HR Professional
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By Mark Bania


Data analytics can strengthen the HR discipline

Human resources and data analytics, at first glance, seem like diametrically opposed concepts. Big data is raw, dispassionate and objective. HR, meanwhile, is the shepherd of the organization’s culture and the perpetual process of attracting and retaining top talent. Its core functions are rooted in empathy and a keen understanding of complex interpersonal dynamics. In the recruitment world, specifically, some assume big data will ultimately become a proxy for the “human” in HR.


Fortunately, research detailing the early adopters of human capital data analytics tells us that the science is a complement, rather than a replacement, for the decades of carefully maintained insights and best practices. It is a tool that makes the HR discipline stronger. What’s clear, however, is that after years of experts hailing the arrival of big data in HR, there are many skeptics still questioning its relevancy.


A summer 2014 and Harris Poll survey of more than 400 Canadian hiring and HR managers found that a vast majority of employers are not on the big data bandwagon, at least when it comes to talent acquisition. In fact, 83 per cent said they never or rarely use data analytics as part of their recruitment strategy. Asked why, half of this group responded that big data is simply not applicable to talent acquisition, a response that lead “inaccessibility” of big data (20 per cent) and its “overwhelming nature” (23 per cent) as the top reasons.


The hesitancy to adopt data analytics is in spite of the fact that nearly half of Canadian companies have open jobs for which they cannot find qualified candidates. Extracting meaning from large and unwieldy datasets is a legitimate challenge for many HR departments running up against staffing and budgetary constraints. The large number of those citing lack of applicability, however, suggests that the intended benefits of data analytics have yet to diffuse the HR community.


So let’s go over what those potential benefits of big data are, based on the one in six Canadian employers who “always” or “usually” use analytics as part of their recruitment strategy:


  • 70 per cent say it lowers their cost per hire
    66 per cent say it lowers time to hire
    49 per cent say it helps them hire more candidates for specialized fields

Big data analytics is boosting recruitment efficiency, and for many, increasing access to elusive, high-skill candidates. To these advocates, it is empowering recruitment in meaningful, bottom-line enhancing ways.


Details on data
But what data is being used, and how is it implemented?


The item at the top of many organizations’ list of recruitment challenges is a lack of top-level candidates applying to open positions. By using a variety of tools that leverage government and online recruitment data, companies can determine whether or not their challenge is simply a matter of the supply of available and qualified talent falling short of regional demand. These tools crunch millions of data points – resumes, job postings, labour force surveys – that were previously unavailable to recruiters just a few years ago. For example, if there is an undersupply of workers in one area, a company can choose to target job advertising in nearby metros and relocate ideal candidates. Or, the data may convince companies to scale back job requirements and consider instituting a training program for the occupation in question.


Similarly, recruiters can access market-specific compensation data to compare how their salary ranges stack up against competitors. In situations where a skills shortage is present, market logic tells us that raising salaries above the median should attract more qualified candidates to the open job, and subsequently, signal more workers to acquire the requisite skills for that profession over the long-term.


Thirdly, companies are becoming increasingly savvy at analyzing their current and past workforce to inform future hiring decisions. In the book The Talent Equation, by Matt Ferguson and professors from University of Pennsylvania’s Wharton School and New York University’s Stern School, the authors crunched nearly 33 million resumes and found that when companies increase their number of sales workers who hold college degrees by just 10 per cent, it is associated with about $31,000 (U.S.) in value added per employee. This is no small amount for a large organization. Companies are capable of doing these types of high-level statistical analyses using the trove of workforce data sitting on their own servers and using the results to implement systemic realignments of their recruiting goals.


Finally, companies can significantly improve upon recruiting time-to-hire and cost-per-hire by using analytics to evaluate their own talent acquisition processes. The average large company invests in dozens of recruitment sources to attract job applicants. These include everything from company career sites, job boards, social media and staffing agencies. Over the course of a year, these services generate a mountain of performance-based data that if aggregated and analyzed, can answer whether recruitment dollars are being spent most advantageously.


Note that in all of these examples, data does not diminish the role of the recruiting expert – it enhances it. Adopting data analytics is the next step of HR’s long transformation from administrative-focused roles to consulting-based, talent advisory roles. Data won’t dehumanize HR and talent acquisition; rather, it will empower recruitment leaders to find the right person, for the right job, at the right time more efficiently than ever before.


Mark Bania is the managing director of Canadian operations at CareerBuilder.

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