Analytics is HR's ticket to boardroom respect and business clout — by becoming data-driven, HR can provide the hard evidence and figures that chief executives and finance directors love. Analytics has become a driving force between both marketing and finance in recent years, so why should human resources be any different?
The majority of senior HR professionals "get" this message. But there's one problem: Putting people analytics into practice is harder than it seems.
A big part of the challenge in building people analytics expertise is simply overcoming the traditional HR structure — transforming the people-focused nature of the industry into a data-driven one not only requires a shift in perspective, but also an entirely new set of skills.
The short supply of mathematical and analytical skills in talent management stymies the uptake of HR analytics. A recent Deloitte study found that while three-quarters of companies believe analytics is important, a dismal 8 percent felt their organizations were actually strong in the area.
It can be quite costly to acquire the right skills, too. A Burtch Works survey, for example, found that an entry-level data science role rakes in a median base salary of $91,000. Of course, given unlimited budget and a fabulous brand, it would be no problem to build a full-time team of talented people. But for most of the corporate world, different tactics (and slow steps) are required.
Before your team goes truffling for analytics talent to bring on, of course, you need to understand exactly what you should be looking for. Analytics is not a solo sport and an entry-level data scientist won't cut it. It takes a team of skilled people to truly do analytics right.
There are roughly three skill sets needed: 1) a deep understanding of HR and business, 2) an ability to pull together the data and 3) knowledge of statistical modeling. So, where can you find these skills?
First, look inside the HR department. There may be people within the existing team already demonstrating an aptitude for statistics, or who used it as part of their degree (psychology, for example, has a statistical component to it). With a little training and encouragement, these are the kinds of people who can start making HR data talk.
Alternatively, there may be people from other parts of the company who can move into HR, either on a rotation to share their knowledge or as a permanent move. Employees in the finance department, for example, should be masters at using analytics. Borrow some of their expertise or partner with them to get started.
If you can't afford permanent members on your staff, bring in contractors or consultants for specific tasks. Or even contact local universities to see if any of their students are interested in hands-on experience to bolster their studies. Starting with outsourced talent may actually help provide the proof of concept you need to increase your team's budget.
Eventually, there will come a time when borrowing people isn't enough and you need to start hiring.
Competition is tough, so you'll need to stand out from the crowd. Because HR is usually new analytics territory, it will appeal to ambitious analytics or data experts looking for a challenge. Instead of simply focusing on the technical requirements for the job, discuss the opportunities and untapped possibilities of big data for talent management.
This is particularly true if you're aiming to lure the rarest of analytics beasts: the data scientist. These highly sought-after experts have an unusual mix of skills, but what motivates them above all else are new challenges and the ability to use their creativity. If you can promise autonomy and an enticing mix of projects, you will stand a better chance of attracting top analytics talent.
While it is far from easy or quick to get up to full speed with HR analytics, it is also a journey that needs to be started. If HR doesn't start doing HR analytics, another department in the company will. In fact, according to research by Harvard Business Review and Visier, 9 percent of organizations have already shifted people analytics out of HR's clutches altogether.
Do you really want to cede control over how data informs talent management to another department? Didn't think so.
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