How To Support HR & Recruiting With Big Data

Jeremy Staffing

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Raising ITs Focus On How To Support HR & Recruiting With Big Data

Big data has exploded over the past two years, with an astonishing two quintillion bytes of data being created daily. While these hefty loads of information too large for software programs to handle have always existed to a certain extent, today’s technologies are allowing for faster methods of gathering and storage. The new IT challenge is figuring out how to put all these bytes to work. This is especially true in fields like HR where bad hiring decisions cost companies so much time and money.

Pooling Data

HR has the benefit of different types of data pulled from an endless number of sources. According to the Senior Manager of the Human Resources Services at PriceWaterhouseCoopers, Olusola Osinoiki, this information typically is split three ways:

♦ Person data
♦ Structural data, and
♦ Functional data

Person data boils down to the types of information gleaned from resumes, such as names, contact information and education. Structural data defines the role of each player within an organization. It includes job description, pay grade, department, physical location and other variables used to track employee needs and responsibilities. Functional data breaks down individual worker performance and activity into data sets such as attendance, benefits activity and payroll.

Putting Big Data to Use

“The role of IT is bigger and stronger than ever just due to the complexity of big data storage technology and the tools required to analyze,” says Jan Schiffman, Technical Director at Jobscience. HR has access to programs that will scrape and store all the information they need about their employees or potential candidates. The trick is putting that data to use.

HR and recruiting teams need to work hand-in-hand with IT in order to get the answers they need from these massive sets of information. One of the biggest questions companies have tried to answer over time is, “Who is the best candidate for this job?” Comparing data sets, such as assessing productivity markers according to education or years of experience in various roles, helps pinpoint correlations that count. Cluster analysis and building neural networks are two useful methods that IT teams can put in motion today to help in building profiles used in successful hires.

“Quality is also about avoiding ambiguity,” says Peter Larsen, CEO and founder of DataTrim. The process of putting big data to its best use begins before any information is collected, according to Knowing which questions you want answered will help you tailor your research, resulting in cleaner data sets companies can use to find solutions.

According to Jan, this points to a need for IT to understand the inner workings of HR as well. In the future, recruitment teams may grow to include a data scientist to help with research and big data analysis.

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