Join Joel Gurin and Prasanna Tambe for a free webinar on Wednesday, February 26th at 2pm ET.
In Leading with Data: Boost Your ROI with Open and Big Data Joel Gurin and Prasanna Tambe will discuss the differences and implications of open data and big data, how they are creating new jobs and businesses, and how data can be utilized.

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This animated infographic has been supplied by CareerBuilder. Excerpt from The Talent Equation by Matt Ferguson, Lorin Hitt, and Prasanna Tambe:

Large companies are undoubtedly familiar with the applications of big data, but until recently the focus has been primarily on the consumer end. Every click of our mouse and swipe of our credit card leaves behind a trail of data, and companies are racing to collect it, store it, and learn from it. As a result, segmenting consumer behavior ?rst through sales receipts and later through web analytics has revolutionized sales and marketing. It continues to evolve today. The predictive behavior models that the best consumer goods companies use are essentially able to determine what their customers want before they even know they want it. The ability to process and learn from these datasets is as important as the product or service itself to overall market performance.

Seeing this obvious success, executives around the country are now asking: What can big data do for human resources? Think about the massive amount of information a company keeps on their employees—work histories, demographic pro? les, education levels, skills competencies, compensation and bene? t ? gures, performance and productivity measures—there’s practically no end to the information residing within the typical HR department. As is the case with most data stored on servers or in file cabinets, however, human capital data is widely untouched, due to an inability or lack of initiative to steamline, process, store, and, most importantly, analyze it.

The Talent Equation is about using an incredible quantity of human capital data to create achievable solutions for leaders in the C-suite and HR. Emphasis on this topic was in part refueled by the success of the 2011 ? lm (and 2003 Michael Lewis book of the same name) Moneyball, which depicted how the mid-market, payroll-challenged Oakland A’s competed with the cash-rich ball clubs by using advanced statistics to gain a recruiting edge. Similarly, attracting, retaining, and maximizing the returns of personnel do not have to be subjective guessing games. Focused data analysis can help companies ? nd, train, and retain the right people in spite of potential skills shortages, resource limitations, and other recruiting challenges:

  • Predictive analytics on labor supply and demand are helping companies decide where to open new facilities or in which markets they’ll ?nd a higher concentration of specialized worker skill sets.
  • Smart data analysis helps organizations put an end to common screening practices like skipping over job hoppers’ resumes or candidates who’ve been unemployed for a long period of time. Evolv, an HR data research ?rm, found that new hires in these categories were no more or less likely to be ?red or leave voluntarily than other employees. Big data helps applicant-to-employer matching technologies by identifying job titles and skill sets that could lend themselves to similar positions, but are often lost in translation.
  • Real-time, market-by-market salary and compensation data helps HR leadership keep offers competitive for highly skilled workers in ?elds like IT or engineering, who often ?eld multiple offers simultaneously.
  • Candidate experience analysis helps companies rewrite how applicants interface with screening systems, resume software, and company recruiters—a process that can reduce the cost of hire and attract the best talent pool possible.