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Gaining Insight from Operational Data for Service Optimization

  • Kristof Kloeckner
  • John Davis
  • Nicholas C. Fuller
  • Giovanni Lanfranchi
  • Stefan Pappe
  • Amit Paradkar
  • Larisa Shwartz
  • Maheswaran Surendra
  • Dorothea Wiesmann
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

Service optimization is key in the drive to further automate and increase the effi-ciency of the services provided to clients. A given client may be ahead, in one or more areas, versus where other clients are. Learning from these best-of-breed cli-ents benefits the other clients in optimizing their services. Each of the clients normally generates a large number of data points for all the elements comprising the services they consume. Important data points are generally contained within incident tickets and change tickets. These tickets contain not only information about the nature of the issue, but also contain resolution information.

Notes

Acknowledgements

This work was done through collaboration of IBM Research and Technical services, and authors are grateful to Sinem Guven, Karin Murthy, Jin Xiao, Anup Kalia and Sander Plug for their contribution.

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Copyright information

© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Kristof Kloeckner
    • 1
  • John Davis
    • 2
  • Nicholas C. Fuller
    • 3
  • Giovanni Lanfranchi
    • 1
  • Stefan Pappe
    • 4
  • Amit Paradkar
    • 3
  • Larisa Shwartz
    • 3
  • Maheswaran Surendra
    • 5
  • Dorothea Wiesmann
    • 6
  1. 1.Global Technology ServicesIBM (United States)ArmonkUSA
  2. 2.Global Technology ServicesIBM (United Kingdom)HursleyUK
  3. 3.IBM Research DivisionIBM (United States)Yorktown HeightsUSA
  4. 4.Global Technology ServicesIBM (Germany)MannheimGermany
  5. 5.Global Technology ServicesIBM (United States)Yorktown HeightsUSA
  6. 6.IBM Research DivisionRüschlikonSwitzerland

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