Method and system for employee assesment

A system for identification of high potential employees;

• said system comprising a processor and a memory coupled to the processor, comprising computer implemented instruction to:
• generate, a Human Capital Value (HCV) data model, wherein the HCV data model comprises attributes for each employee of an organization;
• receive, one or more employees to be classified into high potential employees and non-high potential employees;
• receive, all attributes for the one or more employees from the HCV data model;
• select, a plurality of attributes as important attributes for the one or more employees from all attributes, wherein selection is based on either a plurality of feature extraction techniques or user input;
• generate a combined attribute set, wherein generating a combined attribute set comprises:
• ranking the plurality of attributes based on distinguishing capability among high potential employees and non-high potential employees;
• and
• combining, a predefined number of top ranking attributes of each of the plurality of feature extraction technique;
• and
• identify, the high potential employees, by labelling each of the one or more employees as high potential employees or non-high potential employees wherein the labelling is performed using at least one of classification model based approach and reference set based approach and is based on the combined attribute set.

A computer program product for controlling access to a resource of an electronic device, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:

• generating, a Human Capital Value (HCV) data model, wherein the HCV data model comprises attributes for each employee of an organization;
• receiving, one or more employees to be classified into high potential employees and non-high potential employees;
• receiving, all attributes for the one or more employees from the HCV data model;
• selecting, a plurality of attributes as important attributes for the one or more employees from all attributes, wherein selection is based on either a plurality of feature extraction techniques or user input;
• generating a combined attribute set, wherein generating a combined attribute set comprises:
• ranking the plurality of attributes based on distinguishing capability among high potential employees and non-high potential employees;
• and
• combining, a predefined number of top ranking attributes of each of the plurality of feature extraction technique;
• and
• identifying, the high potential employees, by labelling each of the one or more employees as high potential employees or non-high potential employees wherein the labelling is performed using at least one of classification model based approach and reference set based approach and is based on the combined attribute set.