International Conference on Availability, Reliability, and Security, pp. 180–187. IEEE Computer Society, Krakow (2010)CrossRefGoogle Scholar
  12. 12.
    Patterson, D.: A simple way to estimate the cost of downtime. In: 16th USENIX Conference on System Administration, pp. 185–188. ACM, Berkeley (2002)Google Scholar
  13. 13.
    Dübendorfer, T., Wagner, A., Plattner, B.: An economic damage model for large-scale internet attacks. In: 13th IEEE International Workshop on Enabling Technologies: Infrastructures for Collaborative Enterprises, pp. 223–228. IEEE Computer Society, Modena (2004)CrossRefGoogle Scholar
  14. 14.
    van Hee, K.M., Reijers, H.A.: Using Formal Analysis Techniques in Business Process Redesign. In: van der Aalst, W.M.P., Desel, J., Oberweis, A. (eds.) BPM 2000. LNCS, vol. 1806, pp. 142–160. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  15. 15.
    Tumay, K.: Business process simulation. In: 28th Winter simulation conference, pp. 55–60. IEEE Computer Society Press, Crystal City (1995)CrossRefGoogle Scholar
  16. 16.
    Schwalbe, K.: Information technology project management. Thomson Course Technology, Cambridge (2006)Google Scholar
  17. 17.
    Hlupic, V., Robinson, S.: Business process modelling and analysis using discrete-event simulation. In: 30th Winter Simulation Conference, pp. 1363–1370. IEEE Computer Society Press, Los Alamitos (1998)Google Scholar
  18. 18.
    Kelton, W., Sadowski, R., Sturrock, D.: Simulation with Arena. McGraw-Hill Higher Education, Boston (2004)Google Scholar
  19. 19.
    Rosenkranz, F.: Geschäftsprozesse: Modell- und computergestützte Planung. Springer, Berlin (2006)Google Scholar
  20. 20.
    Greasley, A.: Using business process simulation within a business process reengineering approach. Business Process Management Journal 9(4), 408–420 (2003)CrossRefGoogle Scholar
  21. 21.
    Gaver Jr., D.P.: A waiting line with interrupted service, including priorities. Journal of the Royal Statistical Society 24(1), 73–90 (1962)Google Scholar
  22. 22.
    Banks, J.: Handbook of Simulation: Principles, Methodology, Advances, Applications, and Practice. Wiley, New York (1998)Google Scholar
  23. 23.
    Pang, G., Whitt, W.: Service interruptions in large-scale service systems. Management Science 55(9), 1499–1512 (2009)CrossRefGoogle Scholar
  24. 24.
    Bartholdi, J., Hackman, S.: Warehouse & distribution science: Release 0.95, http://www.warehouse-science.com

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Axel Kieninger
    • 1
  • Florian Berghoff
    • 1
  • Hansjörg Fromm
    • 1
  • Gerhard Satzger
    • 1
  1. 1.Karlsruhe Service Research InstituteKarlsruhe Institute of TechnologyKarlsruheGermany

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