The High Cost of Low Performance
From the largest organization to the smallest, the hidden costs of variable productivity tend to secretly cripple organizations. Ultimately the impact of low-performing employees is due to bad hiring practices -- or rather, "hiring that's not nearly as good as it could be." But what exactly are the hard-dollar costs of sub-par hiring practices?

Fortunately, there is a special field of Industrial Psychology devoted to calculating the "utility" of different hiring tools. Utility is a fancy term for the money you gain by using better hiring systems, or conversely, the money you lose from using bad ones. In 1998, Frank Schmidt and John Hunter investigated 85 years of research* in a massive study about hiring tools. Since employee behavior seems to change about as much as the immutable laws of statistics, their results are just as enlightening today -- adjusted upward a bit for inflation.

The Good, the Bad, and the Average
A few basic concepts underlie these findings. The most important is that employee productivity does, in fact, vary among individuals. (If that's not true where you work, you must be in the robotics industry.) How much does actual performance vary? Measuring productivity can be difficult when the work product is intangible, but it can be done. As a rough rule of thumb, the performance for a superior unskilled 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 role it's estimated to be about 48%.

Real Money
Now, what do those percentages mean in dollars? Take a hypothetical small company in which all the employees are merely average. Following are the dollar-cost differences between their productivity now, and what it could be if they only hired employees in the "superior" category.

• 100 Unskilled/Semi-skilled workers @ $40,000/year; x 19% difference = $760,000 cost.
• 50 skilled workers @50,000/year; x 32% difference = $800,000 cost.
• 25 Managers/Professional workers @60,000/year x 48% difference = $720,000 cost.

That adds up to $2,280,000 per year, or $11,400,000 over five years -- not just one time, but every five years.

Imagine how much worse it could be if more of their workers were below average! It doesn't take a rocket scientist to see that recruiting accuracy can make the difference between financial success and bankruptcy.

Remember, these percentages represent average differences in performance. If you want your organization to run at peak performance levels, you need to do two things: reduce the differences in performance, and raise the average productivity.

Narrowing the Differences and Improving the Average
There are both internal factors and external factors that affect performance variation and average productivity. The major ones are:

• Size of the available labor market
• Organizational "attractiveness" (i.e., pay, benefits, culture, location, etc.)
• The organization's ability to measure performance differences
• The financial impact of these performance differences (e.g., type of job or the average number of years workers remain on the job)
• The number and skill of internal personnel who manage the hiring process
• The accuracy and completeness of the job model
• The ability of each hiring tool to accurately predict performance.

Working From a System
Making progress begins with looking at each job as a "whole system." This means working from a model that considers the whole job and the whole person. When performance in most jobs is statistically analyzed, it tends to fall into four basic areas. These are:

• Cognitive ability: The ability to think, problem solve, learn, technical knowledge, etc.
• Planning ability: The ability to plan, organize, sequence, etc.
• Interpersonal ability: The ability to get things done through others, coach, sell, resolve problems, etc.
• Attitudes, interests and motivations: Likes and dislikes associated with the job.

If your hiring process skips any of these, skills in that area are left to chance. For example, technical managers tend to place heavy emphasis on technical skills (i.e., a specific cognitive ability) but readily admit that technical people fail more often because of poor interpersonal skills, an area they seldom measure. Call center managers, on the other hand, tend to skip attitudes, interests and motivations, even though customer service representatives tend to quit because they do not like the work. Skip it, or fail to accurately measure it, and you will get performance differences.

Setting the Levels
It is important to remember the "Goldilocks" principle: Some applicant skills are too high for the job, some are too low, and others are just right. On the "too high" end, I have known many organizations that recruited from the best schools and only hired folks with the highest grades. What did they get? People who started off like a rocket, but became discouraged and quit when they weren't promoted to president within two years. Other firms set their targets too low -- and guaranteed a ready supply of people with low productivity.
Setting just the right level, however, is tricky. For example, most of us would think that smarter people tend to be better performers. Intelligence and performance do "track" together -- but only to a point. When people have more intelligence than the job requires, they're likely to get bored, and performance becomes unstable. The challenge to each hiring organization is to find the "breaking point" where performance peaks. Each of the four major performance groups has it's own performance "breaking points." And smart testing can find them.

Accuracy
Unfortunately, a successful testing program takes expertise and hard work. To start with, forget about using any tests that were not designed expressly to predict performance. Then get ready to validate each test for each job. If you can't prove that high test scores predict high performance and low scores predict low performance, then toss your test.
How exactly should you go about validating tests? That's another Big Question. Its easier to begin with what you should not do:

• Don't do studies that use small groups. They are NOT valid because they don't statistically represent scores of a large group.
• Don't compare applicant scores with a "average scores" of special groups such as criminals, engineers, sales people, accountants, etc. They are NOT valid because, for example, they do not predict how a person applying for a job in engineering will actually perform as an engineer.
• Don't take validation results from jobs that are significantly different from your jobs. They are NOT valid because the jobs are very different.

Thoroughness
Remember those four basic areas of job performance? You need a validated tool to accurately measure each one. These tools include: realistic job previews, learning and problems solving tests, planning tests, one-on-one simulations, job samples, case studies, behavioral interview techniques, situational interview techniques, and tests of attitudes, interests and motivations. You can pick and choose among these tools depending on the thoroughness and accuracy you need, and the complexity of the position.
Sounds like too much effort? At least technology now lets us administer tests in a few hours that in the old days could take several days. And no matter how much it costs, it can't possibly approach the millions of dollars your workforce may be wasting every year just by being average.

*The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings, Psychological Bulletin, Sept 1998, Vol. 124, No. 2, pp 262-274.

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