Intelligent scheduling of events

A system for intelligent scheduling of events, comprising:

• one or more computers with executable instructions that when executed cause the system to:
• receive, by a processor executing the executable instructions, data from a plurality of data sources each storing information associated with each member of a plurality of group members;
• generate, by the processor, a machine learning model having learned relationships and responsibilities interdependent within the plurality of group members according to an analyzation of the data;
• determine, by the processor according to the machine learning model, one or more members from the plurality of group members to assign one or more events thereto according to the learned relationships and responsibilities associated with the one or more events and the plurality of group members, wherein the one or more events include documented events and non-documented events learned based on the learned relationships and responsibilities, and wherein certain events of the documented events and the non-documented events are identified as needing to be requisitely performed at certain, non-prescheduled times in order for the one or more members to participate in subsequent events of the one or more events;
• cognitively and automatically schedule, by the processor, the one or more events as assigned to the one or more members, wherein the one or more members are optimally selected from the plurality of group members to be assigned particular tasks of the one or more events according to a ranking based on a plurality of factors related to the learned relationships and responsibilities determined using the machine learning model, and wherein automatically scheduling the one or more events includes notifying those of the one or more members that sub-events of the certain events must be completed at a certain time, as determined by the automatic scheduling, to complete the certain events identified as needing to be requisitely performed to thereby subsequently participate in the subsequent events of the one or more events;
• detect, by the processor using sensor data collected by a user device associated with the one or more members, an anomaly that will cause the one or more members assigned to the one or more events unable to perform the scheduled one or more events;
• and
• cognitively reassign, by the processor, the one or more events to an alternative member of the plurality of group members having a rigidity factor above a predetermined threshold such that the alternative member of the plurality of group members assumes sole responsibility to perform the one or more events, wherein, commensurate with the reassigning, a timing and location of the one or more events remains unchanged.

A computer program product for intelligent scheduling of events by a processor, the computer program product comprising a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:

• an executable portion that receives, by the processor, data from a plurality of data sources each storing information associated with each member of a plurality of group members;
• an executable portion that generates, by the processor, a machine learning model having learned relationships and responsibilities interdependent within the plurality of group members according to an analyzation of the data;
• an executable portion that determines, by the processor according to the machine learning model, one or more members from the plurality of group members to assign one or more events thereto according to the learned relationships and responsibilities associated with the one or more events and the plurality of group members, wherein the one or more events include documented events and non-documented events learned based on the learned relationships and responsibilities, and wherein certain events of the documented events and the non-documented events are identified as needing to be requisitely performed at certain, non-prescheduled times in order for the one or more members to participate in subsequent events of the one or more events;
• an executable portion that cognitively and automatically schedules, by the processor, the one or more events as assigned to the one or more members, wherein the one or more members are optimally selected from the plurality of group members to be assigned particular tasks of the one or more events according to a ranking based on a plurality of factors related to the learned relationships and responsibilities determined using the machine learning model, and wherein automatically scheduling the one or more events includes notifying those of the one or more members that sub-events of the certain events must be completed at a certain time, as determined by the automatic scheduling, to complete the certain events identified as needing to be requisitely performed to thereby subsequently participate in the subsequent events of the one or more events;
• an executable portion that detects, by the processor using sensor data collected by a user device associated with the one or more members, an anomaly that will cause the one or more members assigned to the one or more events unable to perform the scheduled one or more events;
• and
• an executable portion that cognitively reassigns, by the processor, the one or more events to an alternative member of the plurality of group members having a rigidity factor above a predetermined threshold such that the alternative member of the plurality of group members assumes sole responsibility to perform the one or more events, wherein, commensurate with the reassigning, a timing and location of the one or more events remains unchanged.