Economics has been called the dismal science. Recruiting analytics should be called miserable math. You have to use such metrics, but it’s painful to do so. What makes the experience so unpleasant? It’s complicated. Performance data can be analyzed in many different ways, and that’s exactly what’s happening in recruiting today. There is no general agreement about what constitutes the baseline measures of success.

How can we improve the recruiter’s experience with analytics? Let’s start with a radical notion: while CEOs say they care about operational efficiency, the only thing they really pay attention to is results. To put it bluntly, they are bored to tears by time-to-fill, but intensely interested in the return that’s achieved on your investment of corporate funds.

Does that mean you shouldn’t measure other aspects of your recruiting strategy? Of course not. It does mean, however, that the first metrics you should define, collect and analyze are those that matter most to the people who matter most in the enterprise. Get those right, and you’ll have the support you need to expand your analytics program into other areas.

What are the key metrics that will enable you both to report and manage your results effectively? They are your return on investment (ROI) measured in two ways:

• Quantity of talent generated.

and

• Quality of talent generated.

Analytics for Dummies

As with the famous Dummies series, there’s nothing at all degrading about simplifying a complex subject so that it can be effectively addressed. In this case, we acknowledge that data can be collected and analysis performed on a wide range of ever more fine-grained aspects of recruiting operations and performance. What’s most important, however, at least inside the political and power structure of most organizations is not how complicated our measurements are, but how clearly they detail the contribution we make to organizational success.

For that reason, our primary analytics goal should be to ensure that we maximize the return on our investment in the enterprise’s recruitment advertising and sourcing dollars. That return is best measured with four metrics:

• Response Rate per Source. The number of applicants generated by each job board, social media site, or other source used during a specific period of time.

• Applicant Cost per Source. The direct financial, as well as indirect labor costs invested in each source, is divided by the total number of applicants generated by that source.

• Conversion Rate by Source. The number of applicants from each job board, social media site, or another source that is converted into new hires during a specific period of time.

• New Hire Cost per Source. The direct financial, as well as the indirect labor costs invested in each source, is divided by the total number of new hires generated by that source.

The response rate is a measure of both a source’s effectiveness in connecting your opportunity with the greatest number of prospective candidates and your ability to write a compelling job description. As a general rule of thumb, the variations between sources are the result of the former, while the level of consistency across sources (high or low) reflects the latter.

The conversion rate, in contrast, is a measure of a source’s effectiveness in connecting your opportunity with the best prospective candidates and the caliber of the experience provided to candidates in your recruiting process. As with response rates, the variations between sources are the result of the former, while the level of consistency across sources (high or low) reflects the latter.

There is, however, a caveat to these guidelines. For some time now, there have been concerns expressed about both the fidelity of data and the yields generated by applicant tracking systems. The technology used by some ATS vendors to track applicant sources – basically, they rely on the memory of the job seeker – simply cannot provide accurate data or support meaningful analysis. And, the creaky and overly long structure of many ATS application forms leads to high drop-off rates and thus undercuts the conversion of candidates to applicants. An accurate picture of applicants is the key to all metrics, but especially these two, both of those concerns must be addressed for any analytics program to be effective.

As important as recruitment analytics are, they need not diminish the recruiter’s experience. It is possible to install a meaningful measurement process without using calculations that only an economist could love. The key is to focus on a small number of metrics that both promote recruiters’ effective management of organizational assets and reassure senior leaders in the enterprise that recruiters are effectively contributing to organizational success.