Fuzzy analytic hierarchy process prioritization of key performance indicators in IT service management

Purpose To achieve a more concrete measurement of service quality, this paper proposes a prioritization model of key performance indicators (KPIs) that monitors the service quality of IT service management processes. Design/methodology/approach Phase one establishes the baseline of process performance and enables the acquisition of customer perceptions via the ITIL framework’s “Maturity Self-Assessment Questionnaire.” Phase two defines (KPIs) for each process activity and their adherence to the SMART criteria, then, the fuzzy analytical hierarchy process (FAHP) assigns weights to the KPIs, enabling a hierarchical performance system. Finally, the FAHP approach is implemented in a case study. Findings The proposed prioritization model produced a set of KPIs with different weights, where those with the highest weights are selected to represent the “Process KPIs.” Integrating fuzzy logic into AHP eliminates both the uncertainty and the reduced reliability associated with the traditional form of the AHP’s evaluation of attribute importance through pairwise comparison. Originality/value The study aspires to investigate the possibility of deploying a multi-criteria decision-making model for prioritizing implemented KPIs. The evaluation system for index development uses the analytical hierarchy process method combined with the deployment of fuzzy logic sets, which define human knowledge using mathematical expressions. Fuzzy sets and logic express satisfaction preferences of personal evaluation amongst other information analysis concerns. This can effectively assist IT service managers in devising high-level KPIs to monitor and improve service quality continuously.