Predictive analytics is one of the hottest topics in business today. Unfortunately, it is often misunderstood and misrepresented. Predictive analytics is about much more than graphs, dots, and plotted projection lines. Its real value is not the ability to crunch numbers and spit out data. The value comes from what we can do with the information in real life. And so, beneath the noise and chatter in our industry, there is a very important voice in the conversation. It is the story being told by the analytics themselves.
Today, we have the ability to examine that information through the lens of data science to reveal insights that are interesting, relevant, and often surprising. Let me begin with a topic relevant to every talent decision maker: the value of a high-paid recruiter.
When an issue arises in recruiting, such as an aging requisition or an unsatisfied hiring manager, it’s tempting to conclude that something’s wrong on the recruiter side. You might buy into the idea that you need to deploy a hired gun — a great recruiter who might cost quite a bit more –and that recruiter will save the day. After all, you get what you pay for, and if you pay more for a recruiter, you get better recruiting, right?
So we asked ourselves, “Do high paid recruiters do a better job than their lower-paid counterparts, and if so, what exactly do they do well?” In our organization, we have more than 1,000 recruiters. Those recruiters come from many backgrounds and many skill levels. To truly answer the question, the initial challenge is to identify an apples-to-apples field of comparison. Metrics such as time to fill won’t necessarily tell the story, nor will volume and type of roles recruited. This is because the expectations would vary from one type of assignment to another.
We do, however, have a real area of common comparison for recruiters. That is, performance against goals. In our organization, we have a recruiter performance program that has been in place, in the same structure and format, for several years. It does evolve, as a great program should, but the structure remains consistent. We have been collecting and recording recruiter performance during that time. That means we have a statistically significant data set comprised of a large number of people and a long-enough time span to reveal real trends.
To address the question, we took a look at recruiter performance against goals on a monthly basis. We divided our recruiter population into four quartiles: highest paid, second highest paid, third, and then the lower quartile. For each section we calculated average performance against goals over a two-year span, giving each recruiter a number rating. A rating of “1” equaled an average of 100 percent goal fulfillment. This could mean that the recruiter was at 120 percent of goal one month, and 80 percent on another. A rating of .7 means that the recruiter met averaged 70 percent of goal, and a 1.3 meant that the average was 130 percent, and so on.
With that in mind, we graphed the performance for each group, identifying the median performance rate for each quartile and then the range of performance rate for each. When we compared the highest paid and lowest quartile, the results looked graphed out as follows.
A comparison of the highest-paid quartile to the lower quartile revealed an interesting comparison. In fact, the success rate for the most- and least-expensive recruiters, as reflected in goal attainment, was almost identical (identified by the black line for each group in the graph). So, if the median performance against goal is the same, why bother paying more to the top recruiters?
To find an answer, we applied another level of context to the same information. We graphed the actual range of performance levels for recruiters in each group. This is represented as the shaded areas around the median in the graph. Now, a real difference becomes apparent. In the higher-paid group, that shaded area is much smaller. In effect, there is much less variation in the performance between one recruiter and another.
In other words, the highest-paid recruiters may not have delivered more impressively by exceeding goals more than their more junior counterparts, but they did deliver more consistently. This may fly in the face of the idea of that “rock star” recruiter who magically finds purple squirrels and makes problems go away. It does emphasize a much humbler concept that truly delivers client satisfaction over time: say what you’re going to do, do it well, and do it reliably.
If we understand that recruiter performance can only go so far in improving results, how do we adjust the process to turn consistency into value? In the case of a recruiter, it is possible to improve the outcome in cases where large fluctuations in performance are the problem. A senior-level recruiter can, in fact, help ensure that results are delivered to expectation.
This is not to say that people in lower-paid positions can’t also deliver great performance. Thorough training, management at the activity level to make sure individual activities that lead to results are completed, and tighter oversight can make a less experienced team perform with more consistency.
When you pay more for a skill, are you paying for rock-star heroics, or consistency and reliability? In the case of the recruiter, the benefits appear to lean in the direction of consistency and reliability. People may have varying opinions based on their experience with recruiters, but with the right framework for interpretation, the data reveals a solid answer.
Love our content? Now you can experience it in person! We’d like to invite you to the ERE Recruiting Conference this April 6-8. Become a data-driven decision maker over two days at the Red Rock Resort in Las Vegas. Sign up today!
