Improving Your Recruiting Results By Updating Your Sourcing Metrics (A checklist of what to fix)

Blame sourcing and its metrics when you’re not getting top candidates.

It is increasingly important to focus on the effectiveness of both sourcing and recruiting. First, because all corporate overhead functions are being pushed to “do more with less.” Second, AI and machine learning are slowly creeping into sourcing and cannot operate without robust metrics and data. Finally, a recent survey found that recruiting leaders still have a lot of work to do because a majority of them failed to meet their hiring goals last year (it was the highest failure percentage in four years).

Realize That Sourcing Is The Primary Limiting Factor In Recruiting

It’s important to realize that sourcing, as the top of “the recruiting funnel”, is the primary limiting factor in achieving great hiring. Because it’s an indisputable fact…

That you can’t hire top candidates who never made it into your applicant pool.

Currently, too many corporate sourcing processes rely on intuition and tradition rather than data-driven decision-making. You shouldn’t be surprised to learn that your current sourcing process may only have the capability of finding mediocre active job seekers. And that means that if you need to improve that capability. To improve this capability, your first step is to understand “what’s wrong” with typical sourcing metrics and to identify the best ways to use data and the different quality of hire measures in order to identify the optimal sourcing channels.

A Checklist – What’s Wrong With Your Sourcing Metrics

Over the last two decades, I have compiled a list of the common problems with the metrics that cover most sourcing activities. The problems with the highest potential negative impact appear towards the beginning of the list.

Most fail to measure the foundation channel success metric – new-hire performance. Start by realizing that it’s a serious flaw even to think that you can determine whether a sourcing channel was effective before the candidate begins performing. And that means that the foundation channel success measure will have to be calculated only after the candidate has started their job. And that foundation success measure must be…

“The percentage of the candidates produced by this channel that were hired and soon became above-average performers.”

While focusing on this foundational metric, I recognize that it is a serious mistake to get distracted by what I call “quality of candidate indicators,” which measure a candidate’s capabilities before they start the job. The types of candidate quality metrics that should be ignored after the hiring decision has been made include the percentage of qualifications met, interview ratings or candidate engagement levels.

Here’s an example. If you were hiring a starting major league pitcher, you would judge the channel’s effectiveness solely by the new hire’s actual performance (i.e., the number of games that that pitcher won during their first few months on the job). It would be a mistake to substitute candidate quality measures, like pitch speed during tryouts, for performance metrics such as the win–loss record. Additionally, if you were to include a second after-hire performance measure, it should be the retention rate of your above-average new hires during their first year.

Because it’s not data-driven, your process allows bad sourcing decisions – although everyone wants to use the best channels, they often don’t. Because of the absence of usable data on which channels work, recruiters have no choice but to rely on past practices or intuition when they are selecting a channel to use. Instead, the decision process for determining the most effective channels to use must be objective and supported by data. 

Your channel effectiveness recommendations are not reported by the job family – almost all channel effectiveness metrics “lump” each channel’s performance into a single number (i.e., 24% of referrals became above-average performers). This is a huge mistake because the most effective sourcing channels vary significantly by job family. And that means that channels that work for janitors won’t automatically work for AI engineers. You must track and report a separate performance number for each major job family to obtain optimal channel utilization. You will also likely improve your results by considering additional data breakdowns by the most effective channels in each geographic region and during each quarter of the year.

Your process for recording the used sourcing channels may be creating misinformation – it might seem like a simple thing. But you will never be able to accurately determine the actual source of hire. In the numerous cases where your recruiter or candidate inaccurately records the source channel that they used (it’s called channel attribution). Because research has shown that many recruiters and candidates don’t care much about accurate recording. So frequently, when they make an entry in the file, they guess about the right source or just check the first box they notice. And if this practice is not stopped, it will unknowingly lead to extremely bad channel selection decisions. An alternative is to ask new-hires during onboarding to directly name the specific source that had the most impact on their decision to apply.

Your process doesn’t report which recruiters are actually using the most effective channels – in most cases, individual recruiters are completely free to use any source that they want. And because they are so busy. Research has shown that many individual recruiters frequently use the same sourcing template for literally every job. To maximize your impact, your sourcing data must drive continuous improvement in your channel usage pattern. So, the first and the most important step should be requiring each of your recruiters to use the most effective channels every time. Next, there should be a metric that reveals which of your individual recruiters are actually using the most effective channels. And finally, to encourage the use of the best channels. Your recruiters should be recognized and even rewarded for using the most effective channels (and sanctioned when they use any of the bad ones). 

Because channel performance changes over time, you must be more scientific in identifying channel effectiveness – because the effectiveness of sourcing channels continually changes over time. It’s essential for your sourcing team to continually identify the specific channels that still work and those that no longer work. The sourcing team should also be constantly exploring the effectiveness of new and emerging sourcing channels. The first step in learning about these emerging channels is to study “hiring source surveys” from organizations like SHRM. And since you can’t know the effectiveness of a channel that you haven’t used. Make your sourcing more scientific by increasing the use of split sample experiments, machine learning, and pilot tests.

Your ROI calculations emphasize costs over business impacts – unfortunately, most efforts to calculate the ROI of sourcing place too great of an emphasis on costs. And even though costs are always of some importance. When you need significantly better results, you might actually want to spend more money on sourcing. This overemphasis on costs is unjustified because sourcing costs seldom exceed 10% of the job’s salary. In this case, the other side of the ROI equation (the value returned) may be up to 20 times greater than the cost per hire. So, TA leaders need to work with the offices of the CFO and the COO to quantify the direct business impacts (in dollars) from great sourcing and hiring. 

Your channel performance metrics don’t allow you to compare humans to technology – anyone who uses Google search already knows that electronic search technologies can sometimes far outperform human-driven searches. However, most sourcing functions fail to provide side-by-side comparison metrics that would reveal the specific cases where AI and machine learning assisted searches outperformed human searches. That means that whenever AI-assisted search technology becomes available, you should test its performance improvement percentage in a side-by-side comparison against human searchers.

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What Are The Best Sources For Those With Limited Time And Resources?

When your data or a survey reveals the most effective source channels, such as employer referrals, those with limited time and resources cannot implement a broad referral program that encompasses all variations (employer, reference, former employee, and nonemployee referrals). Instead, they should focus on one targeted subprogram (like top performer referrals) that has been proven over time to be both highly impactful and simple to execute.

I call these variations “best in category micro-channels.” Because this single variation will produce the very best results of any sourcing approach in this category. The top 10 effective micro-channels that I have discovered are:

1. Referrals from one of your top-performing employees. 
2. Top performing former employees that want to return (boomerangs).
3. Finalists that rejected one of your offers.
4. Silver Medalists that recently came in second for this same open job.
5. Finding their work or reading about it online.
6. Poaching top performers directly from one of your competitors.
7. Referrals from non-employees – including referral recommendations from your former top employees, top job references, top vendors, online influencers and professional association leaders.
8. Those who have endorsed or recommended your top performers on their LinkedIn profiles.
9. Speakers at local professional events (or their referrals).
10. Those that are labeled as “game changers” when you ask those who you trust if they know any.

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Additional Measures That May Indicate When A Channel Is Ineffective

In addition to the above-average performance of the new-hire metric, there are some additional indicators that may reveal whether one is ineffective. They include:

• Quantity of candidates – did the channel fail to produce enough candidates to meet our needs? Or did it produce too many candidates that we were overwhelmed?
• Time to receive candidates – did this channel produce the required number of candidates within the expected number of days? Because if the sourcing channel was too slow, that would negatively impact our time-to-fill.
• Revenue – did new hires from this channel fail to produce the expected increase in output and/or revenue? 
• Sourcing channel costs – when two channels provide the same level of new hire performance. Was the channel with the highest costs used anyway?

Implementation Tips

If you’re serious about implementing a new set of sourcing metrics. Here are four implementation tips to consider.

• Consult with your own data and ROI-driven departments – there is no need to spend a great deal of time researching how to implement effective metrics. Instead, I recommend that you work closely with your own internal departments that excel at using metrics already. This might include the Six Sigma and metric teams in supply chain, finance, and machine learning.
• Realize that reporting your dollar impacts gets the most executive attention – when you are reporting your sourcing results to executives. Since executives are highly money-focused, you will gain greater support by collaborating with the CFO’s office to deliver credible calculations that quantify the business impact of your sourcing and recruiting actions.
• Consider adding a metric that reports the percentage of your channels that are effective on passive candidates – those currently employed and equipped with up-to-date skills and training. Recruiting leaders recognize that the best candidates are often passive, and channels aimed at active candidates rarely work for this group. Therefore, measure the percentage of channels rated effective for reaching employed candidates, aiming for an ideal passive candidate effectiveness of over 40%.
• Consider adding a metric that reveals when high-priority jobs were actually treated special – leaders understand that not all roles produce equal impact when filled by top performers, and many have already designated certain positions as high priority. However, rather than assuming that every high-priority job is treated differently, measure how many actually receive special sourcing attention. This targeted metric reinforces your focus on “high priority jobs” that actually received the “white glove treatment” that was promised by your sourcing team.

Final Thoughts

Now that drastic cost-cutting has become all the rage in both business and government, it is becoming more critical every day for TA leaders to be able to prove their business impacts and then quantify them in dollars. Smart talent leaders must also now realize that the movement of AI into sourcing will require additional performance metrics and a huge amount of data. And this growing need makes it an ideal time to focus on refining and updating your sourcing metrics.

Note for the reader

This is the latest post from Dr. Sullivan, who was labeled “the Michael Jordan of Hiring” by Fast Company Magazine.

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