John Sullivan points out in his ERE post on referral programs that numbers are available for those who want to invest in measurement discipline and operate at the level of evidence versus opinion. There is plenty of data that suggests referrals work and make sound business sense. And, just like the issue of diversity, there are other dimensions of referral process effectiveness that can be quantified.
In a hiring environment using pre-employment assessment, it is possible to examine the relationship between quality of hire and quality of referral. In one client analysis, we were able to document that individuals scoring higher on the assessment tended to refer individuals who also performed well. And as one might also conclude, those who scored less well referred candidates with similar performance results. It is important to create referral behaviors from those more likely to generate high value candidates.
The anomaly, and there are always some, was the cluster of individuals with modest assessment results but with a high level of referring activity. There was no pattern to the quality of the candidates they put forth. We called these the ambassadors. They are just out piping a ‘follow me tune’ attracting all comers. Even a blind squirrel finds an acorn. It is important not to get referrals for referrals sake.
As such, using HR Analytics it is possible to target referral behaviors more selectively. But first, you need better candidate data.