Key Factors in Achieving Service Level Agreements (SLA) for Information Technology (IT) Incident Resolution

In this paper, we analyze the impact of various factors on meeting service level agreements (SLAs) for information technology (IT) incident resolution. Using a large IT services incident dataset, we develop and compare multiple models to predict the value of a target Boolean variable indicating whether an incident met its SLA. Logistic regression and neural network models are found to have the best performance in terms of misclassification rates and average squared error. From the best-performing models, we identify a set of key variables that influence the achievement of SLAs. Based on model insights, we provide a thorough discussion of IT process management implications. We suggest several strategies that can be adopted by incident management teams to improve the quality and effectiveness of incident management processes, and recommend avenues for future research.