Abstract: A first device may provide, via a global digital twin of the first device, a communication mode assignment, of a communication mode, to a local digital twin of a second device. The communication mode assignment is to cause the local digital twin to communicate with the global digital twin via the communication mode. The first device may generate, via the global digital twin, a task assignment, and may provide, via the global digital, the task assignment to the local digital twin. The first device may update, via the global digital twin, a model based on the task assignment, and may receive, via the global digital twin and from the local digital twin, a model update associated with the local digital twin. The first device may update, via the global digital twin, the model based on the model update.

Abstract: A method and associated systems for predicting when a resource will become critical to a business. A processor of a computer system identifies a resource as being capable of becoming critical to a business by identifying a historic impact of the resource as a function of prior incidents during which a disruption of the resource had resulted in a severe impact upon the business. The processor further identifies performance parameters and social parameters that were related to these prior periods of criticality and uses these parameters, along with real-time measurements of the performance parameters, to derive a performance index and a social business index that allow the processor to determine whether the resource will become critical during a current or future time period. The processor represents this current or future period of criticality as a pulse-width modulated waveform that may be further processed by automated means.

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 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.