Organizations providing large scale software and hardware maintenance support services typically capture detailed metrics of each service request (SR) for a customer. Examples of such metrics include the time taken to resolve the problem, success of the resolution, escalations across levels of support, field engineer site visit statistics, and parts replacement data - the latter two for hardware maintenance only. For some SRs, targeted customer surveys may be conducted to elicit feedback about how effectively the end-to-end problem resolution process was performed. Application of analytics to such data to enable continuous improvement of the operational efficiencies of providing maintenance services is an open area of research. This paper describes the authors' experience with several analytics projects in this domain. Improvement of maintenance support services can lead to faster and better problem resolution, leading to reduced down time and an increase in the overall resiliency of a computing environment.