Claims:We claim:
1. A method of evaluating performance of one or more employees (101) of an organization, the method comprising:
providing, by a performance evaluating system (107), a review matrix corresponding to one of plurality of review contexts assigned to one or more recommenders (103) on corresponding end user devices (105);
receiving, by a performance evaluating system (107), a feedback in the review matrix for each of the one or more employees (101) from the one or more recommenders (103), wherein the feedback comprises a recommender’s review score and review comments;
generating, by the performance evaluating system (107), a system review score for each of the one or more employees (101) by analysing the review comments;
computing, by the performance evaluating system (107), a compound review score for each of the one or more employees (101) for each of the plurality of review contexts using the recommender’s review score and the system review score;
computing, by the performance evaluating system (107), a cumulative evaluation score for each of the one or more employees (101) using the compound review score generated for each of the plurality of review contexts, predefined organizational weights and historical evaluation score of each of the one or more employees (101); and
analysing, by the performance evaluating system (107), the cumulative evaluation score of each of the one or more employees (101) to evaluate performance of each of the one or more employees (101).
2. The method as claimed in claim 1 further comprises ranking, by the performance evaluation system, each of the one or more employees (101) based on their respective cumulative evaluation score.

3. The method as claimed in claim 1 further comprises clustering, by the performance evaluation system, the one or more employees (101) depicting equivalent performance based on the ranking and the analysis.

4. The method as claimed in claim 1 further comprises computing, by the performance evaluation system, appraisal rewards to be allotted to each of the one or more employees (101) present in each cluster based on a predefined criteria.

5. The method as claimed in claim 1, wherein the system review score is generated by analysing the review comments using Natural Language Processing (NLP) technique.

6. The method as claimed in claim 1, wherein computing the compound review score comprises:
computing, by the performance evaluating system (107), a Square Error (SE) value between the recommender’s review score and the system review score corresponding to the review context for each of the one or more recommenders (103);

comparing, by the performance evaluating system (107), the SE value with a predefined SE threshold to identify a first weightage value corresponding to the recommender’s review score and a second weightage value corresponding to the system review score; and
correlating, by the performance evaluating system (107), the recommender’s review score with the first weightage value and the system review score with the second weightage value to generate the compound review score.
7. The method as claimed in claim 1, wherein computing the cumulative evaluation score comprises:
correlating, by the performance evaluating system (107), the compound review score of each of the plurality of review contexts with the corresponding predefined organizational weights to generate a current evaluation score for each of the one or more employees (101); and
correlating, by the performance evaluating system (107), the current evaluation score of each of the one or more employees (101) with their respective historical evaluation scores to generate the cumulative evaluation score.
8. The method as claimed in claim 1, wherein the recommender’s review score is generated by averaging individual scores provided for each review parameter in the review matrix by each of the one or more recommenders (103).
9. An performance evaluating system (107) for evaluating performance of one or more employees (101) of an organization, the performance evaluating system (107) comprising:
a processor (109); and
a memory (113) communicatively coupled to the processor (109), wherein the memory (113) stores the processor-executable instructions, which, on execution, causes the processor (109) to:
provide a review matrix corresponding to one of plurality of review contexts assigned to one or more recommenders (103) on corresponding end user devices (105);
receive a feedback in the review matrix for each of the one or more employees (101) from the one or more recommenders (103), wherein the feedback comprises a recommender’s review score and review comments;
generate a system review score for each of the one or more employees (101) by analysing the review comments;
compute a compound review score for each of the one or more employees (101) for each of the plurality of review contexts using the recommender’s review score and the system review score;
compute a cumulative evaluation score for each of the one or more employees (101) using the compound review score generated for each of the plurality of review contexts, predefined organizational weights and historical evaluation score of each of the one or more employees (101); and
analyse the cumulative evaluation score of each of the one or more employees (101) to evaluate performance of each of the one or more employees (101).
10. The performance evaluating system (107) as claimed in claim 9, wherein the processor (109) is further configured to rank each of the one or more employees (101) based on their respective cumulative evaluation score.

11. The performance evaluating system (107) as claimed in claim 9, wherein the processor (109) is further configured to cluster the one or more employees (101) depicting equivalent performance based on the ranking and the analysis.

12. The performance evaluating system (107) as claimed in claim 9, wherein the processor (109) is further configured to compute appraisal rewards to be allotted to each of the one or more employees (101) present in each cluster based on a predefined criteria.

13. The performance evaluating system (107) as claimed in claim 9, wherein the processor (109) generates the system review score by analysing the review comments using Natural Language Processing (NLP) technique.

14. The performance evaluating system (107) as claimed in claim 9, wherein, to compute the compound review score, the instructions cause the processor (109) to:
compute a Square Error (SE) value between the recommender’s review score and the system review score corresponding to the review context for each of the one or more recommenders (103);

compare the SE value with a predefined SE threshold to identify a first weightage value corresponding to the recommender’s review score and a second weightage value corresponding to the system review score; and
correlate the recommender’s review score with the first weightage value and the system review score with the second weightage value to generate the compound review score.
15. The performance evaluating system (107) as claimed in claim 9, wherein, to compute the cumulative evaluation score, the instructions cause the processor (109) to:

correlate the compound review score of each of the plurality of review contexts with the corresponding predefined organizational weights to generate a current evaluation score for each of the one or more employees (101); and
correlate the current evaluation score of each of the one or more employees (101) with their respective historical evaluation scores to generate the cumulative evaluation score.

16. The performance evaluating system (107) as claimed in claim 9, wherein the processor (109) generates the recommender’s review score by averaging individual scores provided for each review parameter in the review matrix by each of the one or more recommenders (103).

Dated this 18th day of October2017

SWETHA S N
OF K & S PARTNERS
AGENT FOR THE APPLICANT
, Description:TECHNICAL FIELD
The present subject matter relates generally to data analytics, and more particularly, but not exclusively to a method and a system for evaluating performance of one or more employees of an organization.