Bad Hire Costs

Recruiting costs are like the weather... everyone talks about them, but no one does anything. Well, you can do something about recruiting costs — if you want to.

Most people don't realize recruiting costs are more than the cost of acquisition or cost of turnover; they are also deeply hidden in the cost of variable productivity. From the largest organization to the smallest, bad hiring practices tend to secretly cripple organizations.

Place an ad, screen resumes, develop a short list, interview applicants, screen-out unqualified people, check references, make an offer to the survivor. Repeat.

These are bad hiring practices. Bad, because any conscientious recruiter who follows up on his or her placements would find that, despite all these efforts, about half of new hires turn out to be low performers. In fact, most studies show typical recruiting practices have about the same accuracy as flipping a coin.

Anyone with doubts should take the time to follow up with a line manager. Ask if he or she sees performance differences among people the recruiter recommended. If the answer is "yes," the recruiter needs to start thinking about why he or she did not see these differences before hiring.

No, recruiters cannot blame all hiring mistakes on hiring managers. Hiring managers have enough to do without being expected to be competency experts. Recruiters are supposed to be the hiring experts. Their job is to forward highly qualified candidates to managers for a final "chemistry check."

When I install hiring systems, recruiters often ask, "But, when do I 'get to know' the person?" I respond by telling them, "Right after you discover they are qualified." Somehow, even seasoned recruiters mistakenly believe that "getting to know" an applicant provides valid information about a person's "hard" skills. Making quick assumptions based on personal impressions is a weakness of the human condition.

Psychologists call this weakness the "halo" effect. It occurs when a recruiter or hiring manager is so impressed by an applicant that he or she makes unfounded assumptions about other job skills. But enough jawboning about good and bad "practices" — what is the hard-dollar cost of loosey-goosey hiring?

There is a special field of Industrial Psychology devoted to calculating the "utility" of different hiring tools. Utility is a fancy term for calculating the money you gain by using better hiring systems. But I like to think of utility as the money you lose from bad hiring tools. Frank Schmidt and John Hunter in 1998 investigated 85 years of research* about hiring tools. I thought you might be interested in a few things they had to say about the cost of hiring.

Get a Grip

Before we continue, if you don't see differences in employee productivity, then there is no reason to do anything different. Your job may be so simple there is no difference in productivity among candidates; your hiring system is already a finely tuned "machine"; your management is asleep at the switch; or you don't care about individual performance. If you cannot see or are not concerned about performance differences, there is no reason to waste more time reading this article. But if you want to learn more about the hidden cost of un-validated hiring tools, read on.

2. The bell curve can be divided into roughly four groups. People in the top 16% who produce the most (superior), people between 84% and 51% who produce more than average, people between 50% and 17% who produce less than average, and people in the bottom 16% (fish bait).

3. Productivity differences are statistically defined by something called a "standard deviation." Bigger standard deviations indicate bigger productivity differences between people. Smaller standard deviations means performance differences are smaller.

Most organizations can see differences in productivity in almost all jobs. Productivity is easy to measure when the work product is tangible (such as in sales or production), but when the work product is intangible (such as in management, professional, or staff jobs), measuring productivity gets more challenging. Regardless of the work product, though, the ability to see and measure productivity is critical to the next step.

The goal of a recruiter is to progressively "narrow" individual differences in productivity by using better and better methods to ensure only uniformly high-producing employees are hired. That means taking positive action to decrease the standard deviation and stabilizing it somewhere above the average.

What does a standard deviation mean in dollars? In a lower-level job, the standard deviation for a superior worker is estimated to be 19% more than an average worker, in a skilled job the figure is estimated at 32%, and in a superior manager/professional it's estimated to be about 48%. Converting this to dollars, the following table shows the productivity loss of a small company with 100 skilled and semi-skilled workers, 50 skilled workers, and 25 managers:

At this point, many of the people who at first thought my individual numbers were reasonable will probably go "overload" when they see how quickly a small difference in productivity can add up. It doesn't take a rocket scientist to see that recruiting accuracy can make the difference between success and failure. Are the numbers simply too big to process? Well, this is not a time to take a "head in the sand" posture.

It may sound trite, but the western ideology of independence and opportunity are under attack from a small group of fanatics whose primary goal is to disrupt and destroy our economy. I do not pretend to understand their motives, but that does not change the fact that recruiters hold some high-impact solutions to productivity and America's economic success.

Recruiters screen in and screen out employees. Stone-age hiring tools are like defective sieves: they allow too many impurities to pass through unchecked. If you want your organization to run at peak performance levels, you need to scientifically examine your costs and continually improve your effectiveness using validated hiring tools that accurately predict performance.