Most Impactful Tech of the Year: Big Data Analytics

What is the value of an employee? Squeezed by decreased funding and increased pressures to perform, HR professionals want the answer to that question — but are often left sloshing through a sea of data.

Thanks to new technology, employee information springs seemingly eternal from almost every facet of the enterprise, from retention tactics to benefits satisfaction and engagement rates. A whole subsection of the HR tech market claims it can organize that data, with varying degrees of success.

Its growing necessity in the field, as well as the outsized positive impacts it can have on an organization, makes Big Data analytics our winner for most Impactful Tech of the Year.

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Access to that tech, however, is one of the central conflicts surrounding its rise. While most recognize its importance, only one in three HR managers has access to any kind of predictive analytics. Not understanding the actual value of employees can lead to massive spending with few calculable results, potentially putting HR in a bad position with the other aspects of the organization, Michael Gretczko, principal at Deloitte, said. And most HR professionals are at least aware of that.

“Many of the clients we have worked with aren’t sure how to take that first step,” Gretczko said. “‘I know we should use data, but to what end?’”

In fairness, HR leaders may start at a slight disadvantage, Ravin Jesuthasan, managing director at Willis Towers Watson, told HR Dive. The newer demands on the profession can feel like they came from left field, largely because until recently, HR was seen as a processes profession rather than a strategic one.

But those that have found their niche with big data have transformed their HR departments into people-first organizations that buoy the beating heart of the enterprise.

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Recruiting and engagement have seen huge advancements thanks to big data analytics, for example. Recruiting efforts can generate a “tremendous amount” of data, creating an opportunity for prepared departments, Jesuthasan said. Recruitment data, such as time to hire and successful hiring, can integrate with data from social media and assessment tests to create a more thorough picture of candidates and hiring pools.

Managing data drives profitability. The use of predictive analytics is “the biggest recruiting trend” in 2018, according to Greg Moran, president and CEO of Outmatch.

“How do we know? We surveyed nearly 200 HR professionals and they told us loudly and with one voice: there is a better way to hire, and it starts with predictive analytics,” Moran told HR Dive.

Gretczko agrees, noting that analytics has led to a “revolution” in talent acquisition, now that machines can identify candidates that may be a good fit for companies.

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But analytics arguably has more room to grow in the employee engagement space. Managers now have access to demographic, transactional and behavioral data on employees, opening up what Gretczko calls the “science of engagement.” In other words: How do you get into your employees’ heads?

To find out, more HR managers are turning to data storytelling: in essence, finding the story that interconnected pieces of data tell. It’s not a “run of the mill” analytics skill set, Karen Crone, CHRO at Paycor, said, but it’s increasingly important for employers that want to compete.

Getting manager buy-in for the use of data and analytics will be key. HR will have to focus on efficiency and scaling to simplify their work, all while keeping an eye on the potential pitfalls. HR also will need to get better at illustrating the tremendous benefits of using data analytics, whether implemented to create robust candidate pipelines or the ability to quickly screen talent. Data analytics are the future of the profession, and will inevitably lead to AI-driven HR processes. Those HR managers who realize its value early on will see the most success.

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