Self-training machine-learning system for generating and providing action recommendations

An apparatus comprising at least one processor, at least one communications interface, a user interface, and at least one memory including computer program code, the at least one memory and computer program code configured to, with the processor, cause the apparatus to at least:

• cause display of an interactive user interface (IUI) via the user interface of the apparatus, wherein:
• the IUI comprises an action list comprising one or more action items each corresponding to one or more team members of a team,
• the one or more action items are automatically ordered based on one or more action priorities,
• at least one of the one or more action items corresponds to a coaching opportunity and a recommendation for responding to the coaching opportunity,
• the coaching opportunity is automatically identified using a recommendation model trained using machine learning based at least in part on performance data corresponding to a plurality of key performance indicator metrics,
• the recommendation for responding to the coaching opportunity is determined (a) using the recommendation model trained using machine learning and (b) based on the performance data corresponding to the plurality of key performance indicator metrics, and
• the recommendation model is trained using information regarding previous handlings of coaching opportunities and corresponding outcome indicators for a cluster of teams.

A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code portions stored therein, the computer-executable program code portions, when executed by a processor of computing entity, are configured to cause the computing entity to at least:

• cause display of an interactive user interface (IUI) via a user interface of the computing entity, wherein:
• the IUI comprises an action list comprising one or more action items each corresponding to one or more team members of a team,
• the one or more action items are automatically ordered based on one or more action priorities,
• at least one of the one or more action items corresponds to a coaching opportunity and a recommendation for responding to the coaching opportunity,
• the coaching opportunity is automatically identified using a recommendation model trained using machine learning based at least in part on performance data corresponding to a plurality of key performance indicator metrics,
• the recommendation for responding to the coaching opportunity is determined (a) using the recommendation model trained using machine learning and (b) based on the performance data corresponding to the plurality of key performance indicator metrics, and
• the recommendation model is trained using information regarding previous handlings of coaching opportunities and corresponding outcome indicators for a cluster of teams.