Case Study: Comparing Assessments for Prospective Call Center Employees

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SAMPLE EXCERPT:

[. . .] Correlation with complaints about telephone sales order customer service representatives are non-significant. Work sample (T) is highly correlated with work sample (C ). The criterion-related validity figures for work sample (T) are not significant for error rate (which is negative) and a speed (which is positive). However, the correlations with complaints about telephone sales order customer service representatives are high and significant. Work sample (C ) is highly correlated with work sample (T). As with work sample (C ), correlation figures with work sample (T) are not significant for error rate (which is negative) and a speed (which is positive). And, again for this work sample, correlations with complaints about telephone sales order customer service representatives are high and significant.

The results of the work samples and the clerical test indicate that they are at appropriate levels for using in the selection process for the telephone order sales customer service representatives. The finding that the two work sample tests are fundamentally redundant is helpful, as one or the other could be eliminated from the assessment battery without any deleterious effects. The clerical test was found to be a good predictor assessment for two different criteria: error rate and speed. This leads one to believe that using one work sample test and the clerical test is an economical and accurate predictor of future job task performance.

3. What limitations in the above study should be kept in mind when interpreting the results and deciding whether or not to use the clerical test and work sample?

A. How similar are the new applicants to the workers used for the study? If they are not similar, then the results of this study are less generalizable to other populations.

The new applicants form a new data set, and although the differences between current workers and new employee may not be great, it is strongly beneficial to treat them as separate groups in this and subsequent analyses. Indeed, generalizability is always an issue in quasi-experimental or descriptive studies. The best solution for this problem is to clearly segregate data sets and to run periodic analyses of the fit between the assessment processes and the performance of employees overall. The layman's solution would be to keep a close eye on the performance of newly hired employees.

B. Are the criterion measures used (e.g., error rate, complaints) really valid indicators of CSR performance? If they are not, then the tests are not really predicting important dimensions of CRS performance.

The fundamental skills that are being assessed through the criterion measures appear to be related to ultimate job performance. However, this determination will need to be evaluated in the future as the performance of employees selected under the new assessment processes is analyzed.

C. Employees may not have been as motivated as job applicants to perform well on the tests. This could reduce the validity of the test when used with new applicants.

Motivation is a critical component of test performance. Differences in motivation levels and other types of affect are likely to produce different patterns of performance. The question becomes: How different are the patterns? If the performance patterns are not statistically significant between the two groups, then the matter is noted but is moot. Changes are not needed in the overall assessment processes.

D. Possible restriction of range on criteria since current employees who were already hired participated in the study.

Moreover, it becomes difficult to partition experience on the job from other variables considered to have potential for influence on performance scores. At this point, the human resources people are faced with completing more sophisticated statistical analysis that better accounts for the many variables, such as a multivariate analysis (MONOVA) (French, ). By measuring several dependent variables at the same time, there is more opportunity to discover which factor is truly important. The thing to remember is that data must collected with the idea of using these more sophisticated statistical processes in the future.

References

French, A., Macedo, M., Poulsen, J., Waterson, T., & Yu, A. (2008). Multivariate Analysis of Variance (MANOVA). San Francisco, CA: San Francisco State University. Retreived http://userwww.sfsu.edu/efc/classes/biol710/manova/MANOVAnewest.pdf

Shoukri, M.M. (2010) Measures of interobserver agreement and reliability (2nd ed). Boca Raton, FL: Chapman & Hall/CRC Press.

Validity evidence: Types of validity.… [END OF PREVIEW]

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"Comparing Assessments for Prospective Call Center Employees."  Essaytown.com.  July 2, 2014.  Accessed August 17, 2019.
https://www.essaytown.com/subjects/paper/comparing-assessments-prospective-call/5222888.