Abstract: Career coaching comprising defining a number of employment positions, wherein each employment position comprises a number of required skills. Relationships between the employment positions are modeled, wherein the model maps potential transitions between employment positions according to similarities of required skills. A number of persons who have occupied the employment positions are modeled according to skills, employment history, and job performance. A user provides user data that comprises skills, employment history, and job performance. The user data is compared to the modeled persons, and a number of potential employment opportunities from among the number of employment positions are matched to the user based on similarities between the user and the modeled persons. The potential employment opportunities are then displayed to the user on a graphical user interface.

Abstract: A method of testing a network node in a communication system includes obtaining a natural language requirement specification that describes a testing requirement associated with the network node, and selecting one or more test case specifications from a library of test case specifications based on the natural language requirement specification. The method includes extracting textual features from the test case specifications, generating a feature vector including the extracted textual features from the test case specifications, and mapping the feature vector to a plurality of available test scripts. One or more of the plurality of available test scripts are selected for execution in response to the mapping of the feature vector, and for one or more of the selected test scripts, a confidence score is generated that measures a confidence of an association of the test case specification with the selected test script. Related systems are also disclosed.

Abstract: A method, apparatus, system, and computer program code for digitally presenting a comparison of labor resource allocations between organizations. A computer system identifies employee data for a set of employees. The employee data includes job titles, and job descriptions. Using a set of machine learning models, the computer system extracts skills data from the job descriptions. Based on the skills data extracted from the job descriptions and using the set of machine learning models, the computer system maps the job titles to normalized titles within a job taxonomy that governs relationships between business functions, subfunctions, and the normalized titles. The computer system determines a resource allocation for an organization over each of the normalized titles. The computer system generates a granular comparison of the granular resource allocation to a set of benchmark allocations. The computer system digitally presents the granular comparison in a graphical user interface.

Abstract: Career coaching comprising defining a number of employment positions, wherein each employment position comprises a number of required skills. Relationships between the employment positions are modeled, wherein the model maps potential transitions between employment positions according to similarities of required skills. A number of persons who have occupied the employment positions are modeled according to skills, employment history, and job performance. A user provides user data that comprises skills, employment history, and job performance. The user data is compared to the modeled persons, and a number of potential employment opportunities from among the number of employment positions are matched to the user based on similarities between the user and the modeled persons. The potential employment opportunities are then displayed to the user on a graphical user interface.

Abstract: A method, an apparatus, and a computer program product for digitally presenting a statistically relevant business insights into a set of business metrics for an organization. A computer system generates a plurality of dimension aggregates for facts of human resources data across a plurality of different combinations of dimensions of human resources data. The computer system identifies a set of comparable aggregates among the plurality of dimension aggregates based on an intersection of the dimensions of human resources data among the different combinations. The computer system generates a set of statistics for each comparable aggregate of the set of comparable aggregates. The computer system generates a business insight into the set of business metrics of the organization based on the set of statistics for the set of comparable aggregates. The computer system digitally presents the business insight.

Abstract: A method, computer system, and computer program product for digitally presenting a human resource competitive model for an organization. A computer system identifies organizational data for the organization, including business metrics. The computer system determines a most similar group among a set of flexible comparison groups in each of a set of comparator categories by applying a set of comparison models to the organizational data. The computer system identifies a metrics distribution for the flexible comparison group based on benchmark metrics for a subset of benchmark organizations that has been grouped into the flexible comparison group. The computer system compares the business metrics for the organization to the metrics distribution for the flexible comparison group to determine a human resource competitive model for the organization across a set of business functions. The computer system digitally presents the human resource competitive model for the organization across the set of business functions.