Advertisement

Quantifying the Complexity of IT Service Management Processes

  • Yixin Diao
  • Alexander Keller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4269)

Abstract

Enterprises and service providers are increasingly looking to process-based automation as a means of containing and even reducing the labor costs of systems management. However, it is often hard to quantify and predict the additional complexity introduced by IT service management processes before they actually have been deployed. Our approach consists in looking at this problem from a different, new perspective by regarding complexity as a surrogate for potential labor cost and human-error-induced problems: In order to effectively evaluate the benefits of IT service management processes – and to target the types of processes that contribute most to management complexity and cost – we need a set of metrics for quantifying the complexity and human cost of carrying out IT service management processes. This paper proposes such measures, and demonstrates how they can be applied to a typical service delivery process in order to assess its complexity hotspots as a basis for process re-engineering.

Keywords

Eclipse Modeling Framework Scalable Vector Graphic Complexity Score Eclipse Modeling Framework Model Process Complexity Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    IT Infrastructure Library. ITIL Service Support, version 2.3. Office of Government Commerce (June 2000)Google Scholar
  2. 2.
    Brown, A.B., Keller, A., Hellerstein, J.L.: A Model of Configuration Complexity and its Application to a Change Management System. In: Clemm, A., Festor, O., Pras, A. (eds.) Proc. of the 9th IFIP/IEEE International Symposium on Integrated Management (IM 2005), Nice, France, pp. 631–644. IEEE, Los Alamitos (2005)Google Scholar
  3. 3.
    Budinsky, F., Merck, E., Steinberg, D.: Eclipse Modeling Framework, 2nd edn. Addison-Wesley, Reading (2006)Google Scholar
  4. 4.
    Couch, A.L., Wu, N., Susanto, H.: Toward a Cost Model for System Administration. In: Blank-Edelman, D.N. (ed.) Proc. 19th Large Installation System Administration Conference (LISA 2005), San Diego, CA, USA, pp. 125–141. USENIX (December 2005)Google Scholar
  5. 5.
    Kubicki, C.: The System Administration Maturity Model – SAMM. In: Proc. 7th Large Installation System Administration Conference (LISA 1993), Monterey, CA, USA, pp. 213–225. USENIX (November 1993)Google Scholar
  6. 6.
    Li, M.: An Introduction to Kolmogorov Complexity and Its Applications. Springer, Heidelberg (1997)CrossRefMATHGoogle Scholar
  7. 7.
    Patterson, D.: A Simple Way to Estimate the Cost of Downtime. In: Couch, A.L. (ed.) Proc. 16th Large Installation System Administration Conference (LISA 2005), Philadelphia, PA, USA, pp. 185–188. USENIX (November 2002)Google Scholar
  8. 8.
    Service Data Objects, http://www.eclipse.org/emf/sdo.php
  9. 9.
    Tennant, G.: Six Sigma: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd. (2001)Google Scholar
  10. 10.
  11. 11.
    World Wide Web Consortium, W3C Recommendation. Scalable Vector Graphics (SVG) 1.1 Specification (January 2003), http://www.w3.org/TR/SVG/

Copyright information

© IFIP International Federation for Information Processing 2006

Authors and Affiliations

  • Yixin Diao
    • 1
  • Alexander Keller
    • 1
  1. 1.IBM T.J. Watson Research CenterYorktown HeightsUSA

Personalised recommendations