US 11,238,409 B2 · Techniques for extraction and valuation of proficiencies for gap detection and remediation

Abstract

Gaps in proficiencies may be identified within an enterprise. Understanding gaps in the existing workforce may help inform training, hiring, and firing decisions to ensure successful completion of the upcoming projects and deadlines. Using a multi-level model for each proficiency that accounts for enterprise needs as well as hiring, retraining, and the like, a relationship between proficiencies, projects, and employees over time may be generated as a multi-dimensional temporal model. The temporal model may be simulated to forecast gaps in proficiencies of the employed workforce. Recommendations regarding retraining, hiring, and termination can be made to help users remedy the deficiencies. Additionally, the proficiencies most valuable to the enterprise may be determined using a catalog of proficiencies to cluster the proficiencies into proficiency clusters for each job or job category and the proficiencies scored. Employees and candidates may be scored using the clusters to inform hiring, firing, and retraining decisions.

Claims15

Dependent claims

A method comprising:

generating, by a computer system, a plurality of multi-level models, wherein:
each multi-level model comprises a neural network that is trained using a machine-learning process to approximate partial differential equations-based proficiency gap computations for one of a plurality of proficiencies for an enterprise;
and
the enterprise comprises a plurality of individuals;
generating, by the computer system, a multi-dimensional temporal model based on the plurality of multi-level models;
identifying, by the computer system, one or more gaps in proficiencies for the enterprise as a whole based on executing the multi-dimensional temporal model;
determining, by the computer system, one or more recommendations to remedy the one or more gaps, wherein the one or more recommendations are generated based on boundary condition constrained simulations and the multi-dimensional temporal model;
and
transmitting, by the computer system, the one or more recommendations to a user device for display to a user.

6 more elements

A non-transitory computer-readable memory storing a plurality of instructions executable by one or more processors, the plurality of instructions comprising instructions that when executed by the one or more processors cause the one or more processors to perform processing comprising:

generating a plurality of multi-level models, wherein:
each multi-level model comprises a neural network that is trained using a machine-learning process to approximate partial differential equations-based proficiency gap computations for one of a plurality of proficiencies for an enterprise;
and
the enterprise comprises a plurality of individuals;
generating a multi-dimensional temporal model based on the plurality of multi-level models;
identifying one or more gaps in proficiencies for the enterprise as a whole based on executing the multi-dimensional temporal model;
determining one or more recommendations to remedy the one or more gaps, wherein the one or more recommendations are generated based on boundary condition constrained simulations and the multi-dimensional temporal model;
and
transmitting the one or more recommendations to a user device for display to a user.

6 more elements

Dependencies are inferred from the claim text.

Techniques for extraction and valuation of proficiencies for gap detection and remediation

Life of this patent

Techniques for extraction and valuation of proficiencies for gap detection and remediation

Life of this patent

Abstract

Claims15