CLIAMS:1. A method for evaluating performance of organizational units using Human Capital Value (HCV), the method comprising:
receiving, by a processor (202), input data spread across an enterprise from a user, wherein the input data comprises employee data, project related data, and organizational unit data for performance evaluation;
analyzing, by the processor (202), the input data for generating HCV variables, wherein the HCV variables are stored in a repository (108);
parsing, by the processor (202), the HCV variables to determine whether each of plurality of HCV variables is one of an input variable, an output variable, and a variable to be neglected;
based on the parsing, determining, by the processor (202), an optimal set of variables; and
computing, by the processor (202), an efficiency of the each organizational unit based on the determining, the computing being based on Multi Criteria Decision Analysis (MCDA) techniques, wherein the organizational units are ranked in a decreasing order based on the computing.

2. The method as claimed in claim 1, wherein the parsing is based on the rankings assigned to the organizational units, the rankings belong to the optimal set of variables where all variables are one of known, partially known, and not known.

3. The method as claimed in claim 1 further comprising calculating, by the processor (202), an auxiliary measure value for the each organizational unit, wherein the calculation is based on auxiliary variables, derived from the optimal set of variables and data pertaining to the optimal set of variables.

4. The method as claimed in claim 2 further comprising providing, by the processor (202), auxiliary ranks to the each organizational unit based on the auxiliary measure value.

5. The method as claimed in claim 3 further comprising comparing the ranks and auxiliary ranks of the each organizational unit, wherein based on the comparison, the rankings are validated.

6. The method as claimed in claim 1, wherein the MCDA technique comprises one of a CCR model, a dual form CCR model, a cross efficiency model, and a super efficiency model.

7. The method as claimed in claim 1, wherein the computing comprises ranking the organizational units based on weights given to each variable.

8. The method as claimed in claim 7, wherein the weights are associated with main criteria and at least one sub-criteria of the organizational unit.

9. The method as claimed in claim 1, wherein the computing comprises identifying, by the processor (202), the organizational units as performance outliers.

10. The method as claimed in claim 1, wherein the determining is based on one of domain knowledge, a fractional factorial model, and an automatic model discovery.

11. An evaluation system (100) for evaluating performance of organizational units using Human Capital Value (HCV), the evaluation system (100) comprising:
a processor (202);
a variable generator module (212), executable by the processor (202) to:
receive input data spread across an enterprise from a user, wherein the input data comprises employee data, project related data, and organizational unit data for performance evaluation; and
analyze the input data for generating HCV variables, wherein the HCV variables are stored in a repository (108); and
an evaluation module (110), executable by the processor (202), to:
compute efficiency of the each organizational unit based on identification, wherein the computation is based on Multi Criteria Decision Analysis (MCDA) techniques; and
rank each of the organizational unit based on the efficiency of the each organizational unit.

12. The evaluation system (100) as claimed in claim 11, further comprising a selection module (214), executable by the processor (202), to:
parse each of the HCV variables to determine whether each of the HCV variables is an input variable, an output variable, or a variable to be neglected; and
identify an optimal set of input-output variables from the HCV variables.

13. The evaluating system (100) as claimed in claim 11 further comprises an auxiliary module (216), executable by the processor (202), to:
calculate an auxiliary measure value for the each organizational unit, wherein the calculation is based on auxiliary variables, derived from the optimal set of variables and data pertaining to the optimal set of variables; and
provide auxiliary ranks to the each organizational unit based on the auxiliary measure value.

14. The evaluating system (100) as claimed in claim 11, wherein the MCDA technique comprises one of a Data Envelopment Analysis (DEA) method, a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, and an Analytic Hierarchy Process (AHP), and wherein the DEA method comprises a CCR model, a dual form CCR model, a cross efficiency model, and a super efficiency model.

15. The evaluating system (100) as claimed in claim 11 further comprises a validation module (218), executable by the processor (202), to compare the ranks and auxiliary ranks of the each organizational unit, wherein based on the comparison the rankings are validated.
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