As part of the data analysis process regarding Police and Fire Recruit candidates, I noticed a need for improved data for deeper dives into where candidates finished in the selection process. Initially we were only tracking Pass/Fail results for candidates as it related to race/sex of the candidates. This did not tell us where in the selection process we were losing candidates.
I noticed that, using our applicant tracking system, we could create new candidate statuses for each step of the selection process that would better define where we lost candidates in the tracking process. This would (and did) allow for a deeper dive into whether or not we lost minority candidates in any given aspect of the testing process at a higher rate than in the others. For example, it allowed us to see if we lost more minority candidates from failing written versus oral exams, as well as from the candidates self-selecting out of the process (failing to self-schedule testing or attend testing), etc.This provided as thorough an analysis of candidate data as our system would allow.
I noticed that, using our applicant tracking system, we could create new candidate statuses for each step of the selection process that would better define where we lost candidates in the tracking process. This would (and did) allow for a deeper dive into whether or not we lost minority candidates in any given aspect of the testing process at a higher rate than in the others. For example, it allowed us to see if we lost more minority candidates from failing written versus oral exams, as well as from the candidates self-selecting out of the process (failing to self-schedule testing or attend testing), etc.This provided as thorough an analysis of candidate data as our system would allow.