Posted on by Judy

Another way to assess the effectiveness of the selection system is to examine the decision-making accuracy Employee selection is basically a system to predict which applicants will succeed on the job. Highly qualified applicants are expected to perform well on the job. Similarly, scemingly less qualified applicants are not expected to perform well on the job. Unfortunately, the hiring process is complex. Some applicants can put on a “good show” and still be mediocre employees, whereas other applicants may interview poorly but still be excellent employees, Organizations cannot assume the selection process is working well without collecting and analyzing data. One option to calculate the decision-making accuracy of a selection system is to classify applicants into one of two categories: strong applicants (ones who appear to be highly qualified and are predicted to do the job well-a good hire) and weak applicants (ones who do not appear to be highly qualified and are predicted to not do the job well-a poor hire). Once hired and after sufficient time (typically six months to a year) has passed, employees can also be classified into two categories: good hire or poor hire. After all of this data is collected, the overall decision-making accuracy of the selection process (the total hit ratio) can be calculated as the percentage of correct predictions The table below shows data about the 200 tellers employed at the bank Strong applicant Weak applicant Poor hire 20 70 Good hire 80 30 Totals 100 100 1. Calculate the total hit ratio by adding the correct predictions and then dividing that number by the total number of decisions ma de. What is this percentage? Do you think this percentage is impressive 2. What percentage of weak applicants turned out to be good hires 3. What percentage of strong applicants turned out to be good hires? This percentage is known as the positive hit ratio. 4. Compare your answers to questions 2 and 3. Do you think the bank’s system is effective? https://media.cheggcdn.com/media%2F1a2%2F1a24e48a-ee1b-4831-839e-af5be1bc768f%2Fimage

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