Dealing with Bad Data

Every manager of data struggles with the same problem: bad data. It’s not just the Human Resources function. We have even coined a favorite phrase for it—GIGO: Garbage in, garbage out. Bad data can’t be the excuse not to present the needed metrics to a hiring manager or an executive or your own teams. If everyone has the problem, then there must be workarounds to dealing with bad data so that you can use it in your reporting without ill effect. There are a few different classes of bad data to manage:

Incomplete data. Every report on the planet will eventually have one row of data that isn’t included. It’s okay. What’s not okay is not being aware of what you don’t have. If you are reporting voluntary turnover and you cannot get that information from a newly acquired entity, then make sure it’s clearly noted on your dashboard. You’ll probably get some executive intervention so that next time the data hole is patched.

Inaccurate data. Time-to-Start metrics have this problem all the time. Somehow, after running the data the first time, you find that your average time to start is -34 days because recruiters were taking out reqs after the candidate was identified and hired. You can intervene to fix the process and fix the data. Beware of using averages with inaccurate data. One practical method of repairing the data to get at least an approximation of Time-to-Start is to remove the offending rows. If you find that your time to fill is -34 days, look through the ...

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