The Power of Big Data and Analytics in Recruiting
Kevin Wheeler, who will deliver the opening keynote at the first-ever Talent Acquisition Technology Conference, explains why analytics is so important in recruiting today.
By Andrew R. McIlvaine
This fall, a brand-new event brought to you by the people behind the popular HR Technology Conference® will feature the world's most renowned experts and talent acquisition leaders exploring how technology is transforming the way talent is sourced, hired and brought into leading organizations: The Talent Acquisition Technology Conference, which will be co-located with the Recruiting Trends Conference at the Hilton Austin in Texas on Nov. 15 and 16. Kevin Wheeler, entrepreneur, futurist, business advisor, thought leader and founder and chairman of the Future of Talent Institute, will present Talent Acquisition Tech's opening keynote, "The Promise and Peril of Predictive Analytics." Kevin, who spent 25 years in leadership roles at Charles Schwab Co. and Alphatec Electronics before founding the Future of Talent Institute, will address the growing use of cutting-edge tools that make it easier to analyze passive candidates and predict whether they would succeed in an organization. Wheeler will explore how this brave new world of talent acquisition offers a number of potential advantages and how it also raises critical privacy questions that can't be ignored. We recently spoke with Kevin about the importance of predictive analytics and Big Data in recruiting today and how it is changing the face of the profession.
What's at stake for companies in this area -- what sets companies that make smart use of analytics for recruiting apart from those that don't?
I think it's increasingly core to having a successful business: maximizing the talent you have while minimizing the numbers of people necessary for getting things done. Your success or failure as a company is no longer based on equipment or finance; it's almost trite to say this, but it's based on your people. When you have high quality people, you can improve the overall productivity and efficiency of your workforce by many factors. But we really have to appreciate the true value that talent analytics brings and the fact that it can help you predict whether someone's going to be a capable employee or not with good accuracy today. I think you will see more and more companies appreciate the fact that how well you do at talent analytics is going to have a direct impact on your profitability.
How do you see analytics changing the face of recruiting within the next five years?
I think it's a massive, transformational change. Now that we have all this information available, how do we make sense of it and tell a story about it that's meaningful to leadership? When you present a whole bunch of numbers, it's sort of meaningless -- turnover rates, hiring rates -- it doesn't mean anything unless you're in the field. You need to tell a story about what it means for the organization. And if you can get to predictive analytics, as in, what can you tell us about our current workforce, what we'll need in the future, these are the kind of changes we'll have to make or money we'll need to spend if we want to achieve this particular goal -- that's what recruiting is being asked to do, and I think the really good recruiting departments are beginning to figure this out and trying to put together the numbers that will help them tell this story about what's happening today and what they'll need to do in the future. It's probably not fully understood or appreciated by a lot of recruiting functions, but in five years it's going to weed out those who don't understand it or who can't figure it out.
What tends to stand in the way of recruiting departments making effective use of analytics?
Very few people in recruiting have a data mindset. There are a lot of people in recruiting who are more focused on the people side of things, but hard data, numbers, process thinking -- it's not where most of them are coming from. So for them, getting their heads around this is really hard. To ask them to take a bunch of numbers and turn them into a compelling story for someone in leadership is difficult for them. If you look at the job postings out there, there's a raft of them for analysts in the recruiting space. So that alone tells you they've heard the call, and now they're trying to figure out how to deliver. Many of them will make that change fine, and many already are. But a whole bunch, even those that hired analysts, still aren't going to be able to tell the story properly.
So how do you use this data effectively to tell a story to leadership?
Here's an example: Let's say your company's leaders say they're going to open a new location in a particular city. By using data to tell a story, you can say to leadership that "In this city there are only 200 of the engineers we're going to be looking for and we are going to have a very difficult time hiring there, and let me show you the breakdown of the available skills there, and while it may make sense economically to move to this city based on cost of living and tax breaks, from a people perspective it's going to be very expensive and difficult to find the people we need there." Historically, this would have been ignored by leadership, who would say "We're going to move there because of tax breaks" and then tell recruiting, "Go find people with these skills." So recruiting would have gone out and reactively looked for people and discovered there weren't that many and then this huge, agonizing battle to find people would have ensued and, in the end, recruiting would get penalized for not finding talent. But if they had this data on hand to present in a compelling fashion, the leadership team would have made a different decision. Talent analytics gives you the ability to support the strategic business initiatives of the company and, at the same time, lower the cost of recruiting while increasing speed and efficiency.
What's the best piece of advice you'd give with respect to vendor selection in this area?
Obviously, there's a growing volume of vendors offering different pieces of a solution in the space. I think probably the best advice you could give anyone today is to take your time, think through what you really need from an output standpoint, what you really want it be able to give to you. That's why you should have a data analyst onboard before you buy a system -- someone who knows what they need and want. And if you're thinking about switching ATS systems, you should buy one that has an open and flexible approach to analytics, that has an open API or has the capability to integrate with tools you may want to use in the future.