DESC:METHOD AND SYSTEM FOR EMPLOYEE ASSESSMENT ,CLAIMS:1. A method for identification of high potential employees; said method comprising processor implemented steps of:
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.

2. The method according to claim 1, wherein the HCV data model is generated based on attributes of each employee, such that attributes are extracted from a backend database of an employee organization’s enterprise application wherein the attributes comprise demographics, skill set, organizational experiences, training and certifications, efforts and project related data of an employee.

3. The method according to claim 1, wherein the plurality attributes are selected using a plurality of feature extraction techniques such that the plurality of feature extraction techniques comprise one or more of Weka based feature extraction techniques.

4. The method according to claim 1, wherein the classification model based approach comprises:
using at least one of Weka based classification techniques for classification of employees; and
ranking the employees based on the combined attribute set wherein the higher ranked employees are labelled as high potential employees.

5. The method according to claim 1, wherein the reference set based approach comprises:
performing principle component analysis (PCA) on the selected plurality of attributes;
receiving a reference set of employees comprising employees who are identified as high performance employees on the basis of having exceptional attributes than others, wherein the reference set is created based on predefined criteria;
calculating, the distance between the one or more employees and the reference set of employees, wherein distances calculation dataset is under PCA space and uses Mahalanobis distance calculation approach;
deriving, a threshold value of distance using quartile statistics; and
labelling each of the plurality of employees below the threshold value as high potential employees.

6. 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.

7. The system according to claim 6, wherein the HCV data model is generated based on attributes of each employee, such that attributes are extracted from a backend database of an employee organization’s enterprise application wherein the attributes comprise demographics, skill set, organizational experiences, training and certifications, efforts and project related data of an employee.

8. The system according to claim 6, wherein the plurality attributes are selected using a plurality of feature extraction techniques such that the plurality of feature extraction techniques comprise one or more of Weka based feature extraction techniques.

9. The method according to claim 6, wherein the classification model based approach comprises:
using at least one of Weka based classification techniques for classification of employees; and
ranking the employees based on the combined attribute set wherein the higher ranked employees are labelled as high potential employees.

10. The method according to claim 6, wherein the reference set based approach comprises:
performing principle component analysis (PCA) on the selected plurality of attributes;
receiving a reference set of employees comprising employees who are previously identified as high performance employees, wherein the reference set is based on predefined criteria;
calculating, the distance between the one or more employees and the reference set of employees, wherein distances calculation dataset is under PCA space and uses Mahalanobis distance calculation approach;
deriving, a threshold value of distance using quartile statistics; and
labelling each of the plurality of employees below the threshold value as high potential employees.