I have this idea floating around in my head that there is this line. The line is where information about a candidate begins to make us less efficient in hiring. Could be too much information or too little information. That’s really the entire crux of our hiring process.

At which point does the amount of information we have on a candidate make us inefficient in hiring?

Seth Godin has a concept call he calls “A/J testing“, instead of what most of us use in business as A/B testing. In A/B testing we test two possible outcomes that we believe to be fairly similar to see which one works best. In Seth’s A/J testing you test two possible outcomes that you believe are very different.

This got me thinking about what if we just didn’t interview. We posted, we sourced, we did some screening, we might even do some assessments, but then we just make an offer and have them show up. That’s our “J test”. We hire ten candidates that way, all for the same job. Then we do our A test as our same old process for another ten candidates.

What do you think your outcomes would be?

Here’s what I think would happen:

A test = same results you have now.

J test = slightly worse results than what you have now, but with an extremely lower time to fill.

In high volume hourly, with moderate to high turnover, the J test, might then play itself out as a better overall result if you are getting people hired faster. If we are truly no better than a coin flip when it comes to interview selection, does the interview really matter, especially in high volume?

This is just one example of a possible J test in recruiting and HR, there could be endless tests. You could J test compensation models, team structures, flexible scheduling, etc.

The key is to every once in while test something that no one else is. That is attempting innovation. That is pushing boundaries.