January 27, 2021

Dwight Schrute’s 4 Lessons for Successful Data-Driven Recruiting

You probably know him best as assistant to the regional manager, owner of Schrute Farms, and an award-winning paper salesman. What you might not know is Dwight Schrute is also an expert on data-driven recruiting.

Fact. Over the past decade, data analytics in recruitment have evolved from simple job posting and advertising metrics to comprehensive breakdowns of candidate engagement, diversity analytics, social media marketing, and more. One early issue was deciphering certain types of recruitment metrics, which might as well have been written in matrix text. Fortunately, recent recruitment technology has increased the accessibility and clarity of information across the board.

Question. If recruitment metrics have evolved and are more accessible than ever, what’s the problem now?

There are four common mistakes that recruiters make with their data-driven hiring practices. Fortunately, over his illustrious career at Dunder Mifflin Paper Company, Dwight has secretly shared some lessons about using recruitment metrics successfully.

Lesson 1: Don’t Take ‘Best Practices’ Advice Too Literally

“Whenever I’m about to do something, I think, ‘Would an idiot do that thing?’ And if they would, I do not do that thing.” — Dwight Schrute

Dwight just nailed an important aspect of data-driven hiring many recruiters miss. It’s important to use your own insight and judgment, especially when given advice or best practices. Despite what anyone may tell you, there is no single method to become a successful data-driven recruiter. Why? Not every organization works the same.

As a recruiter, you have to consider organizational context when implementing a data-driven hiring practice. Recruitment metrics fit into every organization’s recruiting process differently. The hiring data tracked at Amazon and Salesforce may not apply to your company’s goals for the year. Your organization’s needs will determine the type of recruitment metrics you’re looking for, how you manage data, the systems you integrate data with, and the way your team collaborates with data.

In addition, your organization’s moral obligations to different initiatives, including diversity, sustainability, and cultural contributions, will also influence how your team mines data. Before you jump the gun on following a best practice, make sure it’s a best practice for your organization’s data needs.

Lesson 2: Your Data Should Serve a Purpose

“They say that no man is an island. False! I am an island, and this island is volcanic. And it is about to erupt. With the molten hot lava of strategy!” — Dwight Schrute

Strategy is crucial when it comes to data-driven hiring. In most cases, recruiters will have an abundance of available recruitment metrics, but they won’t know what to do with all that information. Before pouring over different data technology and analytics dashboards, go back to the basics and ask yourself: What am I trying to uncover about my client or candidate?

For example, if you’re looking to hire a software engineer from a talent pool of exclusively underrepresented candidates, wouldn’t you want as much data on those candidates as possible? Whether you’re looking for a breakdown on diverse representation, the average market value, or the predominant skills of your talent pool, use recruitment metrics with a purpose.

If you’re not sure your recruitment metrics are useful, take a page out of Michael Scott’s book and ask your data, “Why are you the way that you are?”

Figuring out the why behind your data will be especially important in 2021. Recruiters are going to see a lot of changes to the usual candidate and market patterns thanks to the shift to remote work, an increase in gig workers, increased access to global talent, and an emphasis on diversity and inclusion. If the metrics you used to track aren’t adding any value to your current state of hiring, don’t be afraid to throw them away.

Lesson 3: Use Data to Innovate and Improve, Not Just Report

“It’s a real shame because studies have shown that more information gets passed through water cooler gossip than through official memos. Which puts me at a disadvantage because I bring my own water to work.” — Dwight Schrute

While many of us haven’t seen a water cooler in months, notice what Dwight just did. He used data to identify a workplace trend, and consequently, a problem he faces because he is excluded from that trend. Unfortunately, he does nothing to fix this issue.

Many recruiters do the same thing with their recruitment metrics. While they succeed in reporting metrics to their teams and using hiring insights during their daily recruiting tasks, they rarely use data to identify bottlenecks and fix them. Fortunately, there are a few teams who have shown others how data can fix existing organizational issues.

For example, employee retention has long been a significant concern for many organizations. Prior to the pandemic, especially among millennial candidates, job hopping was a popular trend. With this issue in mind, Wells Fargo created a predictive model to identify the prevailing qualities in what it called “engaged high-performing workers.” Using the data it collected, the company looked for candidates with those same qualities. The result? The retention for new employee tellers and personal bankers increased by about 12 percent.

To put it simply, Wells Fargo’s recruitment team identified a problem with their data and didn’t hesitate to build a plan to fix it.

Lesson 4: Treat HR Technology Vendors as Partners, Not a Service

“I studied him, to figure out why I hated him so much. But that blossomed into a very real friendship, as these things often do.” — Dwight Schrute

You probably don’t hate your HR technology vendor, but we realize your relationship with them can feel distant. However, your relationship with a technology vendor should feel like a partnership.

As with any partnership, you shouldn’t hesitate to openly communicate with your vendors about the problems you wish to solve with your data. HR technology is now more dynamic, flexible, and customer-centric than ever before. The technology offered in the market today goes beyond traditional software models to offer customizable solutions for each and every team. By working with your technology vendors, your team can work to build an optimal data workflow for your organization.

It’s also important to realize that discovering the best data-driven recruiting process for your team requires trial and error. There are so many HR tech vendors that can help you extract and transform data into valuable assets for your open requisitions. Don’t hesitate to try out different tools and play around with them enough to see where they add or reduce friction in your process.

Lessons Learned

While Dwight Schrute has made some questionable decisions over his career, he’s been spot-on about data-driven recruiting. From finding a purpose for your data, forming a partnership with your HR tech vendor, and using recruitment metrics to innovate and improve, there’s no better time than now to embrace your role as a data-driven recruiter. By doing so, like Dwight, you’ll be ready “to face any challenge that’s foolish enough to face you.”

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Hiretual is an AI-powered recruitment software that functions as a candidate data engine to centralize all recruiting efforts for hiring teams big and small. Hiretual integrates with 30+ applicant tracking systems to drive real-time data synchronization and scalability in an organization's tech stack. Experience fast and simple AI sourcing across 750+ million profiles on the open web, build personalized engagement campaigns with extensive market insights, and rediscover old profiles in your database with intelligent data enrichment.
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