Abstract: A method for predicting an impact of a service level agreement including collecting workload data and effort data and constructing a cost model for the service level agreement, defining a baseline service parameter corresponding to the code model of the service level agreement, and calibrating the cost model of the service level agreement, by calibrating a workload volume from the workload data and an effort time from the effort data to match the baseline service parameter, to output a service level agreement impact model.

Abstract: A method includes obtaining, by one or more processor, data related to a service level agreement for a service from a provider, wherein the service includes providing, to a client, network resources from a shared pool of network resources in a computing environment. The one or more processor utilizes the data to generate input parameters and these input parameters include target parameters for the service level agreement, penalty parameters for the service level agreement, and statistical process control parameters. The one or more processor analyzes the input parameters to model risk associated with probability of failure of the service from the provider in a given computing environment and generates and based on the risk model, allocating, by the one or more processor, a portion of the network resources.

Abstract: A method includes obtaining, by one or more processor, data related to a service level agreement for a service from a provider, wherein the service includes providing, to a client, network resources from a shared pool of network resources in a computing environment. The one or more processor utilizes the data to generate input parameters and these input parameters include target parameters for the service level agreement, penalty parameters for the service level agreement, and statistical process control parameters. The one or more processor analyzes the input parameters to model risk associated with probability of failure of the service from the provider in a given computing environment and generates and based on the risk model, allocating, by the one or more processor, a portion of the network resources.

Abstract: Statistical process control, performance distribution identification, and a simulation model based on, for example, Monte Carlo simulation, are used to calculate the risk of various service levels. A recommended service level is determined, the service level being one that is estimated to have an appropriate risk for both the outsourcing supplier and the customer.

Abstract: A method for predicting an impact of a service level agreement including collecting workload data and effort data and constructing a cost model for the service level agreement, defining a baseline service parameter corresponding to the code model of the service level agreement, and calibrating the cost model of the service level agreement, by calibrating a workload volume from the workload data and an effort time from the effort data to match the baseline service parameter, to output a service level agreement impact model.

Abstract: An approach for modeling a service delivery system is presented. Data from the service delivery system is collected. Discrete event simulation, queueing, and system heuristics models are constructed from the collected data. Based on the constructed models, a first utilization error indicating first variations among measures of utilization of staffing by the service delivery system is determined. Based on the first utilization error, a problem that causes the first variations is determined and in response, adjustments to the models to correct the problem are determined. A second utilization error is determined. The second utilization error indicates second variations among other measures of the utilization of staffing by the service delivery system which are based on the adjustments. Based on the second utilization error, a consistency among the adjusted models is determined, and in response, an initial recommended model of the service delivery system is derived.

Abstract: An approach for validating a model is presented. Data from a system being modeled is collected. First and second models of the system are constructed from the collected data. Based on the first model, a first determination of an aspect of the system is determined. Based on the second model, a second determination of the aspect of the system is determined. A variation between the first and second determinations is determined. An input for resolving the variation is received and in response, a model of the system that reduces the variation is derived.

Abstract: A method for managing performance of an IT service delivery process to ensure the changes meet service performance objectives. Key performance metrics (KPIs) of a service delivery process are collected in a continuous manner at defined time intervals, both before a change to improve performance is applied to the process (baseline measurements) and after a change is applied to the process (post-change measurements). A process behavior graph is generated comprising each baseline and post-change performance measurement at the time interval collected, the time interval at which the change was applied to the process, and the performance objectives for the process. The graph is displayed to a user to enable the user to determine the impact the change has on the service delivery process in view of differences between the baseline and post-change performance measurements, and to determine whether the process meets performance objectives in view of the performance objectives.

Abstract: A computer implemented method allocates resources within a workload management program. A computer identifies a first ratio for a first skill team of plurality of skill teams. The computer determines whether the first ratio for the first skill team exceeds a skill team threshold of the first skill team. Responsive to the computer determining that the first ratio for the first skill team exceeds the skill team threshold of the first skill team, the computer allocates the resources from at least one of the plurality of skill teams other than the first skill team to the first skill team. A computer program product and a computer system for allocating resources within a workload management program are also provided.

Abstract: A method for managing performance of an IT service delivery process to ensure the changes meet service performance objectives. Key performance metrics (KPIs) of a service delivery process are collected in a continuous manner at defined time intervals, both before a change to improve performance is applied to the process (baseline measurements) and after a change is applied to the process (post-change measurements). A process behavior graph is generated comprising each baseline and post-change performance measurement at the time interval collected, the time interval at which the change was applied to the process, and the performance objectives for the process. The graph is displayed to a user to enable the user to determine the impact the change has on the service delivery process in view of differences between the baseline and post-change performance measurements, and to determine whether the process meets performance objectives in view of the performance objectives.