Analysis of a Personalized Provision of Service Level Agreement (SLA) Algorithm

Abstract

The existence of restricted Service Level Agreement (SLA) choices, which typically correspond with a couple of service tiers, can result in a customer accepting a service that may not effectively respond to their needs. From a service provider perspective, it is also a less than optimum business model, with capacity being reserved for customers who will not use it and subsequently being unavailable for customers who would. We, therefore, advocate the use of personalized SLAs to avoid such situations, which can ideally be set up without the assistance of a human operator. We suggest classifying customers according to their distinguishing features, one of which includes a customer’s propensity to have online devices in their home. Through the results presented in this paper, we are confident about the accuracy of our classification results; however, we recognize that there are opportunities for latency improvements in the efficiency of the process.