Essay on Navigating Employee Selection: Insights from Multiple Regression and Practical HR Management

Multiple regression is a method of combining predictor scores under mechanical methods of combining predictor information. Multiple regression is used to show the maximum linear association between two or more predictors and a criterion. Multiple regression can be represented using the formula:- y=b0+b1x1+b2x2 … bpxp+e where Y represents predicted work performance, E represents a constant, B represents regression weights for test X, and X applications score on the test (Bratton &Gold, 2017).

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Multiple regression may be referred to as a compensatory method of combining predictors data. It is possible to compensate for data from a low score on one predictor with a high score. Multiple regression has two assumptions. The assumptions are, that predictors are linearly related to the criterion, and predictors are additive and can compensate for one another.

Multiple regression has its advantages as well as its disadvantages. Some of its advantages include its flexibility. Multiple regression can be modified to handle normal data non-linear relationships or both. Multiple regression also minimizes errors in predictions and predictors to yield the best estimates of applicants’ future performance. Multiple regression equations can be constructed using different predictors, or the same predictors weighed differently (Mondy & Martocchio, 2016).

The disadvantage of using multiple regression is that statistical issues are challenging to solve. An example of such a situation is when a small sample size is used to determine whether regression weights or predictor’s weights are correlated and increase standard error weights. Another example is if preliminary screening will not be done. It requires assessing all predictors’ applications, which can be costly with a significant applicant number (Noe et al., 2015).

Most Practical Issues Learnt from the Course

The course teaches students the use of the best and most effective methods when selecting applicants and future employees, thus enhancing how an organization's workforce can produce quality products and services. During selection, the legal requirements and assessment issues should be governed by section laws and rules put in place. The rules should help the human resource manager comply and avoid breaking the law required. An example of such a rule is the reasonable accommodation for applicants with disabilities and if not, provide a reasonable explanation (Albrecht, 2015).

The human resource manager should consider the criteria for selecting and evaluating assessment methods. Such criteria include the assessment’s validity, methods for predicting job performance, and cost to develop and administer an assessment. The biodata, inventories, characteristics, and interests of the applicants should be an essential consideration during selection because they are a significant predictor of future job performance. One can predict future performance by looking at the current performance and the applicant’s past performance. The human resource needs to ask for this data during the application process (Rahim et al., 2018).

A human resource manager should use a personality test to determine and know individual applicants’ character traits. Character traits should help the manager select and know the best candidate, thus making the best decision for the company’s future performance. The traits should also predict an applicant’s past and future performance. They include emotional stability, openness, agreeableness, flexibility, and others. A personal test should consider true/ false questions or multiple choices (Furnham &Wright, 2015).

Consideration of such issues should help a student become a better manager in the future who makes the best decisions for the company’s best interest without oppressing the applicants. With these issues learned, a manager can handle applicants better and have the courage to tackle challenges that may arise and attract and retain talent. The course also teaches managers to learn from past mistakes and achievements and use them to better future performance.

References

Albrecht, S. L., Bakker, A. B., Gruman, J. A., Macey, W. H., & Saks, A. M. (2015). Employee engagement, human resource management practices, and competitive advantage. Journal of Organizational Effectiveness: People and Performance.

Bratton, J., & Gold, J. (2017). Human resource management: theory and practice. Palgrave.

Furnham, A., & Wright, J. D. (2015). Personality Assessment: Overview. In International Encyclopedia of the Social & Behavioral Sciences (Second Edition) (pp. 849-856). Elsevier.

Mondy, R. W., & Martocchio, J. J. (2016). Human resource management. Pearson.

Noe, R. A., Hollenbeck, J. R., Gerhart, B., & Wright, P. M. (2015). Human resource management. Instructor, 2015. http://mis.kent.edu/ap/new-syllabi/Summer-2015-syllabi/34180%20SIII%20Stevens.pdf

Rahim, R., Supiyandi, S., Siahaan, A. P. U., Listyorini, T., Utomo, A. P., Triyanto, W. A., ... & Khairunnisa, K. (2018, June). TOPSIS Method Application for Decision Support System in Internal Control for Selecting Best Employees. In Journal of Physics: Conference Series (Vol. 1028, No. 1, p. 012052). IOP Publishing.