Big data is a driving force behind business strategy today—and human resources is no exception. It’s given recruiters the tools they need to make better hires and is changing the way organizations measure performance, boost employee engagement, prioritize training, and analyze talent needs. HR today has access to a gold mine of data, an unprecedented amount of information: insights, intelligence, trends, future-casting.
There’s a reason the job of data scientist just ranked as the top career opportunity for 2016: There are currently more than 1,700 job openings for a job “…where demand outpaces supply,” said Scott Dobroski, Glassdoor’s career trends analyst.
Making data science one more crucial skill to add to the skills gap HR is dealing with today. But it’s worth the effort to stay on top of big data and data science – here’s why:
Why HR Needs Big Data
Recruiters have access to a lot of information about potential hires: Social media, online databases, employment records, online tests, and even contest results. This information can help them assess leadership qualities, critical thinking skills, and other hard and soft skills that can make the difference between a mediocre and remarkable employee.
For example, personality testing analyzes a candidate’s skills and personality in relation to an existing team—identifying strengths, weaknesses, and complementary skills that indicate how well he or she will fit into a particular role.
But this is only one example of why HR needs big data. In fact, a growing number of HR departments are turning to big data to improve decision-making and efficacy.
The Big Data Difference
Regardless of the industry, both recruiting and training are vital. Many enterprises see human capital as the most influential factor for long-term economic value. Here are a couple of examples of how data has helped organizations make smarter hiring decisions:
- Customer support. Xerox revitalized its call centers by analyzing information collected during a six-month period. By analyzing the data, they realized a personality assessment was a far better predictor of success than a hiring decision based predominantly on previous experience. As a result, Xerox improved employee satisfaction and cut call center turnover rates by 20 percent.
- One financial services provider had an epiphany regarding its recruiting strategy. When hiring sales staff, they were using academic excellence as a key performance indicator. However, a look at their sales productivity and turnover rate showed that wasn’t a critical factor. Instead, hiring for previous sales experience, time management skills, and resume quality made a more predictable difference. The shift in their hiring strategy led to a $4 million difference in revenue.
Why a Lack of Big Data Skills Is an Issue
Beyond more strategic recruiting, understanding data and analytics can help organizations track how training impacts employee progress, improve how and where they communicate, and gain insight into factors that affect performance and retention.
Using data to pinpoint how employees are getting burned out, for example, can lead to better hires and internal support. Predictive analytics can indicate where a candidate or employee might run into problems in the future, providing an opportunity to address potential issues proactively.
The trick is that somebody has to know how to read this information. That’s the essence of the big data skills crisis: There simply aren’t enough HR professionals who know how to gather and interpret the information available through analytics.
As I have said before, it’s not just the numbers, it’s how they’re crunched.
Finding a Data Scientist Means Thinking Outside the Box
You may have to use unconventional hiring methods to recruit talent to tackle your HR analytics. Why? First, there’s the previously mentioned talent shortage; like many other technical skills, the competition for experts can be fierce. Creative talent sourcing—like new graduates or freelancers—can improve your odds of finding a match.
However, this field is relatively new, which is why the number of data scientists falls short of demand—but that doesn’t necessarily mean the skills aren’t out there. As noted in a leading site on Business Analytics, Big Data, Data Mining, and Data Science, people working in this field may be educated as statisticians, mathematicians, or computer scientists, or they may have expertise working with data science tools like Hadoop, R, or SAS.
Data mining takes a broad spectrum of skills, so regardless of whether you use social media, crowdsourcing, or other networks to find a data scientist, you should keep an open mind.
Jump on the Big Data Bandwagon Now
Big data is infinitely useful for HR, and it’s worth investing time and resources to find the right people for your needs.
Start by looking at basic analytics and prepare your team to take a more data-centric approach to its work; identify tools that can help you succeed, and roll out any changes needed to support internal data collection. Beginners may consider outsourcing for some data help, but using a consultant to coach internal staff can be an excellent place to start, too.
Big data improves the recruiting process, making it more efficient and more reliable. It even gives organizations the information to help existing employees grow and become better workers. Businesses should start seriously thinking about finding HR analytics talent to harness data’s real potential.
A version of this post was first published on Converge on 3/22/16