How analytics can help clients better identify, manage talent

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In 1998, consulting giant McKinsey predicted an imminent “war for talent.”

That day is here.

The current highly-competitive job market — exacerbated by long-term low unemployment and a service economy that places a premium on talent and performance — makes finding candidates who aren’t simply qualified for open positions but are motivated, likely to succeed and a good fit for corporate culture, very challenging. But HR organizations that implement effective, sophisticated hiring strategies aimed at that goal can, and will, evolve into true corporate partners, positively affecting the bottom line.

That’s the lesson from a new report by Bersin by Deloitte that calls out several key practices used by high-performing companies that have created what Bersin calls “high-maturity talent acquisition functions.” Those practices include aligning hiring with business strategy, upward mobility for employees, and workplace “values” as hiring criteria.

However, one of the most significant keys, based on Bersin’s survey of more than 1,200 talent and business leaders, involves the effective use of cutting-edge technology, in particular predictive data analytics and artificial intelligence.

The use of data analytics in hiring is evolving, with the help of big data models and machine learning algorithms, from simple “semantic analysis” — matching key words in job requirements with those in resumes — to a more evaluative and proactive function. By employing both internal and external publicly available data, analytic teams can track employee performance, forecast headcount, anticipate trends in people and skills and optimize recruiting workflows. Smart organizations “leverage predictive data to create a TA strategy,” says Robin Erickson, vice president and talent acquisition research leader at Bersin by Deloitte.

In terms of integrating analytics into the HR function, employer have options. Third-party predictive services for TA, for instance, are accessible in a cloud-based model, and they tout not only faster, friendlier, more accurate and more productive hiring “experiences,” but the ability to reduce bias in the hiring process.

“Companies that are not prioritizing analytics do so at their own risk,” according to the authors of an ambitious, wide-ranging survey of more than 10,000 HR and business leaders by Deloitte Consulting, its 2017 “Global Human Capital Trends” report.

In terms of artificial intelligence, AI tools are revamping the interview process and improving the overall candidate experience. Chatbots, voice, video, even gaming interfaces help to objectify initial candidate assessments, and savvy vendors of applicant tracking systems are front-ending them with such capabilities. “AI and a vid­eo interview may be better able to identify promis­ing candidates than a traditional interview, saving money and reducing time-to-hire,” according to Deloitte’s HCM study.

In addition, HR managers are using Robotic Process Automation (RPA) systems to address the overload of repetitive tasks related to benefits, compensation and compliance, and AI tools promise to extend RPA’s efficiency and effectiveness. IBM, for example, is working with several RPA vendors to incorporate capabilities from its AI engine Watson such as natural language processing and pattern recognition.

It’s worth noting that identifying and cultivating high-performing employees was the third most important corporate priority among Deloitte’s global respondents (slightly behind establishing an “organization of the future” and prioritizing “careers and learning”). The reason is simple. “Without the best talent, organizations don’t succeed,” Erickson says.

The trends in technology, particularly AI and data analytics, are bending toward that goal.

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