• DocumentCode
    589145
  • Title

    Streamlining Service Levels for IT Infrastructure Support

  • Author

    Palshikar, G.K. ; Mudassar, M. ; Vin, H.M. ; Natu, Maitreya

  • Author_Institution
    Tata Res. Dev. & Design Centre, Tata Consultancy Services Ltd., Pune, India
  • fYear
    2012
  • fDate
    10-10 Dec. 2012
  • Firstpage
    309
  • Lastpage
    316
  • Abstract
    For IT Infrastructure Support (ITIS), it is crucial to identify opportunities for reducing service costs and improving service quality. We focus on streamlining service levels i.e., finding right resolution level for each ticket, to reduce time, efforts and cost for ticket handling, without affecting workloads and user satisfaction. We formalize this problem and present two statistics-based search algorithms for identifying problems suitable for left-shift (from expensive, expertise intensive L2 level to cheaper, simpler L1 level) and right-shift (from L1 to L2). The approach is domain-driven: it produces directly usable and often novel results, without any trial-and error experimentation, along with detailed justifications and predicted impacts. This helps in acceptance among end-users and more active use of the results. We discuss one real-life case-study of results produced by the algorithms.
  • Keywords
    business data processing; cost reduction; data mining; resource allocation; search problems; text analysis; IT infrastructure support; ITIS; data mining; domain-driven approach; end-user acceptance; left-shift; right-shift; service cost reduction; service level management process; service quality improvement; statistics-based search algorithms; ticket handling cost reduction; time reduction; user satisfaction; Algorithm design and analysis; Business; Data mining; Databases; Prediction algorithms; Software; Training; Customer Support; Domain-driven Data-mining; IT infrastructure Support; ITIL; Service quality; Support Analytics; Ticket routing; Workforce management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on
  • Conference_Location
    Brussels
  • Print_ISBN
    978-1-4673-5164-5
  • Type

    conf

  • DOI
    10.1109/ICDMW.2012.118
  • Filename
    6406456