Development of an Incident Prioritization Model Using Fuzzy Logic to Improve Quality and Productivity in IT Support Services

  • Dristesh Hoorpah
  • Somveer KishnahEmail author
  • Sameerchand Pudaruth
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 863)


Managing a high volume of incidents is a very complicated task for companies which provide support services. The application support analysts as well as managers must effectively assess the level of importance of incidents during the day to better prioritize each of them. As this process is very complex and time consuming, a lot of efforts are spent in the incident prioritization activity, which is manually carried out by the first level support team and by the analysts at the start of their shift and during the workday by going through each of the incidents and determining the order on which they need to be worked on. Bad incident prioritization leads to a decrease in quality of service as analysts fail to manage customers’ expectations and this impacts productivity. To reduce this problem, a system which allows prioritization of incidents was proposed. To implement the solution, the range of factors which contributes to determine the priority of an incident was identified and a survey was conducted in multiple companies involved in ITSM to determine the importance of each of these factors. A fuzzy logic approach was formulated to determine the final priority of an incident. The results show a 19% increase in productivity and a 9% increase in quality of service.


Service management Fuzzy logic Incident prioritization 


  1. 1.
    Schütze, R.: An intuitionistic fuzzy approach for service level management. In: Improving Service Level Engineering. Fuzzy Management Methods. Springer, Cham (2018)Google Scholar
  2. 2.
    The HP IT Service Management (ITSM) Reference Model.
  3. 3.
    van Bon, J.: Foundations of ITIL® V3 (Best Practice IT Management). Van Haren Publishing, The Netherlands (2007)Google Scholar
  4. 4.
    Sarnovsky, M., Surma, J.: Predictive models for support of incident management process in IT service management. Acta Electrotechnica et Informatica 18(1), 57–62 (2018)CrossRefGoogle Scholar
  5. 5.
    European Network and Information Security Agency: Good Practice Guide for Incident Management. ENISA, Greece (2010)Google Scholar
  6. 6.
    Microsoft Operations Framework. (2018)
  7. 7.
    Kempter, S.: Checklist Incident Priority. IT Process Wiki. (2018)
  8. 8.
    Zadeh, L.A.: A very simple formula for aggregation and multicriteria optimization. Int. J. Uncertainty Fuzziness Knowl.-Based Syst. 24(6), 961–962 (2016)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Dabbagh, M., Lee, S.: An approach for prioritizing NFRs according to their relationship with FRs. Lecture Notes on Software Engineering, vol. 3, issue 1, pp. 1–5 (2015)Google Scholar
  10. 10.
    Ruby, Balkishan: Fuzzy logic based requirement prioritization (FLRP)—an approach. Int. J. Comput. Sci. Technol. 6(3), 61–65 (2015)Google Scholar
  11. 11.
    Mamdani, E., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud. 7(1), 1–13 (1975)CrossRefGoogle Scholar
  12. 12.
    Chaudhary, N., Sangwan, O., Singh, Y.: Test case prioritization using fuzzy logic for GUI-based software. Int. J. Adv. Comput. Sci. Appl. 3(12), 222–227 (2012)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Dristesh Hoorpah
    • 1
  • Somveer Kishnah
    • 1
    Email author
  • Sameerchand Pudaruth
    • 1
  1. 1.University of MauritiusReduitMauritius

Personalised recommendations