Big Data

How Big Data Can Help You Find and Hire the Most Elusive Talent

Your data can work a lot harder to help recruit, engage and retain top talent.
How Big Data Can Help You Find and Hire the Most Elusive Talent
Image credit: Volker Möhrke | Getty Images
Guest Writer
Chief Data Scientist, ADP
6 min read
Opinions expressed by Entrepreneur contributors are their own.

Gone are the days when businesses had a wealth of qualified candidates competing over every job opening. With U.S. unemployment hovering around historic lows of 4 percent, a growing number of jobs being created nationwide, and more than 10,000 baby boomers retiring daily, organizations are struggling to recruit top talent from the market while retaining their current employees.

Today’s market for talent is a seller’s market, and the dynamic of hiring is changing as job hunters are now armed with assets that can give them the upper hand. Research shows that a majority of job seekers consult online, crowdsourced resources when looking for their next opportunity. Prospective recruits can see anonymous salary information, reviews of a company’s culture and values, work-life balance and career advancement opportunities. Similarly, the quality of a company’s management is becoming an increasingly decisive factor for whether employees remain at their current organizations. Research by Gallup reveals that nearly half of employees have left a job because of a bad manager, and that 70 percent of variation in team performance hinges on the team leader.

Related: What to Do When Your Growth Has Stalled

But not all is lost for employers. They are already sitting on a wealth of data that, if leveraged properly, can be a powerful tool in attracting top talent, enabling those workers to do their best work, and retaining them for the long haul. Data can help companies bring precision to the hiring process by sourcing better-fitting candidates, benchmarking and broadcasting their superior management to candidates throughout the recruitment process, and spotting and addressing weaknesses among managers that might be leading to unengaged employees.

Sourcing the right candidates from the start.

Transparency is becoming an increasingly important value in the hiring process. Employers want to know that they are hiring candidates who are interested in the company, qualified for the position and pose a low flight-risk. Meanwhile, candidates want to know they are entering into a position that is aligned with their skill sets and career path, and that the workplace offers a good culture and engaging management. Employers can respond to an era of greater transparency by using data to source candidates that are a better fit off the bat.

How so? Through automation and big data. Earlier, companies had little to guide them on a potential applicant’s future flight risk other than gut feeling. Now, tools integrated with artificial intelligence (AI) and deep analytic capabilities can parse the data on your company’s current employees -- including their prior experiences, skills and latest achievements -- to learn what good candidates look like based on past hiring decisions. In addition to your own enterprise data, AI can look at data from across the industry to build a profile that can then be applied to cull resumes, screen candidates based on warning signs, and grade and rank a shortlist of qualified candidates for each job opening.

Related: Are You Hiring the Best Candidate for the Job or the One You Like the Most?

Measuring (and marketing) the previously unknowable.

ADP research shows that 61 percent of employees are either actively or passively looking for new opportunities. The top reason employees are looking to leave? A poor relationship with their direct manager. This points to an issue contributing to talent retention. Still today, many companies don’t organize their recruitment efforts around the fact that employees don’t leave jobs, they leave managers.

We’re quickly approaching a future, however, where big data will be able to measure what was previously unknowable -- benchmarking management quality against the industry standard. By collecting data on retention, engagement, performance and attrition from team to team, companies can determine whether their managers meet, exceed or fall short of the benchmark.

The quality of a good manager can be measured by the engagement and retention among their team members, and even harder business metrics that indicate their team’s performance, such as financial returns and client satisfaction. Benchmarking this against the industry, you might discover that engagement among teams with certain managers is well above industry average, which can be conveyed to candidates in a provable way throughout the recruiting and hiring process, appealing to candidates based on their actual desires.

The team leader 2.0: Data-enabled managers.

Given that so much hinges on the employee-manager relationship, it’s important to make sure team leaders are likeable, helpful and invested in the development of those who they manage. The problem is: qualitative performance reviews don’t cut it. Managers simply don’t always have the hours in the day to take care of core business needs and also ensure their team members are fully supported. But, this doesn’t have to be a big lift, especially when a business leverages the right tools.

Related: 4 Hiring Practices You Needed to Drop Yesterday (and What to Do Instead)

Data and predictive analytics can help bring actionable insights front-and-center for managers to help them understand how to better support their team members. For example, data- fueled intelligence can identify when a team member is at high risk of leaving because they’ve been in their role for too long or could be getting “burnt out.” This information can signal a manager to pay more specific attention to that team member, offer new assignments or develop more regular check-ins with the unengaged employee.

Has a large team recently lost several members? That’s cause to investigate, and data analytics tools can monitor and help predict these situations before it’s too late. You might find that 20 people reporting to one manager is way above the industry benchmark for that department, leading to low engagement and retention. Or that management styles differ greatly between high- and low-turnover teams, showing the path for how one style can inform another. This gives businesses an opportunity to course correct by adjusting staffing plans as well as addressing any other statistical outliers among managers.

Big data analytics, once thought to be a novelty, are now commonplace. And they can benefit job seekers and employers. Now, companies of any size can leverage data they might not have even realized was useful in the past to gain a competitive advantage in the labor market. Those who apply their internal engagement statistics, employee profiles and management data to the job market can more easily source, secure and sustain talent that is exactly right for their business -- at a time when they need to more than ever.

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