SourceCon

Sourcing News and Knowledge – Beyond the Obvious


Big Data

How Big Data Analytics Enables Predictive Sourcing


No comments

bigstock-big-data-exabyte-terrabyte-or--41517229 (1)

As the big data juggernaut makes its inexorable way into the world of HR, debate continues on exactly what “big data” means. Glen Cathey’s piece, “Analytics, Big Data & Moneyball HR/Recruiting for Dummies,” does a great job of advancing the idea that “for something to be defined as ‘big data,’ it should adhere to the ‘3 Vs’: Volume, Velocity, and Variety.” HR possesses data that fits all three definitions, though perhaps not on the scale of petabytes. There is data from thousands of candidates and hundreds to tens of thousands of employees; data created in daily, weekly, monthly, and quarterly cycles; and data from numerous internal systems and outside sources. The quantity, speed, and variety of the sources that comprise HR big data are relative to the business cycles, transactions, and the size of the business that HR is operating in. Simply stated, the Big in big data is scaled to whatever business function is generating the data. It is important for HR to not get confused by wording and, in the process, dismiss the compelling opportunity that big data analysis presents across the spectrum of HR sub-disciplines. Nowhere in HR is this truer than in the area of talent acquisition. Sourcing teams can capitalize on the insights derived from big data predictive analytics to be more proactive and effective and increase their strategic contribution to the company.

Related Conference Sessions

SourceCon 2014 Denver is in Denver, CO, on October 1–2, 2014. Learn more »

HR has been working hard to create and add value to organizations by moving from a focus on the transactional to the strategic. big data enables the tying in of workforce planning efforts to talent acquisition strategies. Because business cycles are moving faster than ever before, talent acquisition teams that don’t leverage big data analytics and insight to become more proactive will not only continue to find themselves frantically scrambling to fill positions, but will also risk seeing their company fall behind the competition. Leveraging big data is the key enabler for driving talent acquisition in the most efficient, cost-effective, and timely manner.

Big data collected from the candidate response behaviors on modern job boards provides a real-world, right-now example. Despite the claims of some “experts” that job boards are dead, they continue to be one of the best tools for sourcing the talent you need. CareerXroads’ 2012 Source of Hire report shows that job boards remain one of the key sources for new hires, and new research reveals that 64 percent of respondents consider job boards to be their preferred recruiting source for niche positions. Job boards are evolving to provide a gold mine of information for sourcers.

Part of job posting evolution is the ability to tag aspects of job listings that provide essential information, such as how many times a posting is being viewed and how many clicks are resulting from the views. Job board-derived big data analysis can show precisely which sources have the greatest likelihood for generating the flow of the specific types of candidates you need. This analysis can also forecast candidate volume and how long it will take to receive the majority of responses for a posting on a given board.

Big data analysis can also measure the effectiveness of a recruitment campaign so you can make necessary adjustments to improve performance. For example, analysis might reveal that Thursday is the best day of the week to post nursing jobs at NurseHires.com but that such jobs get a better response on Tuesday at WeNeedNurses.com. Big data can even tell you what times of day are best to post at each job board so that your posting gets maximum exposure.

Big data can likewise help uncover valuable trends and patterns on “click decisions” so that you can investigate why or why not a candidate takes the critical last step to apply for your posted job. You might discover an employment branding issue, or a problem with the wording of the posting, or a non-standard job title that throws candidates off. Then you can adjust accordingly.

The reality is that companies cannot attempt to point their resources—time, money, people, etc.—at every potential sourcing opportunity. Nor can they afford to waste valuable time and money sourcing from channels that have a low potential of finding them qualified candidates. Because one of the biggest line-items in a budget is job board advertising, gleaning big data’s job board insights is a better way to predict where budget dollars are best spent.

Unless you are blessed with in-house data scientists—and ones who have been assigned to HR—you will need to work, at least initially, with an outside partner who can gather and analyze the required mountains of data. Some larger organizations will want to set up their own big data shop, but it can take several years. It’s possible to run on parallel tracks, however: getting immediate access to big data’s insights via a provider while building your own infrastructure.

Don’t let the fear of statistics and charts, or the phrase “big data” itself, overwhelm you into paralysis. It is critical to take even small steps to move down the path. Those who take initial steps, ideally with help from the right external partners, will be well on their way to transforming their talent acquisition efforts and enabling their companies to achieve greater productivity and profitability. If you’re not doing this, your competitors are—and you’ll have no way of knowing how many good candidates you’ve missed out on.

David Bernstein is the head of eQuest’s new Big Data for HR/Predictive Analytics Division, which enables organizations to make evidence-based decisions about their recruiting and hiring strategy. He writes and speaks regularly on how data analytics can predict future behavioral patterns of candidates and create a competitive advantage in candidate sourcing.