Competency-Assessment-at-MEPL-5

Competency Based Assessment

By HR, 3EA
Competency Based Assessment

With the consistently advancing and broadening business challenges, the approach with the management of human resources has additionally experienced a paradigm shift. The upper hand accomplished through innovation, technology, new items and data is transitory and immensely volatile. The main distinctive attribute among competitors which stays, are the abilities and commitment from the employees. The administrative headship accordingly has an essential impact as they straightforwardly impact the performance and the members of the company. A finely characterized and uniform competency system is the initial move towards a sorted-out way to deal with the human asset management of the association.

There is a consistent need to build effectiveness and create and deliver value in every deal. Along these lines it is basic that a more scientific approach like competencies be utilized to characterize and comprehend the learning, aptitudes and state of mind required to play out a job efficaciously. Assessing an employee's performance in view of pre-characterized competencies and their behavioral patterns, thusly is called competency based assessment (CBA).

Abstract
We assisted a top Education & Training Institute by prescribing a procedure to comprehend their employees' potential which they needed to factor in their organizational growth plans. They wanted to have a reasonable thought on their present talent pool in order to choose their talent gradient to fuel their dynamic growth plans. The HR team of 3EA interacted with the employers of this institute & realized that their need is more in terms of surveying the non-technical competencies.

Research Methodology
Data Collection Method & Tools

  • Primary Data Collection

    A questionnaire containing 50 situation-based questions was designed & was methodically surveyed across all the branches of the institute in 69 cities, 21 states.

    We effectively characterized the competencies, rating scales and created customized evaluation simulations. The HR group of the institute alongside our team at 3EA successfully planned the venue and schedules. Three to four panels assisted & carried out the assessments, standardizations & consolidations of the evaluations. About 200 employees of the institute appeared for the competency based structured interview. Based on their answers, they were evaluated for six competencies viz. Emotional Intelligence Quotient, Ability to work under pressure, Entrepreneurship Quotient, Adaptability Quotient, Leadership Quotient & last but not the least Loyalty Quotient.

  • Tools

    MS Excel was used for Data Understanding, Cleaning, Preparing & making Dashboards.

    IBM SPSS Statistics 20 was used for Data Analysis

    SQL Server Reporting Services (SSRS) was used to automate the reports of each employee.

  • Data Analysis

    With the help of SPSS, I carried out the method of Correlation & Regression.

    • Correlation

      Pearson's r & Scatterplot was computed to assess the relationship among the 6 variables. In this case, the two hypotheses were-
      H0: There is no correlation between the pair of parameters
      H1: There is correlation between the pair of parameters

    • Linear Regression
      Firstly, to check whether the assumptions of Linear Regression are met or not I ran a test for Multicollinearity & Heteroscedasticity
      a)Test for Multicollinearity was done by checking Variance Inflation Factor (1/Tolerance).
      b) Test Heteroskedasticity Glejser to check Heteroscedasticity-

      H0: There is no problem of Heteroscedasticity
      H1: There is problem of Heteroscedasticity
      After that I proceeded with Linear Regression

    • Independent t- Test
      a)Levene's Test for Equality of Variances between Males & Females
      b)t-Test for Equality of Means between Males & Females

    • Chi-Square Test of Association-
      a)Gender*EIQ
      b)Gender * Ability to work under pressure
      c)Gender * Entrepreneurship

  • Results from Data Analysis

    • Correlation

      1.There was a strong correlation between EIQ & AWUP [r= 0.534, p=0.0001]
      2.There was a strong correlation between AQ & AWUP [r= 0.523, p=0.0001]
      3.There was a moderate correlation between AQ & Loyalty [r= 0.484, p=0.0001]
      4.There was a weak correlation between EIQ & Entrepreneurship [r= 0.317, p=0.0001]
      5.There was a weak to moderate correlation between EIQ & AQ [r= 0.367, p=0.0001]

      The correlation between EIQ & AWUP was more than that between AQ & AWUP.

    • Linear Regression

      a)Test for Multicollinearity-
      Since, the VIF<10 for all predictor or independent variables There was no multicollinearity.

      b)Heteroskedasticity Glejser for Heteroscedasticity –
      Since p-Value for all independent variable > 0.05, the null hypothesis, H0 was accepted There was no problem of Heteroscedasticity.
      Thus, I proceeded with the Linear regression

    Linear Regression 1:

    Dependent Variable-
    Ability to Work Under Pressure
    Predictor Variables/ Independent Variables- Emotional Intelligence Quotient, Loyalty Quotient, Leadership Quotient, Emotional Intelligence Quotient, Entrepreneurship, Adaptability Quotient

    Emotional Intelligence Quotient (EIQ) & Adaptability Quotient (AQ) are positively correlated with 'Ability to Work Under Pressure' (AWUP). Rest of the parameters, were not associated with 'Ability to work under pressure'.

    H0: Predictors don't predict AWUP
    H1: Predictors predict AWUP

    Results-

    i.We rejected the null hypotheses H0 for EIQ & AQ as p- Value 0.05 EIQ & AQ predict AWUP
    ii.Unadjusted R Squared= 0.40 40% Variance in AWUP is explained by EIQ & AQ (overall measure of the strength of association)
    iii.Regression Equation for AWUP:
    AWUP=4.70+(0.41XEIQ)+(0.48XAQ)

    • For every unit increase in EIQ, a 0.41-unit increase in AWUP is predicted, holding all other variables constant.

    • For every unit increase in AQ, a 0.49-unit increase in AWUP is predicted, holding all other variables constant.

    i.As Beta= 0.415 in EIQ Coefficients Table & Beta= 0.435 in AQ Coefficients, i. e. Beta weight of AQ> Beta weight of EIQ, relative importance of AQ is slightly higher than that of EIQ.

    ii.Residuals approximate a normal curve

    Linear Regression 2:
    Dependent Variable-
    Adaptability Quotient
    Predictor Variables/ Independent Variables- Emotional Intelligence Quotient, Loyalty Quotient, Leadership Quotient, Emotional Intelligence Quotient, Entrepreneurship, Ability to Work Under Pressure

    'Ability to work under pressure' (AWUP) & Loyalty Quotient (LOQ) were positively correlated with 'Adaptability Quotient' (AQ). Rest of the parameters, were not associated with AQ

    H0: Predictors don't predict AWUP
    H1: Predictors predict AWUP

    Results-
    i.We rejected the null hypotheses H0 for AWUP & LOQ as p-Value 0.05 AWUP & LOQ predict AQ
    ii.Unadjusted R Squared= 0.42 => 42% Variance in AQ is explained by AWUP & LOQ (overall measure of the strength of association)
    iii.Regression Equation for AWUP:
    AWUP = 2.85+(0.40XAWUP)+(0.32XLOq)

    • For every unit increase in AWUP, a 0.40-unit increase in AQ is predicted, holding all other variables constant.

    • For every unit increase in LOQ, a 0.32-unit increase in AQ is predicted, holding all other variables constant.

    iv.As Beta= 0.421 in AWUP Coefficients Table & Beta= 0.378 in LOQ Coefficients, i. e. Beta weight of AWUP> Beta weight of LOQ, relative importance of AWUP is slightly higher than that of LOQ.
    v.Residuals approximate a normal curve

  • Independent t- Test

    a) Levene's Test for Equality of Variances between Males & Females

    H0: The variances of Male & Female are equal
    H1: The variances of Male & Female are equal are not equal
    As the p- Values for all the parameters >0.05, Male & Female don't have equal variances.

    b) t-Test for Equality of Means between Males & Females

    H0: There is no significance difference between Male & Female for Emotional IQ, Ability to Work Under Pressure, Entrepreneurship, Adaptability Quotient, Leadership Quotient & Loyalty Quotient
    H1: There is significance difference between Male & Female for Emotional IQ, Ability to Work Under Pressure, Entrepreneurship, Adaptability Quotient, Leadership Quotient & Loyalty Quotient
    As, p-Values for all the parameters are > 0.05, there was no significant mean difference between Male & Female for all the 6 parameters.

  • Chi-Square Test of Association-

    Gender*EIQ


    H0: There is no association between gender i.e. being male or female and EIQ
    H1: There is an association between being male or female and EIQ
    Since, p-value= 0.925> 0.05 (d.f.= 8), the null hypothesis was accepted => There was no association between gender i.e. being male or female and EIQ.

    Gender * Ability to work under pressure

    H0: There is no association between gender i.e. being male or female and AWUP
    H1: There is an association between gender i.e. being male or female and AWUP
    Since, p-value= 0.997 > 0.05 (d.f.= 9), the null hypothesis was accepted => There was no association between gender i.e. being male or female and AWUP.

    Gender * Entrepreneurship

    H0: There is no association between gender i.e. being male or female and EQ
    H1: There is an association between being male or female and EQ
    Since, p-value= 0.885 > 0.05 (d.f.= 10), the null hypothesis was accepted => There was no association between gender i.e. being male or female and EQ.

    Similarly, it was for Gender * Adaptability Quotient, Gender * Leadership Quotient & Gender * Loyalty Quotient

Conclusions
Competency Based Assessment rose as an instrument which streamlined and incorporated the HR procedures of the company to yield perceptible and long-haul benefits. It gave accommodating insights into the organizational fit of the potential role holder. This goes far in dealing with the attrition level in the company.
It also reformed the patterns in capabilities management and capacity construction of the employees. With well-defined competencies and consistent comprehension of sought after behaviors to be shown inside the company, the management had a reasonable acuity in regards to the dexterity gaps and measures to recognize and leverage the fortes. For the employees, it gave a chance to coordinate and divert their self-learnings properly to accomplish traceable outcomes, anticipated by the company.
Our reports, generated through SQL Service Reporting Services (SSRS), distinguished those individuals who demonstrated outstanding potential in each of the competencies, deserving recognition and involvement with evocativeness. We likewise suggested the names who might require development bolster. Eventually, we additionally distinguished the individuals who are 'solid inhabitants' and the individuals who are 'travelers'. We will investigate each of these 200 employees alongside their core domain evaluations and will follow up on it.

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Article by: HR, 3EA