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What is Data-Driven Recruitment?

Employee recruitment has become the final frontier of adopting analytics into business practices. Other functions, such as marketing, manufacturing, finance and accounting learned how to harness automation, sophisticated analysis and Big Data to improve the quality of information, ease the gathering of data and assist in better decision making. Recruiters, however, seemingly resisted this trend for many years.

But not anymore.

In the coming years, data-driven recruiting has the ability to transform the human resources industry. This is being accelerated by cloud-based computing solutions, more advanced software, and the overall digitization of the modern organization.

“The old-fashioned fuddy-duddy HR department is changing. The Geeks have arrived. Today, for the first time in the fifteen years I’ve been an analyst, human resources departments are getting serious about analytics. And I mean serious.” — Human resources expert Josh Bersin

What Is Data-Driven Recruitment?

Data-driven recruitment encompasses the technologies and techniques used to analyze a large talent pool and identify the candidates with the proper skills and the right mindset to help the organization achieve its goals. Applied well, it helps companies find the employees that will fit into the corporate culture and become strong team players.

According to a recent report from LinkedIn, data-driven recruiting allows recruiters to

The results are proven; Xerox used algorithm-driven recruiting to decrease their attrition rate in their call centers by 20 percent. And these “people analytics” can drive organizations to recruit more productive workers. For example, the best developer at Apple is more than nine times as productive than an average worker at a competing technology company. The best sales associate at Nordstrom brings in over eight times more revenue than an average salesperson at a competing store.

Other benefits of data-driven recruitment include:

  • Improved workflows
  • Near-immediate access to records and metrics
  • Real-time job matching
  • Predictive analytics (especially important for hiring in cyclical industries)

Part of what makes data-driven recruiting successful is that it takes advantage of a talent pool that can be used as a pipeline to identify candidates and narrow down options until just the most suitable candidates remain. One of the challenges is to make data collection consistent — paper resumes are passé, and candidates should be encouraged to apply through a portal on the organization’s website. This eliminates the need to analyze individual resumes and manually input data. A Boolean search string based on the hiring manager’s requirements should produce a suitable selection of candidates from the talent pool your company has amassed.

Not a Fad: A Requirement

Data-driven recruiting is a strategic asset organizations can no longer afford to ignore. Bersin writes in a 2015 research report from Deloitte: “… cloud computing and Big Data analytics just arrived. More than two-thirds of our clients are in the middle of some kind of core HR system replacement.”

There are two reasons for the urgency to adopt data-driven recruitment, Bersin says:

  • It makes it easier to use the systems
  • It improves the accuracy of the database used for people analysis and decision making

In the Bersin report, 73 percent of organizations seeking upgrades said they want integrated data and analytics to be part of their new systems. Two-thirds of respondents said they are looking for a cloud-based solution.

Data-Driven Recruiting Tips

Recruiting services provider iCims provides some guidelines for organizations looking to embrace data-driven recruiting:

  • Take a holistic approach to capturing metrics and establishing your talent pool
  • Set up highly configurable reporting — even at the individual user level
  • Use the data analytics reporting features built into your existing recruiting software if possible
  • Don’t expect individual recruiters to turn into data experts overnight
  • Develop a formal strategy
  • Look beyond purely transactional metrics
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