Are you tracking longer-term hiring outcomes too? They'll probably take some time to become meaningful, but they're far more important. The data you've compiled is useful since it helps to filter earlier in the process, but it still presumes that your in-person interviewing process makes the correct decision. If the final filter is letting bad candidates through or screening out good candidates, all the correlations you've found could be reflecting only the ability to pass the interview, not the ability to do the job successfully.
Hopefully you're continuing to follow hires 1, 2, 5 years after being hired to tie it back to the data you collect about the interview process. It would be awesome if you could find predictors of candidates that are likely to quit less than a year after being hired or candidates that will receive less-than-stellar ratings from their managers. By doing this, you'd help hiring managers deal with the blindspots in their hiring, not just streamline the existing process.
Are you tracking longer-term hiring outcomes too? They'll probably take some time to become meaningful, but they're far more important. The data you've compiled is useful since it helps to filter earlier in the process, but it still presumes that your in-person interviewing process makes the correct decision. If the final filter is letting bad candidates through or screening out good candidates, all the correlations you've found could be reflecting only the ability to pass the interview, not the ability to do the job successfully.
Hopefully you're continuing to follow hires 1, 2, 5 years after being hired to tie it back to the data you collect about the interview process. It would be awesome if you could find predictors of candidates that are likely to quit less than a year after being hired or candidates that will receive less-than-stellar ratings from their managers. By doing this, you'd help hiring managers deal with the blindspots in their hiring, not just streamline the existing process.