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Whether they're driven by AI, machine learning or search engines built to parse and contextualize unstructured data, an increasing number of tools are being introduced to apply recruiting analytics as part of candidate screening.
The growth of recruitment analytics is likely welcome news for companies looking for a competitive edge when fighting for top talent. "With involuntary unemployment as low as it is, it's currently an employee's market," said Armen Berjikly, senior director of strategy for Ultimate Software, an HR and recruiting software provider in Weston, Fla. "That means that even traditional 'employers of choice,' who relied on having great candidates come to them in hopes of a position, are going to need to both actively broaden their hiring funnel just to replace departures and increase their competitiveness for luring great new talent."
Madhur Mayank Sharma, SAP's head of machine learning for HR, agreed. "The ability to find the right match in the least amount of time possible and enhance the overall recruiting experience for recruiters and hiring managers, as well as for candidates, are some of the key deciding factors for customers to select the right recruiting platform," he said.
However, recruiting analytics by itself isn't a panacea. The best tools, according to Jeff Mills, director of solutions management for SAP SuccessFactors, offer "overall guidance" in addition to analytics. "Recruiting tools are leveraging data to provide deeper, more thoughtful insights into job descriptions, applicants and candidates," he said.
1. Use recruiting analytics across the hiring process
At its core, recruiting is very much like a sales process: A wide range of leads are enticed into the top of a funnel and then progress down its narrowing scope as they're vetted. Like salespeople, many recruiters describe the process as being a series of "conversations," and because conversations tend to be fluid, most believe recruiting analytics can be applied at a number of points throughout the process.
"I see these tools being used not only at the top of the funnel, but also to help find information about candidates online and eliminate human bias," said Brent Skinner, principal analyst at Nucleus Research in Boston.
SuccessFactors' Mills also sees a fit for analytics across the hiring process. He said that some recruiting analytics tools provide real-time source reporting based on job requisition, while others dissect supply-and-demand and pay data to make salary recommendations. Some systems use machine learning to analyze resumes and compare applicants to previous hires and their performance, as part of the winnowing down of potential candidates. Currently, many recruiting analytics tools focus on providing HR and recruiters with feedback on candidates' interviews and assessing their potential fit, along with scores and rankings, according to Mills.
Because recruiting analytics enables HR and hiring managers to evaluate potential candidates from the time a job is defined "all the way until the right candidate is onboarded," in Sharma's words, the technology sometimes pushes a company to reimagine each step of its process and develop capabilities that provide better-aligned insights, predictions and recommendations.
William Tincup, president of RecruitingDaily in Shelton, Conn., believes that such efforts are worth the time and investment. "Any insight that I may gain from the conversions between one step and another step is gold for the team to mine," he said. "Having a basic understanding of my recruiting conversions gives me the confidence to really know when things are going well and when things need my attention."
2. Spot trends with recruiting analytics
Technologies such as machine learning, deep learning and predictive analytics are harnessed to uncover insights that might otherwise be difficult to spot, as well as make predictions and recommendations, Sharma said.
"Skills analytics that can pinpoint the right people, for the right jobs, at the right time, can be the most help to employers and maximize the efficiency of the recruiters and sourcers who work for them," said John Harney, co-founder and CTO of DataScava, a New York City company whose job matching service, TalentBrowser, is based on an unstructured data mining platform.
Berjikly sees "traditional" analytics as having a significant role to play in recruiting. For example, much work remains to be done in combining multiple data sources or delivering insights in ways that help decision-makers act based on evidence instead of instinct.
At the same time, Mills observed, how a tool is implemented "is just as important as the actual technology." The most advanced recruiting analytics package doesn't do employers much good if HR and hiring managers can't make sense of the insights it's calculating.
Thus, usability will only become more important as the use of recruiting analytics grows. While Berjikly said employers with 500 or more workers tend to be the early movers -- in part "because they are absolutely suffocating from data overload" -- so much innovation is going on that "easy-to-use products can be deployed across an organization at affordable costs and provide a 100-person company with the sophistication and advantages of much larger peers."
3. Results first, technology second with recruiting analytics
For all of the technical work being done to advance recruiting analytics, many recruiters and HR professionals say they care less about the technology being used than they do a product's results.
"Organizations have always struggled with how to wade through applicants who have both the necessary skills and a reasonable chance of converting to a hire because other characteristics match -- like location, compensation, hours, desired culture and so on," Berjikly said. Recruiting analytics "provide a meaningful assist" by sorting through huge data sets and uncovering nonobvious patterns. "The payoffs are significant time savings [in] filtering enormous amounts of candidates to a manageable set of qualified prospects and improved productivity when increasing the conversion ratio from offer to hire."
William TincupPresident, RecruitingDaily
As importantly, recruiting analytics tools "can make a material change in how organizations operate their recruiting processes," Mills said. When employers integrate analytics, data and intelligence into their methods, they can better understand how well those processes are working and look for ways to identify roadblocks and inefficiencies. "Driving inefficiencies out of business is critical to sustained success," he said.
And, many experts argue, the recruiting and hiring process itself is an important component of attracting the right candidates. Companies, Tincup said, are the sum of their people. "Regardless of industry or region, it's the people that make the company win or lose. So, recruiting the right team is fundamentally crucial for all companies."
That's why business leaders should treat their recruiting process the way Coca-Cola treats its product formula, he argued. "Work like hell to discover the formula, and then protect it as it becomes a competitive advantage," Tincup said.
Recruitment analytics can be a key ingredient to the recipe, Sharma observed. "Technologies and tools like these can automate repetitive and monotonous tasks, attract the right talent, eradicate biases in recruiting, speed up the hiring process and ultimately save cost and time for organizations," he said.