Skip to Main Content
In IT service delivery, alignment of service infrastructures to continuously changing business requirements is a primary cost driver, all the more as most severe service disruptions can be attributed to poor change impact and risk assessment. An IT service, defined as a means to provide value to a consumer, may be realized by a network of shared application and other resources that are invoked in the context of business processes. In the spirit of service-oriented architecture (SOA) we consider each application or resource as a service. Changing services or service definitions in such an environment includes exceptionally high risk and complexity, as various business processes might depend on a service. In this paper we propose a model for analyzing the business impact of operational risks resulting from change related service downtimes of uncertain duration. The proposed solution takes into account the network of dependencies between services where services may or may not be realized through business processes. Based on the analytical model, we derive decision models in terms of deterministic and probabilistic mathematical programming formulations to schedule single or multiple correlated changes efficiently. Preliminary experiments are described to illustrate the efficiency of the proposed models. Using these decisions models, organizations can schedule service changes with the lowest expected impact on the business.