According to recruiting analytics firm Datapeople, hiring teams have historically operated mostly on gut and intuition rather than data. That’s despite other teams such as finance and sales having powerful platforms for data collection and analysis that help them do their jobs better. The reason is data hygiene.
Datapeople defines data hygiene as the steps necessary to ensure that data is complete, up-to-date, and not duplicative. The cleaner the data, the better the reports. In recruiting, data hygiene can include standardizing naming conventions for sources, closing job requisitions after a hire, and updating candidate status (e.g., ‘rejected’), among other things.
Conventional wisdom, according to Datapeople, says that recruiting analytics is a visualization problem. Companies have a lot of information in an applicant tracking system (ATS), and the trick is presenting it in a usable way.
That is a problem, says Datapeople, but recruiting analytics is, first and foremost, a data hygiene problem. Bad or incomplete data yield reports that are misleading at best and valueless at worst. With inaccurate reports, hiring teams make incorrect assumptions and bad strategic decisions. Also, data hygiene is generally more difficult in recruiting because there’s no industry standard, and every organization develops its own processes.
According to Datapeople, many companies use ATSs to keep records of their recruiting efforts, but they don’t practice good data hygiene. Some hiring teams treat their ATS as a repository of candidates (i.e., a talent funnel). They manage job requisitions in the ATS, but they don’t manage candidates. They collect resumes under one requisition and then move qualified candidates to another requisition. This severs the connection between candidates and the original job post, making it impossible to measure the effectiveness of the post.
Also, Datapeople says that while ATSs do a great job of recording data, they don’t analyze the data. In that way, they’re similar to an accounting ledger, which doesn’t replace an accountant. ATSs store a lot of recruiting information, but companies still need to translate it. Mostly, that means organizing it so hiring teams can see the metrics that matter.
Another wrinkle with ATSs, according to Datapeople, is that they’re great at recording process, but they’re also flexible. The first part of that is good for data hygiene, the second part isn’t. Flexibility enables hiring teams to design their own bespoke processes for candidates. But flexibility also makes measuring and understanding performance difficult for recruiting leaders.
If recruiting data is trapped in an ATS, messy, or incomplete, says Datapeople, hiring teams can’t factor it into daily strategy. However, hiring teams can control data hygiene, which depends largely on how they manage requisitions and candidate pools.
One of the fastest ways to dirty recruiting data, according to Datapeople, is to leave requisitions open. These jobs are commonly called evergreen roles. Rather than closing them, hiring teams leave them open for re-use at the next hire. But it’s impossible to judge how a job performed (past tense) if it never actually closes.
Datapeople says that, in the end, data hygiene depends on solid data cleaning practices from all members of the hiring team at all times. It means team members need basic database management skills, and they need to stay vigilant. And everyone, even long-time recruiters, may have to adopt new processes. But by doing so, hiring teams can cultivate good data hygiene and glean usable insight from the information in their ATSs.
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