In a recent survey of more than 1,000 business leaders, CEOs and other C-suite executives, they said “attracting and retaining talent” is their top concern. However, while acknowledging that talent is a critical success factor, few companies claim to be good at building — or keeping — a strong workforce. Why is this?
There may be a dozen plausible explanations for talent shortages, but one of the most important is the consistent failure of companies to take full advantage of the information they have about their own employees and candidates. Predictive analytics and other data-based technologies can help streamline the hiring process while identifying the best possible talent but more importantly a solid cultural fit.
When it comes to technology in hiring, many companies concentrate recruiting efforts on posting job openings on their websites and by leveraging social media. In fact, nearly 85 percent of HR professionals say social media has a role in hiring, usually through LinkedIn, Facebook, Instagram and Monster or other web-based options.
Social media absolutely produces viable candidates, but this form of technology is just touching the surface when it comes to identifying new hires that fit your company culture while having the personal and professional qualifications for a particular position.
Then there is the challenge of keeping good people once you have them on board. Final vetting too often boils down to a “gut check” by HR or a tech lead — and while that has proven to work, harnessing the power of the data we already own can lead to much more powerful results.
Why Predictive Analytics?
While the human element should always be at the heart of employee recruitment and retention, managers involved in the hiring process will find that predictive analytics can reduce areas of uncertainty around a candidate’s background as well as assist in identifying personal and professional qualities that will contribute to the company’s mission and profitability.
Simply put, predictive analytics involves the use of historical data to predict future outcomes. You’ve probably seen predictive analytics at work as your Google searches turn up increasingly accurate results that take into account your personal search history.
Serious business applications are widespread. Insurance companies, for example, examine historical claims to modify their future exposure to certain risks. Amazon has filed a patent for a service that will use predictive data analysis to ship products before consumers even order them.
From a talent perspective, there is an abundance of historical data about a candidate that can be generated through normal procedures, such as the filling out of a job application. Wells Fargo, the San Francisco-based bank, deploys predictive analytics with a focus on biometric data that can be verified — including a candidate’s job history, tenure at previous employers, career highlights and areas of expertise.
In all, Wells Fargo developed 65 questions for each candidate. Subject-matter experts created the questions and then tested with existing employees representing key demographics, finding correlations between its corporate culture and employee backgrounds. As a result, the bank finds “statistically significant differences” in predictive analytics-vetted employees versus those hired in the market.
With unemployment rates at an historic low, employee retention has remained a key objective for many organizations. Predictive analytics allows an employer to achieve a more in-depth analysis of what may be causing turnover in different parts of the organization. This in turn helps managers adapt quickly to change work conditions to prevent top performer turnover.
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