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Here’s What Happens When a Finance Guy Runs Recruiting Operations
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I recently met Shane Noe, the head of recruiting operations for Box, at a dinner we hosted in San Francisco. In the midst of conversations about recruiting, he mentioned that he’s new to the recruiting space, having spent most of his career as a finance manager. Now that’s unique. I was curious about his bold move into the recruiting sector, and decided to dedicate a blog post to his story. That led to all kinds of revelations and recruiting operations advice from his finance-oriented mind.
Noe followed an unlikely path to become Box’s head of recruiting operations. He spent most of his career as a finance manager, tackling worldwide revenue forecasting for Apple and foreign-exchange hedging for Google. When he moved to Box’s strategic planning and analysis-oriented team, he never imagined it would lead to a role in recruiting.
As Box’s new corporate finance manager, he was tasked with forecasting their financial statements. In order to do that he needed to understand the company’s biggest expense item: headcount. And in order to accurately forecast headcount, he needed to cultivate a deep understanding of Box’s hiring processes. That’s when the stars began to align.
He noticed several areas in recruitment that were inefficient and begging for process improvements. They piqued his interest. When the head of recruiting operations role opened up, he threw his hat in the ring. Sometimes skills and interests match up with job profiles in ways you would never predict, and he quickly became the top candidate and accepted the job.
Financial professionals love metrics. Data. Analytics. They provide great truths and clarity. In a financial analyst’s world, every imaginable source of data can be collected, crunched, and dissected to glean insights and drive efficiency. Recruiting is a treasure trove of data, and in many cases it’s underused.
We asked Noe to share some tips on how to use recruiting metrics to tell the real story of what’s happening on recruiting teams. His tips make it easier to achieve more and set reasonable expectations with management teams.
Here’s the scoop.
Spick and span. Totally hygienic. That’s how clean you want your data to be.
The reality is that your recruiting data probably isn’t clean. So your first step toward progress is to evaluate the current state of your data’s integrity, or how complete, accurate, and consistent it is.
There is often inconsistency across recruiting teams in how they use and maintain their applicant tracking system, which can make it hard to get clean data from a complex ATS. Here are a few pitfalls to watch for.
Inaccurate pass-through rates
A pass-through rate is the percentage of candidates who make it from one stage of an interview (e.g., recruiter screen) to the next (e.g., hiring manager screen). Pass-through rates are critical for identifying problems in the recruiting funnel. For example, a low pass-through rate from a recruiter screen to a hiring manager screen could indicate that the recruiter and hiring manager are misaligned on the requirements for the role.
To keep the pass-through rate data clean, make sure recruiters are rejecting candidates at the proper stage and that they are careful not to move candidates back and forth between stages unintentionally. This happens more often than you’d think and causes inaccuracies, or dirty data.
Botched time-in-stage numbers
The amount of time a candidate spends in each stage of the recruiting process is your time-in-stage metric. Box looks closely at the time a candidate spends in application review, as a way to gauge how quickly its recruiters are reviewing in-bound applications.
Inaccuracies are quite common in time-in-stage metrics. One major cause is having active candidates sitting in a interview stage for a closed job. They sit in the stage indefinitely and destroy time-in-stage metrics. Luckily it’s a quick fix to clean up active candidates in closed jobs.
Skewed time-to-hire data
Your time-to-hire is the time it takes to move a candidate through the entire hiring process, from the moment a job requisition is opened to the moment it’s closed. It’s an important metric when you’re setting expectations with hiring managers, planning your recruiting capacity, and assessing how difficult it will be to fill a role. A couple of job-posting outliers can mess up the data.
“One-to-many” job postings are instances where you post a single job and hire multiple people against it. “Evergreen” job posts are essentially marketing tools. They’re posts that stay on the career site as a way to continuously bring in candidates for hard-to-hire roles. Both of these types of requisitions, while necessary, can cause you to overstate the time to hire and should be excluded from time-to-hire calculations.
If you watch for these pitfalls, you’ll help ensure that your data represents what’s really happening on the ground for your recruiting team.
When recruiters see their data, they begin to understand where and how the process is broken. Don’t tell them that the team’s time-in-stage numbers are bad. Show them specifics. Show them their own numbers.
“At Box, we created a report that included the time-in-application stage data for our recruiters. Some of them were really surprised their numbers were so poor, which made them very motivated to look into the issue. They quickly realized they had active candidates in closed requests, which had negatively affected their data. They’ve kept a closer eye on their work since then and the team has more accurate data for it.” – Shane Noe
On the finance team, Noe often had to speak off the cuff about business metrics to facilitate conversations in formal and informal meetings. He says that in recruiting, we should be able to do the same thing. Data should be top of mind. Knowing these key metrics will be particularly helpful:
When a leader wants to know how much it will cost to hire 10 more salespeople, how long it may take, or how many recruiters you need to get the job done, the recruiting management team can earn a lot of credibility if it has a sense of these numbers and can relay them confidently.
If you have clean data, you can (and should) use it to understand your team’s recruiting capacity. Having this understanding is most critical during your company’s annual planning process. Early in the process, before your corporate finance team comes up with headcount and spend targets, make sure you’ve informed them what you are capable of in the coming year with your current resources. That way, any resource gaps can be addressed up front, before targets are issued.
Good data can lead to game-changing insights, better business performance, and confidence in the recruiting management team. Bad data can lead to a loss in credibility and ultimately result in leadership making the wrong decisions. Clean processes lead to clean data, so begin at the core and understand how your recruiters operate. You’ll set yourself up for success if you do!