Abstract: Various embodiments for enterprise skill development using cognitive computing, by a processor device, are provided. In one embodiment, a method comprises applying cognitive computing to analyze user data from an information system to identify a user's Enterprise Skills Index (ESI) of enterprise skills and skill-gaps by inputting and analyzing a plurality of indices for average achievement within the enterprise.

Abstract: Mechanisms are provided, in a hierarchical feedback aggregation (HFA) system implemented in one or more data processing systems, for collecting and presenting user feedback information for a composite offering. A backend engine of the HFA system, implemented in a first data processing system, registers a hierarchical feedback model for the composite offering. A frontend engine of the HFA system, implemented in a second data processing system, receives user feedback for an identified component of the composite offering. The backend engine of the HFA system generates an aggregate user feedback score for the identified component based on a combination of the user feedback for the identified component and aggregate user feedback scores for child components of the identified component in the hierarchical feedback model. The backend engine outputs a representation of the generated aggregate user feedback score for the component to a user.

Abstract: Mechanisms are provided to implement a brand comparison engine. The mechanisms receive a request to compare brand personalities of a first specified brand and a second specified brand and obtain a first brand personality scale associated with the first specified brand and a second brand personality scale associated with the second specified brand. The mechanisms calculate at least one gap value indicating a difference between at least one personality trait in the first brand personality scale and a corresponding at least one personality trait in the second brand personality scale. The mechanisms also output an output indicating an aspect of the at least one gap based on the calculation.

Abstract: A method and apparatus for the automatic suggestion generation in a relationship management system is described. The method may include obtaining an electronic communication associated with one or more users of a relationship management system, where the communication is part of a series of communications in a process managed by the relationship management system. Furthermore, the method may include analyzing content of the electronic communication to determine a suggested future action within the process managed by the relationship management system. The method may also include generating a suggestion by the relationship management system to notify at least one user of the suggested future action, and storing the generated suggestion within a database coupled with the relationship management system.

Abstract: Computerized methods and systems for improving engagement with a recommendation engine that recommends items, peers, and services are provided. Stored data of a plurality of users is electronically accessed and analyzed. A respective passive profile is determined for each of the users based on the analyzing of the stored data. The respective passive profiles are then stored for use by the recommendation engine. The recommendation engine can then provide recommendations for at least one of items, peers, and services to a respective user based on at least the respective passive profile. The recommendations may be further based on at least one of an explicit profile comprising information provided by the respective user and an activity profile based on tracked activity of the respective user with regard to prior recommended items.

Abstract: According to one aspect, embodiments of the invention provide a crowd management planning system, the system comprising a plurality of store servers configured to be coupled to a network, and a central server, the central server comprising an interface configured to be coupled to the network, a database, and a crowd planning module coupled to the interface and the database and configured to communicate with each one of the plurality of store servers, wherein the crowd planning module is further configured to provide a crowd planning tool to at least one of the plurality of store servers, receive crowd planning information from the at least one of the plurality of store servers based on users' interactions with the crowd planning tool, and store the received crowd planning information in the database.

Abstract: Embodiments are directed towards to managing operations for an organization. An operation engine may be employed to provide operations metrics based on events and resolution actions associated with an incident. Update information may be provided to console modules included in operations command consoles (OCCs) each console module may include module views. The console modules may be employed to provide data objects to the module views. The module views may be employed to provide different visualizations of the incident based on a role that may be associated with the console modules. An OCC may be employed to provide other resolution actions to the operations engine and then that operations engine may provide additional update information to the console modules based on the other resolution actions.

Abstract: Mechanisms are provided, in a hierarchical feedback aggregation (HFA) system implemented in one or more data processing systems, for collecting and presenting user feedback information for a composite offering. A backend engine of the HFA system, implemented in a first data processing system, registers a hierarchical feedback model for the composite offering. A frontend engine of the HFA system, implemented in a second data processing system, receives user feedback for an identified component of the composite offering. The backend engine of the HFA system generates an aggregate user feedback score for the identified component based on a combination of the user feedback for the identified component and aggregate user feedback scores for child components of the identified component in the hierarchical feedback model. The backend engine outputs a representation of the generated aggregate user feedback score for the component to a user.

Abstract: Mechanisms are provided to implement a brand personality perception gap assessment engine. The mechanisms receive an inferred brand personality for a specified brand. The mechanisms further receive an intended brand personality for the specified brand. The mechanisms calculate at least one gap between the inferred brand personality and the intended brand personality. The mechanisms output an output indicating aspects of the at least one gap.

Abstract: Mechanisms are provided to implement a brand comparison engine. The mechanisms receive a request to compare brand personalities of a first specified brand and a second specified brand and obtain a first brand personality scale associated with the first specified brand and a second brand personality scale associated with the second specified brand. The mechanisms calculate at least one gap value indicating a difference between at least one personality trait in the first brand personality scale and a corresponding at least one personality trait in the second brand personality scale. The mechanisms also output an output indicating an aspect of the at least one gap based on the calculation.